Hospital Medicine

“In the end, we will remember not the words of our enemies, but the silence of our friends.”

—Martin Luther King, Jr.

"Code Blue, Emergency Department Code Team to PACU.” A female senior resident dons her personal protective equipment and assembles her team. An enthusiastic male junior resident asks if he can accompany her, and off they go. They encounter a frantic scene in the post-anesthesia care unit (PACU). Before the senior resident can lead the rapid response, a PACU nurse addresses the junior resident: “You are leading the code, correct? What medications would you like?”

“Microaggressions” are subtle, commonplace exchanges that—whether intentional or unintentional—communicate disparaging messages to members of marginalized groups.¹ These groups often include women, members of racial/ethnic groups that are underrepresented in medicine, and lesbian, gay, bisexual, transgender, and queer/questioning (LGBTQ) individuals. Although an individual may not intend to cause harm, their words may still negatively impact the receiving party, who regularly experiences differential treatment based on sex, race, ethnicity, or other social identities. The effects of microaggressions extend beyond personal offense to include anxiety, depression, and even hypertension.^1,2

Addressing microaggressions can be challenging. Given that the recipients of microaggressions are often burdened with responding to them, it is important for bystanders to be empowered to respond as well. A bystander witnesses and recognizes the microaggression and can address it. Based on the work of Sue et al,³ we suggest that bystanders adopt the following strategies:

• Make the “invisible” visible. Many people do not perceive their actions as biased or prejudiced. It is therefore important to bring the implicit bias to the forefront by asking for clarification, naming the implication, or challenging the stereotype.
• Disarm the microaggression. Don’t be afraid to stop, deflect, disagree, or challenge what was said or done, thereby highlighting its potentially harmful impact. Another option is to interrupt the comment as it’s being said and redirect the conversation.
• Educate the speaker. Create a nonpunitive discussion by appealing to common values, promoting empathy, and increasing awareness of societal benefits. The speaker may become defensive and emphasize that their intent was not to cause harm. You must emphasize that, regardless of intent, the impact was hurtful. You may refocus the discussion with a simple statement such as, “I know you meant well, and…”
• Seek external support when needed. Addressing microaggressions can be emotionally taxing. Don’t be afraid to utilize community services, find a support group, or seek advice from professionals.

By virtue of being a neutral third party, bystanders who intervene may have greater success at explaining the impact of the microaggression. In doing so, the bystander also relieves the recipient of the microaggression of a burdensome response. In the above example, another provider in the PACU might pull the nurse aside later and say, “When you asked the junior resident if he was leading the code, you unintentionally indicated that he was the most experienced, which made it more challenging for the female senior resident to lead the response.” In this way, the “invisible” implication of the nurse’s words—that the male resident was the most knowledgeable physician in the room—is made visible, and the female resident is relieved of responding.

Microaggressions do not occur in a vacuum; context matters. Before employing these strategies, consider when, where, and how you address microaggressions. These strategies validate and support those on the receiving end of microaggressions, and thus counteract their deleterious effects. The onus is on us: we must not be silent.

The authors have nothing to disclose.

“In the end, we will remember not the words of our enemies, but the silence of our friends.”

—Martin Luther King, Jr.

"Code Blue, Emergency Department Code Team to PACU.” A female senior resident dons her personal protective equipment and assembles her team. An enthusiastic male junior resident asks if he can accompany her, and off they go. They encounter a frantic scene in the post-anesthesia care unit (PACU). Before the senior resident can lead the rapid response, a PACU nurse addresses the junior resident: “You are leading the code, correct? What medications would you like?”

“Microaggressions” are subtle, commonplace exchanges that—whether intentional or unintentional—communicate disparaging messages to members of marginalized groups.¹ These groups often include women, members of racial/ethnic groups that are underrepresented in medicine, and lesbian, gay, bisexual, transgender, and queer/questioning (LGBTQ) individuals. Although an individual may not intend to cause harm, their words may still negatively impact the receiving party, who regularly experiences differential treatment based on sex, race, ethnicity, or other social identities. The effects of microaggressions extend beyond personal offense to include anxiety, depression, and even hypertension.^1,2

Addressing microaggressions can be challenging. Given that the recipients of microaggressions are often burdened with responding to them, it is important for bystanders to be empowered to respond as well. A bystander witnesses and recognizes the microaggression and can address it. Based on the work of Sue et al,³ we suggest that bystanders adopt the following strategies:

• Make the “invisible” visible. Many people do not perceive their actions as biased or prejudiced. It is therefore important to bring the implicit bias to the forefront by asking for clarification, naming the implication, or challenging the stereotype.
• Disarm the microaggression. Don’t be afraid to stop, deflect, disagree, or challenge what was said or done, thereby highlighting its potentially harmful impact. Another option is to interrupt the comment as it’s being said and redirect the conversation.
• Educate the speaker. Create a nonpunitive discussion by appealing to common values, promoting empathy, and increasing awareness of societal benefits. The speaker may become defensive and emphasize that their intent was not to cause harm. You must emphasize that, regardless of intent, the impact was hurtful. You may refocus the discussion with a simple statement such as, “I know you meant well, and…”
• Seek external support when needed. Addressing microaggressions can be emotionally taxing. Don’t be afraid to utilize community services, find a support group, or seek advice from professionals.

By virtue of being a neutral third party, bystanders who intervene may have greater success at explaining the impact of the microaggression. In doing so, the bystander also relieves the recipient of the microaggression of a burdensome response. In the above example, another provider in the PACU might pull the nurse aside later and say, “When you asked the junior resident if he was leading the code, you unintentionally indicated that he was the most experienced, which made it more challenging for the female senior resident to lead the response.” In this way, the “invisible” implication of the nurse’s words—that the male resident was the most knowledgeable physician in the room—is made visible, and the female resident is relieved of responding.

Microaggressions do not occur in a vacuum; context matters. Before employing these strategies, consider when, where, and how you address microaggressions. These strategies validate and support those on the receiving end of microaggressions, and thus counteract their deleterious effects. The onus is on us: we must not be silent.

The authors have nothing to disclose.

“In the end, we will remember not the words of our enemies, but the silence of our friends.”

—Martin Luther King, Jr.

"Code Blue, Emergency Department Code Team to PACU.” A female senior resident dons her personal protective equipment and assembles her team. An enthusiastic male junior resident asks if he can accompany her, and off they go. They encounter a frantic scene in the post-anesthesia care unit (PACU). Before the senior resident can lead the rapid response, a PACU nurse addresses the junior resident: “You are leading the code, correct? What medications would you like?”

“Microaggressions” are subtle, commonplace exchanges that—whether intentional or unintentional—communicate disparaging messages to members of marginalized groups.¹ These groups often include women, members of racial/ethnic groups that are underrepresented in medicine, and lesbian, gay, bisexual, transgender, and queer/questioning (LGBTQ) individuals. Although an individual may not intend to cause harm, their words may still negatively impact the receiving party, who regularly experiences differential treatment based on sex, race, ethnicity, or other social identities. The effects of microaggressions extend beyond personal offense to include anxiety, depression, and even hypertension.^1,2

Addressing microaggressions can be challenging. Given that the recipients of microaggressions are often burdened with responding to them, it is important for bystanders to be empowered to respond as well. A bystander witnesses and recognizes the microaggression and can address it. Based on the work of Sue et al,³ we suggest that bystanders adopt the following strategies:

• Make the “invisible” visible. Many people do not perceive their actions as biased or prejudiced. It is therefore important to bring the implicit bias to the forefront by asking for clarification, naming the implication, or challenging the stereotype.
• Disarm the microaggression. Don’t be afraid to stop, deflect, disagree, or challenge what was said or done, thereby highlighting its potentially harmful impact. Another option is to interrupt the comment as it’s being said and redirect the conversation.
• Educate the speaker. Create a nonpunitive discussion by appealing to common values, promoting empathy, and increasing awareness of societal benefits. The speaker may become defensive and emphasize that their intent was not to cause harm. You must emphasize that, regardless of intent, the impact was hurtful. You may refocus the discussion with a simple statement such as, “I know you meant well, and…”
• Seek external support when needed. Addressing microaggressions can be emotionally taxing. Don’t be afraid to utilize community services, find a support group, or seek advice from professionals.

By virtue of being a neutral third party, bystanders who intervene may have greater success at explaining the impact of the microaggression. In doing so, the bystander also relieves the recipient of the microaggression of a burdensome response. In the above example, another provider in the PACU might pull the nurse aside later and say, “When you asked the junior resident if he was leading the code, you unintentionally indicated that he was the most experienced, which made it more challenging for the female senior resident to lead the response.” In this way, the “invisible” implication of the nurse’s words—that the male resident was the most knowledgeable physician in the room—is made visible, and the female resident is relieved of responding.

Microaggressions do not occur in a vacuum; context matters. Before employing these strategies, consider when, where, and how you address microaggressions. These strategies validate and support those on the receiving end of microaggressions, and thus counteract their deleterious effects. The onus is on us: we must not be silent.

The authors have nothing to disclose.

From the University of California San Francisco (Dr. Treadwell, Dr. Hessler, Yumei Chen, Swapandeep Mushiana, Dr. Potter, and Dr. Vichinsky), the University of California Los Angeles (Dr. Jacob), and the University of California Berkeley (Alex Chen).

Abstract

• Objective: Adolescents and adults with sickle cell disease (SCD) face pervasive disparities in health resources and outcomes. We explored barriers to and facilitators of care to identify opportunities to support implementation of evidence-based interventions aimed at improving care quality for patients with SCD.
• Methods: We engaged a representative sample of adolescents and adults with SCD (n = 58), health care providers (n = 51), and community stakeholders (health care administrators and community-based organization leads (n = 5) in Northern California in a community-based needs assessment. We conducted group interviews separately with participant groups to obtain in-depth perspectives. Adolescents and adults with SCD completed validated measures of pain interference, quality of care, self-efficacy, and barriers to care. Providers and community stakeholders completed surveys about barriers to SCD care.
• Results: We triangulated qualitative and quantitative data and found that participants with SCD (mean age, 31 ± 8.6 years), providers, and community stakeholders emphasized the social and emotional burden of SCD as barriers. Concrete barriers agreed upon included insurance and lack of resources for addressing pain impact. Adolescents and adults with SCD identified provider issues (lack of knowledge, implicit bias), transportation, and limited social support as barriers. Negative encounters with the health care system contributed to 84% of adolescents and adults with SCD reporting they chose to manage severe pain at home. Providers focused on structural barriers: lack of access to care guidelines, comfort level with and knowledge of SCD management, and poor care coordination.
• Conclusion: Strategies for improving access to compassionate, evidence-based quality care, as well as strategies for minimizing the burden of having SCD, are warranted for this medically complex population.

Keywords: barriers to care; quality of care; care access; care coordination.

Sickle cell disease (SCD), an inherited chronic medical condition, affects about 100,000 individuals in the United States, a population that is predominantly African American.¹ These individuals experience multiple serious and life-threatening complications, most frequently recurrent vaso-occlusive pain episodes,² and they require interactions with multidisciplinary specialists from childhood. Because of advances in treatments, the majority are reaching adulthood; however, there is a dearth of adult health care providers with the training and expertise to manage their complex medical needs.³ Other concrete barriers to adequate SCD care include insurance and distance to comprehensive SCD centers.^4,5

Social, behavioral, and emotional factors may also contribute to challenges with SCD management. SCD may limit daily functional abilities and lead to diminished overall quality of life.^6,7 Some adolescents and adults may require high doses of opioids, which contributes to health care providers’ perceptions that there is a high prevalence of drug addiction in the population.^8,9 These providers express negative attitudes towards adults with SCD, and, consequently, delay medication administration when it is acutely needed and provide otherwise suboptimal treatment.^8,10,11 Adult care providers may also be uncomfortable with prescribing and managing disease-modifying therapies (blood transfusion, hydroxyurea) that have established efficacy.^12-17

As 1 of 8 programs funded by the National Heart, Lung, and Blood Institute’s (NHLBI) Sickle Cell Disease Implementation Consortium (SCDIC), we are using implementation science to reduce barriers to care and improve quality of care and health care outcomes in SCD.^18,19 Given that adolescents and adults with SCD experience high mortality, severe pain, and progressive decline in their ability to function day to day, and also face lack of access to knowledgeable, compassionate providers in primary and emergency settings, the SCDIC focuses on individuals aged 15 to 45 years.^6,8,9,11,12

Our regional SCDIC program, the Sickle Cell Care Coordination Initiative (SCCCI), brings together researchers, clinicians, adolescents, and adults with SCD and their families, dedicated community members, policy makers, and administrators to identify and address barriers to health care within 5 counties in Northern California. One of our first steps was to conduct a community-based needs assessment, designed to inform implementation of evidence-based interventions, accounting for unique contextual factors in our region.

Conceptual Framework for Improving Medical Practice

Our needs assessment is guided by Solberg’s Conceptual Framework for Improving Medical Practice (Figure 1).²⁰ Consistent with the overarching principles of the SCDIC, this conceptual framework focuses on the inadequate implementation of evidence-based guidelines, and on the need to first understand multifactorial facilitators and barriers to guideline implementation in order to effect change. The framework identifies 3 main elements that must be present to ensure improvements in quality-of-care processes and patient outcomes: priority, change process capability, and care process content. Priority refers to ample resource allocation for the specific change, as well as freedom from competing priorities for those implementing the change. Change process capability includes strong, effective leadership, adequate infrastructure for managing change (including resources and time), change management skills at all levels, and an established clinical information system. Care process content refers to context and systems-level changes, such as delivery system redesign as needed, support for self-management to lessen the impact of the disease, and decision support.^21-23

The purpose of our community-based needs assessment was to evaluate barriers to care and quality of care in SCD, within Solberg’s conceptual model for improving medical practice. The specific aims were to evaluate access and barriers to care (eg, lack of provider expertise and training, health care system barriers such as poor care coordination and provider communication); evaluate quality of care; and assess patient needs related to pain, pain interference, self-efficacy, and self-management for adolescents and adults with SCD. We gathered the perspectives of a representative community of adolescents and adults with SCD, their providers, and community stakeholders in order to examine barriers, quality of life and care, and patient experiences in our region.

Methods

Design

In this cross-sectional study, adolescents and adults with SCD, their providers, and community stakeholders participated in group or individual qualitative interviews and completed surveys between October 2017 and March 2018.

Setting and Sample

Recruitment flyers were posted on a regional SCD-focused website, and clinical providers or a study coordinator introduced information about the needs assessment to potential participants with SCD during clinic visits at the participating centers. Participants with SCD were eligible if they had any diagnosis of SCD, were aged 15 to 48 years, and received health services within 5 Northern California counties (Alameda, Contra Costa, Sacramento, San Francisco, and Solano). They were excluded if they did not have a SCD diagnosis or had not received health services within the catchment area. As the project proceeded, participants were asked to refer other adolescents and adults with SCD for the interviews and surveys (snowball sampling). Our goal was to recruit 50 adolescents and adults with SCD into the study, aiming for 10 representatives from each county.

Providers and community stakeholders were recruited via emails, letters and informational flyers. We engaged our partner, the Sickle Cell Data Collection Program,² to generate a list of providers and institutions that had seen patients with SCD in primary, emergency, or inpatient settings in the region. We contacted these institutions to describe the SCCCI and invite participation in the needs assessment. We also invited community-based organization leads and health care administrators who worked with SCD to participate. Providers accessed confidential surveys via a secure link on the study website or completed paper versions. Common data collected across providers included demographics and descriptions of practice settings.

Participants were eligible to be part of the study if they were health care providers (physicians and nurses) representing hematology, primary care, family medicine, internal medicine, or emergency medicine; ancillary staff (social work, psychology, child life); or leaders or administrators of clinical or sickle cell community-based organizations in Northern California (recruitment goal of n = 50). Providers were excluded if they practiced in specialties other than those noted or did not practice within the region.

Data Collection Procedures

After providing assent/consent, participating adolescents and adults with SCD took part in individual and group interviews and completed survey questionnaires. All procedures were conducted in a private space in the sickle cell center or community. Adolescents and adults with SCD completed the survey questionnaire on a tablet, with responses recorded directly in a REDCap (Research Electronic Data Capture) database,²⁴ or on a paper version. Interviews lasted 60 (individual) to 90 (group) minutes, while survey completion time was 20 to 25 minutes. Each participant received a gift card upon completion as an expression of appreciation. All procedures were approved by the institutional review boards of the participating health care facilities.

Group and Individual Interviews

Participants with SCD and providers were invited to participate in a semi-structured qualitative interview prior to being presented with the surveys. Adolescents and adults with SCD were interviewed about barriers to care, quality of care, and pain-related experiences. Providers were asked about barriers to care and treatments. Interview guides were modified for community-based organization leaders and health care administrators who did not provide clinical services. Interview guides can be found in the Appendix. Interviews were conducted by research coordinators trained in qualitative research methods by the first author (MT). As appropriate with semi-structured interviews, the interviewers could word questions spontaneously, change the order of questions for ease of flow of conversation, and inform simultaneous coding of interviews with new themes as those might arise, as long as they touched on all topics within the interview guide.²⁵ The interview guides were written, per qualitative research standards, based on the aims and purpose of the research,²⁶ and were informed by existing literature on access and barriers to care in SCD, quality of care, and the needs of individuals with SCD, including in relation to impact of the disease, self-efficacy, and self-management.

Interviewees participated in either individual or group interviews, but not both. The decision for which type of interview an individual participated in was based on 2 factors: if there were not comparable participants for group interviews (eg, health care administrator and community-based organization lead), these interviews were done individually; and given that we were drawing participants from a 5-county area in Northern California, scheduling was challenging for individuals with SCD with regard to aligning schedules and traveling to a central location where the group interviews were conducted. Provider group interviews were easier to arrange because we could schedule them at the same time as regularly scheduled meetings at the participants’ health care institutions.

Interview Data Gathering and Analysis

Digital recordings of the interviews were cleaned of any participant identifying data and sent for transcription to an outside service. Transcripts were reviewed for completeness and imported into NVivo (www.qsrinternational.com), a qualitative data management program.

A thematic content analysis and deductive and inductive approaches were used to analyze the verbatim transcripts generated from the interviews. The research team was trained in the use of NVivo software to facilitate the coding process. A deductive coding scheme was initially used based on existing concepts in the literature regarding challenges to optimal SCD care, with new codes added as the thematic content analyses progressed. The initial coding, pattern coding, and use of displays to examine the relationships between different categories were conducted simultaneously.^27,28 Using the constant comparative method, new concepts from participants with SCD and providers could be incorporated into subsequent interviews with other participants. For this study, the only additional concepts added were in relation to participant recruitment and retention in the SCDIC Registry. Research team members coded transcripts separately and came together weekly, constantly comparing codes and developing the consensus coding scheme. Where differences between coders existed, code meanings were discussed and clarified until consensus was reached.²⁹

Quantitative data were analyzed using SPSS (v. 25, Chicago, IL). Descriptive statistics (means, standard deviations, frequencies, percentages) were used to summarize demographics (eg, age, gender, and race), economic status, and type of SCD. No systematic differences were detected from cases with missing values. Scale reliabilities (ie, Cronbach α) were evaluated for self-report measures.

Measurement

Adolescents and adults with SCD completed items from the PhenX Toolkit (consensus measures for Phenotypes and eXposures), assessing sociodemographics (age, sex, race, ethnicity, educational attainment, occupation, marital status, annual income, insurance), and clinical characteristics (sickle cell diagnosis and emergency department [ED] and hospital utilization for pain).³⁰

Pain Interference Short Form (Patient-Reported Outcomes Measurement Information System [PROMIS]). The Pain Interference Form consists of 8 items that assess the degree to which pain interfered with day-to-day activities in the previous 7 days at home, including impacts on social, cognitive, emotional, and physical functioning; household chores and recreational activities; sleep; and enjoyment in life. Reliability and validity of the PROMIS Pain Interference Scale has been demonstrated, with strong negative correlations with Physical Function Scales (r = 0.717, P < 0.01), indicating that higher scores are associated with lower function (β = 0.707, P < 0.001).³¹ The Cronbach α estimate for the other items on the pain interference scale was 0.99. Validity analysis indicated strong correlations with pain-related domains: BPI Interference Subscale (rho = 0.90), SF-36 Bodily Pain Subscale (rho = –0.84), and 0–10 Numerical Rating of Pain Intensity (rho = 0.48).³²

Adult Sickle Cell Quality of Life Measurement Information System (ASCQ-Me) Quality of Care (QOC). ASCQ-Me QOC consists of 27 items that measure the quality of care that adults with SCD have received from health care providers.³³ There are 3 composites: provider communication (quality of patient and provider communication), ED care (quality of care in the ED), and access (to routine and emergency care). Internal consistency reliability for all 3 composites is greater than 0.70. Strong correlations of the provider communication composite with overall ratings of routine care (r = 0.65) and overall provider ratings (r = 0.83) provided evidence of construct validity. Similarly, the ED care composite was strongly correlated with overall ratings of QOC in the ED, and the access composite was highly correlated with overall evaluations of ED care (r = 0.70). Access, provider interaction, and ED care composites were reliable (Cronbach α, 0.70–0.83) and correlated with ratings of global care (r = 0.32–0.83), further indicating construct validity.³³

Sickle Cell Self-Efficacy Scale (SCSES). The SCSES is a 9-item, self-administered questionnaire measuring perceptions of the ability to manage day-to-day issues resulting from SCD. SCSES items are scored on a 5-point scale ranging from Not sure at all (1) to Very sure (5). Individual item responses are summed to give an overall score, with higher scores indicating greater self-efficacy. The SCSES has acceptable reliability (r = 0.45, P < 0.001) and validity (α = 0.89).^34,35

Sickle Cell Disease Barriers Checklist. This checklist consists of 53 items organized into 8 categories: insurance, transportation, accommodations and accessibility, provider knowledge and attitudes, social support, individual barriers such as forgetting or difficulties understanding instructions, emotional barriers (fear, anger), and disease-related barriers. Participants check applicable barriers, with a total score range of 0 to 53 and higher scores indicating more barriers to care. The SCD Barriers Checklist has demonstrated face validity and test-retest reliability (Pearson r = 0.74, P < 0.05).⁵

ED Provider Checklist. The ED provider survey is a checklist of 14 statements pertaining to issues regarding patient care, with which the provider rates level of agreement. Items representing the attitudes and beliefs of providers towards patients with SCD are rated on a Likert-type scale, with level of agreement indicated as 1 (strongly disagree) to 6 (strongly agree). The positive attitudes subscale consists of 4 items (Cronbach α= 0.85), and the negative attitudes subscale consists of 6 items (Cronbach α = 0.89). The Red-Flag Behaviors subscale includes 4 items that indicate behavior concerns about drug-seeking, such as requesting specific narcotics and changing behavior when the provider walks in.^8,36,37

Sickle cell and primary care providers also completed a survey consisting of sets of items compiled from existing provider surveys; this survey consisted of a list of 16 barriers to using opioids, which the providers rated on a 5-point Likert-type scale (1, not a barrier; 5, complete barrier).^13,16,38 Providers indicated their level of experience with caring for patients with SCD; care provided, such as routine health screenings; and comfort level with providing preventive care, managing comorbidities, and managing acute and chronic pain. Providers were asked what potential facilitators might improve care for patients with SCD, including higher reimbursement, case management services, access to pain management specialists, and access to clinical decision-support tools. Providers responded to specific questions about management with hydroxyurea (eg, criteria for, barriers to, and comfort level with prescribing).³⁹ The surveys are included in the Appendix.

Triangulation

Data from the interviews and surveys were triangulated to enhance understanding of results generated from the different data sources.⁴⁰ Convergence of findings, different facets of the same phenomenon, or new perspectives were examined.

Qualitative Data

Adolescents and adults with SCD (n = 55) and health care providers and community stakeholders (n = 56) participated in group or individual interviews to help us gain an in-depth understanding of the needs and barriers related to SCD care in our 5-county region. Participants with SCD described their experiences, which included stigma, racism, labeling, and, consequently, stress. They also identified barriers such as lack of transportation, challenges with insurance, and lack of access to providers who were competent with pain management. They reported that having SCD in a health care system that was unable to meet their needs was burdensome.

Barriers to Care and Treatments. Adolescents and adults indicated that SCD and its sequelae posed significant barriers to health care. Feelings of tiredness and pain make it more difficult for them to seek care. The emotional burden of SCD (fear and anger) was a frequently cited barrier, which was fueled by previous negative encounters with the health care system. All adolescents and adults with SCD reported that they knew of stigma in relation to seeking pain management that was pervasive and long-standing, and the majority reported they had directly experienced stigma. They reported that being labeled as “drug-seekers” was typical when in the ED for pain management. Participants articulated unconscious bias or overt racism among providers: “people with sickle cell are Black ... and Black pain is never as valuable as White pain” (25-year-old male). Respondents with SCD described challenges to the credibility of their pain reports in the ED. They reported that ED providers expressed doubts regarding the existence and/or severity of their pain, consequently creating a feeling of disrespect for patients seeking pain relief. The issue of stigma was mentioned by only 2 of 56 providers during their interviews.

Lack of Access to Knowledgeable, Compassionate Providers. Lack of access to knowledgeable care providers was another prevalent theme expressed by adolescents and adults with SCD. Frustration occurred when providers did not have knowledge of SCD and its management, particularly pain assessment. Adolescents and adults with SCD noted the lack of compassion among providers: “I’ve been kicked out of the hospital because they felt like okay, well we gave you enough medication, you should be all right” (29-year-old female). Providers specifically mentioned lack of compassion and knowledge as barriers to SCD care much less often during their interviews compared with the adolescents and adults with SCD.

Health Care System Barriers. Patient participants often expressed concerns about concrete and structural aspects of care. Getting to their appointments was a challenge for half of the interviewees, as they either did not have access to a vehicle or could not afford to travel the needed distance to obtain quality care. Even when hospitals were accessible by public transportation, those with excruciating pain understandably preferred a more comfortable and private way to travel: “I would like to change that, something that will be much easier, convenient for sickle cell patients that do suffer with pain, that they don’t have to travel always to see the doctor” (30-year-old male).

Insurance and other financial barriers also played an important role in influencing decisions to seek health care services. Medical expenses were not covered, or co-pays were too high. The Medicaid managed care system could prevent access to knowledgeable providers who were not within network. Such a lack of access discouraged some adolescents and adults with SCD from seeking acute and preventive care.

Transition From Pediatric to Adult Care. Interviewees with SCD expressed distress about the gap between pediatric and adult care. They described how they had a long-standing relationship with their medical providers, who were familiar with their medical background and history from childhood. Adolescent interviewees reported an understanding of their own pain management as well as adherence to and satisfaction with their individualized pain plans. However, adults noted that satisfaction plummeted with increasing age due to the limited number of experienced adult SCD providers, which was compounded by negative experiences (stigma, racism, drug-seeking label).

One interviewee emphasized the difficulty of finding knowledgeable providers after transition: “When you’re a pediatric sickle cell [patient], you have the doctors there every step of the way, but not with adult sickle cell… I know when I first transitioned I never felt more alone in my life… you look at that ER doctor kind of with the same mindset as you would your hematologist who just hand walked you through everything. And adult care providers were a lot more blunt and cold and they’re like… ‘I don’t know; I’m not really educated in sickle cell.’” A sickle cell provider shared his insight about the problem of transitioning: “I think it’s particularly challenging because we, as a community, don’t really set them up for success. It’s different from other chronic conditions [in that] it’s much harder to find an adult sickle cell provider. There’s not a lot of adult hematologists that will take care of our adult patients, and so I know statistically, there’s like a drop-down in the overall outcomes of our kids after they age out of our pediatric program.”

Self-Management, Supporting Hydroxyurea Use. Interview participants with SCD reported using a variety of methods to manage pain at home and chose to go to the ED only when the pain became intolerable. Patients and providers expressed awareness of different resources for managing pain at home, yet they also indicated that these resources have not been consolidated in an accessible way for patients and families. Some resources cited included heat therapy, acupuncture, meditation, medical marijuana, virtual reality devices, and pain medications other than opioids.

Patients and providers expressed the need for increasing awareness and education about hydroxyurea. Many interview participants with SCD were concerned about side effects, multiple visits with a provider during dose titration, and ongoing laboratory monitoring. They also expressed difficulties with scheduling multiple appointments, depending on access to transportation and limited provider clinic hours. They were aware of strategies for improving adherence with hydroxyurea, including setting phone alarms, educating family members about hydroxyurea, and eliciting family support, but expressed needing help to consistently implement these strategies.

Safe Opioid Prescribing. Adult care providers expressed concerns about safe opioid prescribing for patients with SCD. They were reluctant to prescribe opioid doses needed to adequately control SCD pain. Providers expressed uncertainty and fear or concern about medical/legal liability or about their judgment about what’s safe and not safe for patients with chronic use/very high doses of opioids. “I know we’re in like this opiate epidemic here in this country but I feel like these patients don’t really fit under that umbrella that the problem is coming from so [I am] just trying to learn more about how to take care of them.”

Care Coordination and Provider Communication. Adolescents and adults with SCD reported having positive experiences—good communication, established trust, and compassionate care—with their usual providers. However, they perceived that ED physicians and nurses did not really care about them. Both interviewees with SCD and providers recognized the importance of good communication in all settings as the key to overcoming barriers to receiving quality care. All agreed on the importance of using individual pain plans so that all providers, especially ED providers, can be more at ease with treating adolescents and adults with SCD.

Quantitative Data: Adolescents and Adults With SCD

Fifty-eight adolescents and adults with SCD (aged 15 to 48 years) completed the survey. Three additional individuals who did not complete the interview completed the survey. Reasons for not completing the interview included scheduling challenges (n = 2) or a sickle cell pain episode (n = 1). The average age of participants was 31 years ± 8.6, more than half (57%) were female, and the majority (93%) were African American (Table 1). Most (71%) had never been married. Half (50%) had some college or an associate degree, and 40% were employed and reported an annual household income of less than $30,000. Insurance coverage was predominantly Medi-Cal (Medicaid, 69%). The majority of participants resided in Alameda (34.5%) or Contra Costa (21%) counties. The majority of sickle cell care was received in Alameda County, whether outpatient (52%), inpatient (40%), or ED care (41%). The majority (71%) had a diagnosis of SCD hemoglobin SS.

Pain. More than one-third of individuals with SCD reported 1 or 2 ED visits for pain in the previous 6 months (34%), and more than 3 hospitalizations (36%) related to pain in the previous year (Table 2). The majority (85%) reported having severe pain at home in the previous 6 months that they did not seek health care for, consistent with their reports in the qualitative interviews. More than half (59%) reported 4 or more of these severe pain episodes that led to inability to perform daily activities for 1 week or more. While pain interference on the PROMIS Pain Interference Short Form on average (T-score, 59.6 ± 8.6) was similar to that of the general population (T-score, 50 ± 10), a higher proportion of patients with SCD reported pain interference compared with the general population. The mean self-efficacy (confidence in ability to manage complications of SCD) score on the SCSES of 30.0 ± 7.3 (range, 9–45) was similar to that of other adults with SCD (mean, 32.2 ± 7.0). Twenty-five percent of the present sample had a low self-efficacy score (< 25).

Barriers to Care and Treatments. Consistent with the qualitative data, SCD-related symptoms such as tiredness (64%) and pain (62%) were reported most often as barriers to care (Table 3). Emotions (> 25%) such as worry/fear, frustration/anger, and lack of confidence were other important barriers to care. Provider knowledge and attitudes were cited next most often, with 38% of the sample indicating “Providers accuse me of drug-seeking” and “It is hard for me to find a provider who has enough experiences with or knowledge about SCD.” Participants expressed that they were not believed when in pain and “I am treated differently from other patients.” Almost half of respondents cited “I am not seen quickly enough when I am in pain” as a barrier to their care.

Consistent with the qualitative data, transportation barriers (not having a vehicle, costs of transportation, public transit not easy to get to) were cited by 55% of participants. About half of participants reported that insurance was an important barrier, with high co-pays and medications and other services not covered. In addition, gathering approvals was a long and fragmented process, particularly for consultations among providers (hematology, primary care provider, pain specialist). Furthermore, insurance provided limited choices about location for services.

Participants reported social support system burnout (22%), help needed with daily activities (21%), and social isolation or generally not having enough support (33%) as ongoing barriers. Difficulties were encountered with self-management (eg, taking medications on time or making follow-up appointments, 19%), with 22% of participants finding the health care system confusing or hard to understand. Thirty percent reported “Places for me to go to learn how to stay well are not close by or easy to get to.” ”Worry about side effects” (33%) was a common barrier to hydroxyurea use. Participants described “forgetting to take the medicine,” “tried before but it did not work,” “heard scary things” about hydroxyurea, and “not interested in taking another medicine” as barriers.

Quality of Care. More than half (51%) of the 53 participants who had accessed health care in the previous year rated their overall health care as poor on the ASCQ-Me QOC measure. This was significantly higher compared to the reports from more than 47,000 adults with Medicaid in 2017 (16%),⁴¹ and to the 2008-2009 report from 556 adults with SCD from across the United States (37%, Figure 2).³³ The major contributor to these poor ratings for participants in our sample was low satisfaction with ED care.

Sixty percent of the 42 participants who had accessed ED care in the past year indicated “never” or “sometimes” to the question “When you went to the ED for care, how often did you get it as soon as you wanted?” compared with only 16% of the 2017 adult Medicaid population responding (n = 25,789) (Figure 3). Forty-seven percent of those with an ED visit indicated that, in the previous 12 months, they had been made to wait “more than 2 hours before receiving treatment for acute pain in the ED.” However, in the previous 12 months, 39% reported that their wait time in the ED had been only “between five minutes and one hour.”

On the ASCQ-Me QOC Access to Care composite measure, 33% of 42 participants responding reported they were seen at a routine appointment as soon as they would have liked. This is significantly lower compared to 56% of the adult Medicaid population responding to the same question. Reports of provider communication (Provider Communication composite) for adolescents and adults with SCD were comparable to reports of adults with SCD from the ASCQ-Me field test,³³ but adults with Medicaid reported higher ratings of quality communication behaviors (Figure 4).^33,41 Nearly 60% of both groups with SCD reported that providers “always” performed quality communication behaviors—listened carefully, spent enough time, treated them with respect, and explained things well—compared with more than 70% of adults with Medicaid.

Participants from all counties reported the same number of barriers to care on average (3.3 ± 2.1). Adolescents and adults who reported more barriers to care also reported lower satisfaction with care (r = –0.47, P < 0.01) and less confidence in their ability to manage their SCD (self-efficacy, r = – 0.36, P < 0.05). Female participants reported more barriers to care on average compared with male participants (2.6 ± 2.4 vs 1.4 ± 2.0, P = 0.05). Participants with higher self-efficacy reported lower pain ratings (r = –0.47, P < 0.001).

Quantitative Data: Health Care Providers

Providers (n = 56) and community stakeholders (2 leaders of community-based organizations and 3 health care administrators) were interviewed, with 29 also completing the survey. The reason for not completing (n = 22) was not having the time once the interview was complete. A link to the survey was sent to any provider not completing at the time of the interview, with 2 follow-up reminders. The majority of providers were between the ages of 31 and 50 years (46.4%), female (71.4%), and white (66.1%) (Table 4). None were of Hispanic, Latinx, or Spanish origin. Thirty-six were physicians (64.3%), and 16 were allied health professionals (28.6%). Of the 56 providers, 32 indicated they had expertise caring for patients with SCD (57.1%), 14 were ED providers (25%), and 5 were primary care providers. Most of the providers practiced in an urban setting (91.1%).

Barriers to Care: ED Provider Perspectives. Nine of 14 ED providers interviewed completed the survey on their perspectives regarding barriers to care in the ED, difficulty with follow-ups, ED training resources, and pain control for patients with SCD. ED providers (n = 8) indicated that “provider attitudes” were a barrier to care delivery in the ED for patients with SCD. Some providers (n = 7) indicated that “implicit bias,” “opioid epidemic,” “concern about addiction,” and “patient behavior” were barriers. Respondents indicated that “overcrowding” (n = 6) and “lack of care pathway/protocol” (n = 5) were barriers. When asked to express their level of agreement with statements about SCD care in the ED, respondents disagreed/strongly disagreed (n = 5) that they were “able to make a follow-up appointment” with a sickle cell specialist or primary care provider upon discharge from the ED, and others disagreed/strongly disagreed (n = 4) that they were able to make a “referral to a case management program.”

ED training and resources. Providers agreed/strongly agreed (n = 8) that they had the knowledge and training to care for patients with SCD, that they had access to needed medications, and that they had access to knowledgeable nursing staff with expertise in SCD care. All 9 ED providers indicated that they had sufficient physician/provider staffing to provide good pain management to persons with SCD in the ED.

Pain control in the ED. Seven ED providers indicated that their ED used individualized dosing protocols to treat sickle cell pain, and 5 respondents indicated their ED had a protocol for treating sickle cell pain. Surprisingly, only 3 indicated that they were aware of the NHLBI recommendations for the treatment of vaso-occlusive pain.

Barriers to Care: Primary Care Provider Perspectives. Twenty providers completed the SCD provider section of the survey, including 17 multidisciplinary SCD providers from 4 sickle cell special care centers and 3 community primary care providers. Of the 20, 12 were primary care providers for patients with SCD (Table 4).

Patient needs. Six primary care providers indicated that the medical needs of patients with SCD were being met, but none indicated that the behavioral health or mental health needs were being met.

Managing SCD comorbidities. Five primary care providers indicated they were very comfortable providing preventive ambulatory care to patients with SCD. Six indicated they were very comfortable managing acute pain episodes, but none were very comfortable managing comorbidities such as pulmonary hypertension, diabetes, or chronic pain.

Barriers to opioid use. Only 3 of 12 providers reviewing a list of 15 potential barriers to the use of opioids for SCD pain management indicated a perceived lack of efficacy of opioids, development of tolerance and dependence, and concerns about community perceptions as barriers. Two providers selected potential for diversion as a moderate barrier to opioid use.

Barriers to hydroxyurea use. Eight of 12 providers indicated that the common reasons that patients/families refuse hydroxyurea were “worry about side effects”; 7 chose “don’t want to take another medicine,” and 6 chose “worry about carcinogenic potential.” Others (n = 10) indicated that “patient/family adherence with hydroxyurea” and “patient/family adherence with required blood tests” were important barriers to hydroxyurea use. Eight of the 12 providers indicated that they were comfortable with managing hydroxyurea in patients with SCD.

Care redesign. Twenty SCD and primary care providers completed the Care Redesign section of the survey. Respondents (n = 11) indicated that they would see more patients with SCD if they had accessible case management services available without charge or if patient access to transportation to clinic was also available. Ten indicated that they would see more patients with SCD if they had an accessible community health worker (who understands patient’s/family’s social situation) and access to a pain management specialist on call to answer questions and who would manage chronic pain. All (n = 20) were willing to see more patients with SCD in their practices. Most reported that a clinical decision-support tool for SCD treatment (n = 13) and avoidance of complications (n = 12) would be useful.

Discussion

We evaluated access and barriers to care, quality of care, care coordination, and provider communication from the perspectives of adolescents and adults with SCD, their care providers, and community stakeholders, within the Solberg conceptual model for quality improvement. We found that barriers within the care process content domain (context and systems) were most salient for this population of adolescents and adults with SCD, with lack of provider knowledge and poor attitudes toward adolescents and adults with SCD, particularly in the ED, cited consistently by participant groups. Stigmatization and lack of provider compassion that affected the quality of care were particularly problematic. These findings are consistent with previous reports.^42,43 Adult health care (particularly ED) provider biases and negative attitudes have been recognized as major barriers to optimal pain management in SCD.^8,11,44,45 Interestingly, ED providers in our needs assessment indicated that they felt they had the training and resources to manage patients with SCD. However, only a few actually reported knowing about the NHLBI recommendations for the treatment of vaso-occlusive pain.

Within the care process content domain, we also found that SCD-related complications and associated emotions (fear, worry, anxiety), compounded by lack of access to knowledgeable and compassionate providers, pose a significant burden. Negative encounters with the health care system contributed to a striking 84% of patient participants choosing to manage severe pain at home, with pain seriously interfering with their ability to function on a daily basis. ED providers agreed that provider attitudes and implicit bias pose important barriers to care for adolescents and adults with SCD. Adolescents and adults with SCD wanted, and understood the need, to enhance self-management skills. Both they and their providers agreed that barriers to hydroxyurea uptake included worries about potential side effects, challenges with adherence to repeated laboratory testing, and support with remembering to take the medicine. However, providers uniformly expressed that access to behavioral and mental health services were, if not nonexistent, impossible to access.

Participants with SCD and their providers reported infrastructural challenges (change process capability), as manifested in limitations with accessing acute and preventive care due to transportation- and insurance- related issues. There were health system barriers that were particularly encountered during the transition from pediatric to adult care. These findings are consistent with previous reports that have found fewer interdisciplinary services available in the adult care settings compared with pediatrics.^46,47 Furthermore, adult care providers were less willing to accept adults with SCD because of the complexity of their management, for which the providers did not have the necessary expertise.^3,48-50 In addition, both adolescents and adults with SCD and primary care providers highlighted the inadequacies of the current system in addressing the chronic pain needs of this population. Linking back to the Solberg conceptual framework, our needs assessment results confirm the important role of establishing SCD care as a priority within a health care system—this requires leadership and vision. The vision and priorities must be implemented by effective health care teams. Multilevel approaches or interventions, when implemented, will lead to the desired outcomes.

Findings from our needs assessment within our 5-county region mirror needs assessment results from the broader consortium.⁵¹ The SCDIC has prioritized developing an intervention that addresses the challenges identified within the care process domain by directly enhancing provider access to patient individualized care plans in the electronic health record in the ED. Importantly, ED providers will be asked to view a short video that directly challenges bias and stigma in the ED. Previous studies have indeed found that attitudes can be improved by providers viewing short video segments of adults with SCD discussing their experiences.^36,52 This ED protocol will be one of the interventions that we will roll out in Northern California, given the significance of negative ED encounters reported by needs assessment participants. An additional feature of the intervention is a script for adults with SCD that guides them through introducing their individualized pain plan to their ED providers, thereby enhancing their self-efficacy in a situation that has been so overwhelmingly challenging.

We will implement a second SCDIC intervention that utilizes a mobile app to support self-management on the part of the patient, by supporting motivation and adherence with hydroxyurea.⁵³ A companion app supports hydroxyurea guideline adherence on the part of the provider, in keeping with one of our findings that providers are in need of decision-support tools. Elements of the intervention also align with our findings related to the importance of a support system in managing SCD, in that participants will identify a supportive partner who will play a specific role in supporting their adherence with hydroxyurea.

On our local level, we have, by necessity, partnered with leaders and community stakeholders throughout the region to ensure that these interventions to improve SCD care are prioritized. Grant funds provide initial resources for the SCDIC interventions, but our partnering health care administrators and medical directors must ensure that participating ED and hematology providers are free from competing priorities in order to implement the changes. We have partnered with a SCD community-based organization that is designing additional educational presentations for local emergency medicine providers, with the goal to bring to life very personal stories of bias and stigma within the EDs that directly contribute to decisions to avoid ED care despite severe symptoms.

Although we attempted to obtain samples of adolescents and adults with SCD and their providers that were representative across the 5-county region, the larger proportion of respondents were from 1 county. We did not assess concerns of age- and race-matched adults in our catchment area, so we cannot definitively say that our findings are unique to SCD. However, our results are consistent with findings from the national sample of adults with SCD who participated in the ASCQ-Me field test, and with results from the SCDIC needs assessment.^33,51 Interviews and surveys are subject to self-report bias and, therefore, may or may not reflect the actual behaviors or thoughts of participants. Confidence is increased in our results given the triangulation of expressed concerns across participant groups and across data collection strategies. The majority of adolescents and adults with SCD (95%) completed both the interview and survey, while 64% of ED providers interviewed completed the survey, compared with 54% of SCD specialists and primary care providers. These response rates are more than acceptable within the realm of survey response rates.^54,55

Although we encourage examining issues with care delivery within the conceptual framework for quality improvement presented, we recognize that grant funding allowed us to conduct an in-depth needs assessment that might not be feasible in other settings. Still, we would like readers to understand the importance of gathering data for improvement in a systematic manner across a range of participant groups, to ultimately inform the development of interventions and provide for evaluation of outcomes as a result of the interventions. This is particularly important for a disease, such as SCD, that is both medically and sociopolitically complex.

Conclusion

Our needs assessment brought into focus the multiple factors contributing to the disparities in health care experienced by adolescents and adults with SCD on our local level, and within the context of inequities in health resources and outcomes on the national level. We propose solutions that include specific interventions developed by a consortium of SCD and implementation science experts. We utilize a quality improvement framework to ensure that the elements of the interventions also address the barriers identified by our local providers and patients that are unique to our community. The pervasive challenges in SCD care, coupled with its medical complexities, may seem insurmountable, but our survey and qualitative results provide us with a road map for the way forward.

Acknowledgments: The authors thank the adolescents and adults with sickle cell disease, the providers, and the community stakeholders who completed the interviews and surveys. The authors also acknowledge the SCCCI co-investigators for their contributions to this project, including Michael Bell, MD, Ward Hagar, MD, Christine Hoehner, FNP, Kimberly Major, MSW, Anne Marsh, MD, Lynne Neumayr, MD, and Ted Wun, MD. We also thank Kamilah Bailey, Jameelah Hodge, Jennifer Kim, Michael Rowland, Adria Stauber, Amber Fearon, and Shanda Robertson, and the Sickle Cell Data Collection Program for their contributions.

Corresponding author: Marsha J. Treadwell, PhD, University of California San Francisco Benioff Children’s Hospital Oakland, 747 52nd St., Oakland, CA 94609; [email protected].

Financial disclosures: None.

Funding/support: This work was supported by grant # 1U01HL134007 from the National Heart, Lung, and Blood Institute to the University of California San Francisco Benioff Children’s Hospital Oakland.

From the University of California San Francisco (Dr. Treadwell, Dr. Hessler, Yumei Chen, Swapandeep Mushiana, Dr. Potter, and Dr. Vichinsky), the University of California Los Angeles (Dr. Jacob), and the University of California Berkeley (Alex Chen).

Abstract

• Objective: Adolescents and adults with sickle cell disease (SCD) face pervasive disparities in health resources and outcomes. We explored barriers to and facilitators of care to identify opportunities to support implementation of evidence-based interventions aimed at improving care quality for patients with SCD.
• Methods: We engaged a representative sample of adolescents and adults with SCD (n = 58), health care providers (n = 51), and community stakeholders (health care administrators and community-based organization leads (n = 5) in Northern California in a community-based needs assessment. We conducted group interviews separately with participant groups to obtain in-depth perspectives. Adolescents and adults with SCD completed validated measures of pain interference, quality of care, self-efficacy, and barriers to care. Providers and community stakeholders completed surveys about barriers to SCD care.
• Results: We triangulated qualitative and quantitative data and found that participants with SCD (mean age, 31 ± 8.6 years), providers, and community stakeholders emphasized the social and emotional burden of SCD as barriers. Concrete barriers agreed upon included insurance and lack of resources for addressing pain impact. Adolescents and adults with SCD identified provider issues (lack of knowledge, implicit bias), transportation, and limited social support as barriers. Negative encounters with the health care system contributed to 84% of adolescents and adults with SCD reporting they chose to manage severe pain at home. Providers focused on structural barriers: lack of access to care guidelines, comfort level with and knowledge of SCD management, and poor care coordination.
• Conclusion: Strategies for improving access to compassionate, evidence-based quality care, as well as strategies for minimizing the burden of having SCD, are warranted for this medically complex population.

Keywords: barriers to care; quality of care; care access; care coordination.

Sickle cell disease (SCD), an inherited chronic medical condition, affects about 100,000 individuals in the United States, a population that is predominantly African American.¹ These individuals experience multiple serious and life-threatening complications, most frequently recurrent vaso-occlusive pain episodes,² and they require interactions with multidisciplinary specialists from childhood. Because of advances in treatments, the majority are reaching adulthood; however, there is a dearth of adult health care providers with the training and expertise to manage their complex medical needs.³ Other concrete barriers to adequate SCD care include insurance and distance to comprehensive SCD centers.^4,5

Social, behavioral, and emotional factors may also contribute to challenges with SCD management. SCD may limit daily functional abilities and lead to diminished overall quality of life.^6,7 Some adolescents and adults may require high doses of opioids, which contributes to health care providers’ perceptions that there is a high prevalence of drug addiction in the population.^8,9 These providers express negative attitudes towards adults with SCD, and, consequently, delay medication administration when it is acutely needed and provide otherwise suboptimal treatment.^8,10,11 Adult care providers may also be uncomfortable with prescribing and managing disease-modifying therapies (blood transfusion, hydroxyurea) that have established efficacy.^12-17

As 1 of 8 programs funded by the National Heart, Lung, and Blood Institute’s (NHLBI) Sickle Cell Disease Implementation Consortium (SCDIC), we are using implementation science to reduce barriers to care and improve quality of care and health care outcomes in SCD.^18,19 Given that adolescents and adults with SCD experience high mortality, severe pain, and progressive decline in their ability to function day to day, and also face lack of access to knowledgeable, compassionate providers in primary and emergency settings, the SCDIC focuses on individuals aged 15 to 45 years.^6,8,9,11,12

Our regional SCDIC program, the Sickle Cell Care Coordination Initiative (SCCCI), brings together researchers, clinicians, adolescents, and adults with SCD and their families, dedicated community members, policy makers, and administrators to identify and address barriers to health care within 5 counties in Northern California. One of our first steps was to conduct a community-based needs assessment, designed to inform implementation of evidence-based interventions, accounting for unique contextual factors in our region.

Conceptual Framework for Improving Medical Practice

Our needs assessment is guided by Solberg’s Conceptual Framework for Improving Medical Practice (Figure 1).²⁰ Consistent with the overarching principles of the SCDIC, this conceptual framework focuses on the inadequate implementation of evidence-based guidelines, and on the need to first understand multifactorial facilitators and barriers to guideline implementation in order to effect change. The framework identifies 3 main elements that must be present to ensure improvements in quality-of-care processes and patient outcomes: priority, change process capability, and care process content. Priority refers to ample resource allocation for the specific change, as well as freedom from competing priorities for those implementing the change. Change process capability includes strong, effective leadership, adequate infrastructure for managing change (including resources and time), change management skills at all levels, and an established clinical information system. Care process content refers to context and systems-level changes, such as delivery system redesign as needed, support for self-management to lessen the impact of the disease, and decision support.^21-23

The purpose of our community-based needs assessment was to evaluate barriers to care and quality of care in SCD, within Solberg’s conceptual model for improving medical practice. The specific aims were to evaluate access and barriers to care (eg, lack of provider expertise and training, health care system barriers such as poor care coordination and provider communication); evaluate quality of care; and assess patient needs related to pain, pain interference, self-efficacy, and self-management for adolescents and adults with SCD. We gathered the perspectives of a representative community of adolescents and adults with SCD, their providers, and community stakeholders in order to examine barriers, quality of life and care, and patient experiences in our region.

Methods

Design

In this cross-sectional study, adolescents and adults with SCD, their providers, and community stakeholders participated in group or individual qualitative interviews and completed surveys between October 2017 and March 2018.

Setting and Sample

Recruitment flyers were posted on a regional SCD-focused website, and clinical providers or a study coordinator introduced information about the needs assessment to potential participants with SCD during clinic visits at the participating centers. Participants with SCD were eligible if they had any diagnosis of SCD, were aged 15 to 48 years, and received health services within 5 Northern California counties (Alameda, Contra Costa, Sacramento, San Francisco, and Solano). They were excluded if they did not have a SCD diagnosis or had not received health services within the catchment area. As the project proceeded, participants were asked to refer other adolescents and adults with SCD for the interviews and surveys (snowball sampling). Our goal was to recruit 50 adolescents and adults with SCD into the study, aiming for 10 representatives from each county.

Providers and community stakeholders were recruited via emails, letters and informational flyers. We engaged our partner, the Sickle Cell Data Collection Program,² to generate a list of providers and institutions that had seen patients with SCD in primary, emergency, or inpatient settings in the region. We contacted these institutions to describe the SCCCI and invite participation in the needs assessment. We also invited community-based organization leads and health care administrators who worked with SCD to participate. Providers accessed confidential surveys via a secure link on the study website or completed paper versions. Common data collected across providers included demographics and descriptions of practice settings.

Participants were eligible to be part of the study if they were health care providers (physicians and nurses) representing hematology, primary care, family medicine, internal medicine, or emergency medicine; ancillary staff (social work, psychology, child life); or leaders or administrators of clinical or sickle cell community-based organizations in Northern California (recruitment goal of n = 50). Providers were excluded if they practiced in specialties other than those noted or did not practice within the region.

Data Collection Procedures

After providing assent/consent, participating adolescents and adults with SCD took part in individual and group interviews and completed survey questionnaires. All procedures were conducted in a private space in the sickle cell center or community. Adolescents and adults with SCD completed the survey questionnaire on a tablet, with responses recorded directly in a REDCap (Research Electronic Data Capture) database,²⁴ or on a paper version. Interviews lasted 60 (individual) to 90 (group) minutes, while survey completion time was 20 to 25 minutes. Each participant received a gift card upon completion as an expression of appreciation. All procedures were approved by the institutional review boards of the participating health care facilities.

Group and Individual Interviews

Participants with SCD and providers were invited to participate in a semi-structured qualitative interview prior to being presented with the surveys. Adolescents and adults with SCD were interviewed about barriers to care, quality of care, and pain-related experiences. Providers were asked about barriers to care and treatments. Interview guides were modified for community-based organization leaders and health care administrators who did not provide clinical services. Interview guides can be found in the Appendix. Interviews were conducted by research coordinators trained in qualitative research methods by the first author (MT). As appropriate with semi-structured interviews, the interviewers could word questions spontaneously, change the order of questions for ease of flow of conversation, and inform simultaneous coding of interviews with new themes as those might arise, as long as they touched on all topics within the interview guide.²⁵ The interview guides were written, per qualitative research standards, based on the aims and purpose of the research,²⁶ and were informed by existing literature on access and barriers to care in SCD, quality of care, and the needs of individuals with SCD, including in relation to impact of the disease, self-efficacy, and self-management.

Interviewees participated in either individual or group interviews, but not both. The decision for which type of interview an individual participated in was based on 2 factors: if there were not comparable participants for group interviews (eg, health care administrator and community-based organization lead), these interviews were done individually; and given that we were drawing participants from a 5-county area in Northern California, scheduling was challenging for individuals with SCD with regard to aligning schedules and traveling to a central location where the group interviews were conducted. Provider group interviews were easier to arrange because we could schedule them at the same time as regularly scheduled meetings at the participants’ health care institutions.

Interview Data Gathering and Analysis

Digital recordings of the interviews were cleaned of any participant identifying data and sent for transcription to an outside service. Transcripts were reviewed for completeness and imported into NVivo (www.qsrinternational.com), a qualitative data management program.

A thematic content analysis and deductive and inductive approaches were used to analyze the verbatim transcripts generated from the interviews. The research team was trained in the use of NVivo software to facilitate the coding process. A deductive coding scheme was initially used based on existing concepts in the literature regarding challenges to optimal SCD care, with new codes added as the thematic content analyses progressed. The initial coding, pattern coding, and use of displays to examine the relationships between different categories were conducted simultaneously.^27,28 Using the constant comparative method, new concepts from participants with SCD and providers could be incorporated into subsequent interviews with other participants. For this study, the only additional concepts added were in relation to participant recruitment and retention in the SCDIC Registry. Research team members coded transcripts separately and came together weekly, constantly comparing codes and developing the consensus coding scheme. Where differences between coders existed, code meanings were discussed and clarified until consensus was reached.²⁹

Quantitative data were analyzed using SPSS (v. 25, Chicago, IL). Descriptive statistics (means, standard deviations, frequencies, percentages) were used to summarize demographics (eg, age, gender, and race), economic status, and type of SCD. No systematic differences were detected from cases with missing values. Scale reliabilities (ie, Cronbach α) were evaluated for self-report measures.

Measurement

Adolescents and adults with SCD completed items from the PhenX Toolkit (consensus measures for Phenotypes and eXposures), assessing sociodemographics (age, sex, race, ethnicity, educational attainment, occupation, marital status, annual income, insurance), and clinical characteristics (sickle cell diagnosis and emergency department [ED] and hospital utilization for pain).³⁰

Pain Interference Short Form (Patient-Reported Outcomes Measurement Information System [PROMIS]). The Pain Interference Form consists of 8 items that assess the degree to which pain interfered with day-to-day activities in the previous 7 days at home, including impacts on social, cognitive, emotional, and physical functioning; household chores and recreational activities; sleep; and enjoyment in life. Reliability and validity of the PROMIS Pain Interference Scale has been demonstrated, with strong negative correlations with Physical Function Scales (r = 0.717, P < 0.01), indicating that higher scores are associated with lower function (β = 0.707, P < 0.001).³¹ The Cronbach α estimate for the other items on the pain interference scale was 0.99. Validity analysis indicated strong correlations with pain-related domains: BPI Interference Subscale (rho = 0.90), SF-36 Bodily Pain Subscale (rho = –0.84), and 0–10 Numerical Rating of Pain Intensity (rho = 0.48).³²

Adult Sickle Cell Quality of Life Measurement Information System (ASCQ-Me) Quality of Care (QOC). ASCQ-Me QOC consists of 27 items that measure the quality of care that adults with SCD have received from health care providers.³³ There are 3 composites: provider communication (quality of patient and provider communication), ED care (quality of care in the ED), and access (to routine and emergency care). Internal consistency reliability for all 3 composites is greater than 0.70. Strong correlations of the provider communication composite with overall ratings of routine care (r = 0.65) and overall provider ratings (r = 0.83) provided evidence of construct validity. Similarly, the ED care composite was strongly correlated with overall ratings of QOC in the ED, and the access composite was highly correlated with overall evaluations of ED care (r = 0.70). Access, provider interaction, and ED care composites were reliable (Cronbach α, 0.70–0.83) and correlated with ratings of global care (r = 0.32–0.83), further indicating construct validity.³³

Sickle Cell Self-Efficacy Scale (SCSES). The SCSES is a 9-item, self-administered questionnaire measuring perceptions of the ability to manage day-to-day issues resulting from SCD. SCSES items are scored on a 5-point scale ranging from Not sure at all (1) to Very sure (5). Individual item responses are summed to give an overall score, with higher scores indicating greater self-efficacy. The SCSES has acceptable reliability (r = 0.45, P < 0.001) and validity (α = 0.89).^34,35

Sickle Cell Disease Barriers Checklist. This checklist consists of 53 items organized into 8 categories: insurance, transportation, accommodations and accessibility, provider knowledge and attitudes, social support, individual barriers such as forgetting or difficulties understanding instructions, emotional barriers (fear, anger), and disease-related barriers. Participants check applicable barriers, with a total score range of 0 to 53 and higher scores indicating more barriers to care. The SCD Barriers Checklist has demonstrated face validity and test-retest reliability (Pearson r = 0.74, P < 0.05).⁵

ED Provider Checklist. The ED provider survey is a checklist of 14 statements pertaining to issues regarding patient care, with which the provider rates level of agreement. Items representing the attitudes and beliefs of providers towards patients with SCD are rated on a Likert-type scale, with level of agreement indicated as 1 (strongly disagree) to 6 (strongly agree). The positive attitudes subscale consists of 4 items (Cronbach α= 0.85), and the negative attitudes subscale consists of 6 items (Cronbach α = 0.89). The Red-Flag Behaviors subscale includes 4 items that indicate behavior concerns about drug-seeking, such as requesting specific narcotics and changing behavior when the provider walks in.^8,36,37

Sickle cell and primary care providers also completed a survey consisting of sets of items compiled from existing provider surveys; this survey consisted of a list of 16 barriers to using opioids, which the providers rated on a 5-point Likert-type scale (1, not a barrier; 5, complete barrier).^13,16,38 Providers indicated their level of experience with caring for patients with SCD; care provided, such as routine health screenings; and comfort level with providing preventive care, managing comorbidities, and managing acute and chronic pain. Providers were asked what potential facilitators might improve care for patients with SCD, including higher reimbursement, case management services, access to pain management specialists, and access to clinical decision-support tools. Providers responded to specific questions about management with hydroxyurea (eg, criteria for, barriers to, and comfort level with prescribing).³⁹ The surveys are included in the Appendix.

Triangulation

Data from the interviews and surveys were triangulated to enhance understanding of results generated from the different data sources.⁴⁰ Convergence of findings, different facets of the same phenomenon, or new perspectives were examined.

Qualitative Data

Adolescents and adults with SCD (n = 55) and health care providers and community stakeholders (n = 56) participated in group or individual interviews to help us gain an in-depth understanding of the needs and barriers related to SCD care in our 5-county region. Participants with SCD described their experiences, which included stigma, racism, labeling, and, consequently, stress. They also identified barriers such as lack of transportation, challenges with insurance, and lack of access to providers who were competent with pain management. They reported that having SCD in a health care system that was unable to meet their needs was burdensome.

Barriers to Care and Treatments. Adolescents and adults indicated that SCD and its sequelae posed significant barriers to health care. Feelings of tiredness and pain make it more difficult for them to seek care. The emotional burden of SCD (fear and anger) was a frequently cited barrier, which was fueled by previous negative encounters with the health care system. All adolescents and adults with SCD reported that they knew of stigma in relation to seeking pain management that was pervasive and long-standing, and the majority reported they had directly experienced stigma. They reported that being labeled as “drug-seekers” was typical when in the ED for pain management. Participants articulated unconscious bias or overt racism among providers: “people with sickle cell are Black ... and Black pain is never as valuable as White pain” (25-year-old male). Respondents with SCD described challenges to the credibility of their pain reports in the ED. They reported that ED providers expressed doubts regarding the existence and/or severity of their pain, consequently creating a feeling of disrespect for patients seeking pain relief. The issue of stigma was mentioned by only 2 of 56 providers during their interviews.

Lack of Access to Knowledgeable, Compassionate Providers. Lack of access to knowledgeable care providers was another prevalent theme expressed by adolescents and adults with SCD. Frustration occurred when providers did not have knowledge of SCD and its management, particularly pain assessment. Adolescents and adults with SCD noted the lack of compassion among providers: “I’ve been kicked out of the hospital because they felt like okay, well we gave you enough medication, you should be all right” (29-year-old female). Providers specifically mentioned lack of compassion and knowledge as barriers to SCD care much less often during their interviews compared with the adolescents and adults with SCD.

Health Care System Barriers. Patient participants often expressed concerns about concrete and structural aspects of care. Getting to their appointments was a challenge for half of the interviewees, as they either did not have access to a vehicle or could not afford to travel the needed distance to obtain quality care. Even when hospitals were accessible by public transportation, those with excruciating pain understandably preferred a more comfortable and private way to travel: “I would like to change that, something that will be much easier, convenient for sickle cell patients that do suffer with pain, that they don’t have to travel always to see the doctor” (30-year-old male).

Insurance and other financial barriers also played an important role in influencing decisions to seek health care services. Medical expenses were not covered, or co-pays were too high. The Medicaid managed care system could prevent access to knowledgeable providers who were not within network. Such a lack of access discouraged some adolescents and adults with SCD from seeking acute and preventive care.

Transition From Pediatric to Adult Care. Interviewees with SCD expressed distress about the gap between pediatric and adult care. They described how they had a long-standing relationship with their medical providers, who were familiar with their medical background and history from childhood. Adolescent interviewees reported an understanding of their own pain management as well as adherence to and satisfaction with their individualized pain plans. However, adults noted that satisfaction plummeted with increasing age due to the limited number of experienced adult SCD providers, which was compounded by negative experiences (stigma, racism, drug-seeking label).

One interviewee emphasized the difficulty of finding knowledgeable providers after transition: “When you’re a pediatric sickle cell [patient], you have the doctors there every step of the way, but not with adult sickle cell… I know when I first transitioned I never felt more alone in my life… you look at that ER doctor kind of with the same mindset as you would your hematologist who just hand walked you through everything. And adult care providers were a lot more blunt and cold and they’re like… ‘I don’t know; I’m not really educated in sickle cell.’” A sickle cell provider shared his insight about the problem of transitioning: “I think it’s particularly challenging because we, as a community, don’t really set them up for success. It’s different from other chronic conditions [in that] it’s much harder to find an adult sickle cell provider. There’s not a lot of adult hematologists that will take care of our adult patients, and so I know statistically, there’s like a drop-down in the overall outcomes of our kids after they age out of our pediatric program.”

Self-Management, Supporting Hydroxyurea Use. Interview participants with SCD reported using a variety of methods to manage pain at home and chose to go to the ED only when the pain became intolerable. Patients and providers expressed awareness of different resources for managing pain at home, yet they also indicated that these resources have not been consolidated in an accessible way for patients and families. Some resources cited included heat therapy, acupuncture, meditation, medical marijuana, virtual reality devices, and pain medications other than opioids.

Patients and providers expressed the need for increasing awareness and education about hydroxyurea. Many interview participants with SCD were concerned about side effects, multiple visits with a provider during dose titration, and ongoing laboratory monitoring. They also expressed difficulties with scheduling multiple appointments, depending on access to transportation and limited provider clinic hours. They were aware of strategies for improving adherence with hydroxyurea, including setting phone alarms, educating family members about hydroxyurea, and eliciting family support, but expressed needing help to consistently implement these strategies.

Safe Opioid Prescribing. Adult care providers expressed concerns about safe opioid prescribing for patients with SCD. They were reluctant to prescribe opioid doses needed to adequately control SCD pain. Providers expressed uncertainty and fear or concern about medical/legal liability or about their judgment about what’s safe and not safe for patients with chronic use/very high doses of opioids. “I know we’re in like this opiate epidemic here in this country but I feel like these patients don’t really fit under that umbrella that the problem is coming from so [I am] just trying to learn more about how to take care of them.”

Care Coordination and Provider Communication. Adolescents and adults with SCD reported having positive experiences—good communication, established trust, and compassionate care—with their usual providers. However, they perceived that ED physicians and nurses did not really care about them. Both interviewees with SCD and providers recognized the importance of good communication in all settings as the key to overcoming barriers to receiving quality care. All agreed on the importance of using individual pain plans so that all providers, especially ED providers, can be more at ease with treating adolescents and adults with SCD.

Quantitative Data: Adolescents and Adults With SCD

Fifty-eight adolescents and adults with SCD (aged 15 to 48 years) completed the survey. Three additional individuals who did not complete the interview completed the survey. Reasons for not completing the interview included scheduling challenges (n = 2) or a sickle cell pain episode (n = 1). The average age of participants was 31 years ± 8.6, more than half (57%) were female, and the majority (93%) were African American (Table 1). Most (71%) had never been married. Half (50%) had some college or an associate degree, and 40% were employed and reported an annual household income of less than $30,000. Insurance coverage was predominantly Medi-Cal (Medicaid, 69%). The majority of participants resided in Alameda (34.5%) or Contra Costa (21%) counties. The majority of sickle cell care was received in Alameda County, whether outpatient (52%), inpatient (40%), or ED care (41%). The majority (71%) had a diagnosis of SCD hemoglobin SS.

Pain. More than one-third of individuals with SCD reported 1 or 2 ED visits for pain in the previous 6 months (34%), and more than 3 hospitalizations (36%) related to pain in the previous year (Table 2). The majority (85%) reported having severe pain at home in the previous 6 months that they did not seek health care for, consistent with their reports in the qualitative interviews. More than half (59%) reported 4 or more of these severe pain episodes that led to inability to perform daily activities for 1 week or more. While pain interference on the PROMIS Pain Interference Short Form on average (T-score, 59.6 ± 8.6) was similar to that of the general population (T-score, 50 ± 10), a higher proportion of patients with SCD reported pain interference compared with the general population. The mean self-efficacy (confidence in ability to manage complications of SCD) score on the SCSES of 30.0 ± 7.3 (range, 9–45) was similar to that of other adults with SCD (mean, 32.2 ± 7.0). Twenty-five percent of the present sample had a low self-efficacy score (< 25).

Barriers to Care and Treatments. Consistent with the qualitative data, SCD-related symptoms such as tiredness (64%) and pain (62%) were reported most often as barriers to care (Table 3). Emotions (> 25%) such as worry/fear, frustration/anger, and lack of confidence were other important barriers to care. Provider knowledge and attitudes were cited next most often, with 38% of the sample indicating “Providers accuse me of drug-seeking” and “It is hard for me to find a provider who has enough experiences with or knowledge about SCD.” Participants expressed that they were not believed when in pain and “I am treated differently from other patients.” Almost half of respondents cited “I am not seen quickly enough when I am in pain” as a barrier to their care.

Consistent with the qualitative data, transportation barriers (not having a vehicle, costs of transportation, public transit not easy to get to) were cited by 55% of participants. About half of participants reported that insurance was an important barrier, with high co-pays and medications and other services not covered. In addition, gathering approvals was a long and fragmented process, particularly for consultations among providers (hematology, primary care provider, pain specialist). Furthermore, insurance provided limited choices about location for services.

Participants reported social support system burnout (22%), help needed with daily activities (21%), and social isolation or generally not having enough support (33%) as ongoing barriers. Difficulties were encountered with self-management (eg, taking medications on time or making follow-up appointments, 19%), with 22% of participants finding the health care system confusing or hard to understand. Thirty percent reported “Places for me to go to learn how to stay well are not close by or easy to get to.” ”Worry about side effects” (33%) was a common barrier to hydroxyurea use. Participants described “forgetting to take the medicine,” “tried before but it did not work,” “heard scary things” about hydroxyurea, and “not interested in taking another medicine” as barriers.

Quality of Care. More than half (51%) of the 53 participants who had accessed health care in the previous year rated their overall health care as poor on the ASCQ-Me QOC measure. This was significantly higher compared to the reports from more than 47,000 adults with Medicaid in 2017 (16%),⁴¹ and to the 2008-2009 report from 556 adults with SCD from across the United States (37%, Figure 2).³³ The major contributor to these poor ratings for participants in our sample was low satisfaction with ED care.

Sixty percent of the 42 participants who had accessed ED care in the past year indicated “never” or “sometimes” to the question “When you went to the ED for care, how often did you get it as soon as you wanted?” compared with only 16% of the 2017 adult Medicaid population responding (n = 25,789) (Figure 3). Forty-seven percent of those with an ED visit indicated that, in the previous 12 months, they had been made to wait “more than 2 hours before receiving treatment for acute pain in the ED.” However, in the previous 12 months, 39% reported that their wait time in the ED had been only “between five minutes and one hour.”

On the ASCQ-Me QOC Access to Care composite measure, 33% of 42 participants responding reported they were seen at a routine appointment as soon as they would have liked. This is significantly lower compared to 56% of the adult Medicaid population responding to the same question. Reports of provider communication (Provider Communication composite) for adolescents and adults with SCD were comparable to reports of adults with SCD from the ASCQ-Me field test,³³ but adults with Medicaid reported higher ratings of quality communication behaviors (Figure 4).^33,41 Nearly 60% of both groups with SCD reported that providers “always” performed quality communication behaviors—listened carefully, spent enough time, treated them with respect, and explained things well—compared with more than 70% of adults with Medicaid.

Participants from all counties reported the same number of barriers to care on average (3.3 ± 2.1). Adolescents and adults who reported more barriers to care also reported lower satisfaction with care (r = –0.47, P < 0.01) and less confidence in their ability to manage their SCD (self-efficacy, r = – 0.36, P < 0.05). Female participants reported more barriers to care on average compared with male participants (2.6 ± 2.4 vs 1.4 ± 2.0, P = 0.05). Participants with higher self-efficacy reported lower pain ratings (r = –0.47, P < 0.001).

Quantitative Data: Health Care Providers

Providers (n = 56) and community stakeholders (2 leaders of community-based organizations and 3 health care administrators) were interviewed, with 29 also completing the survey. The reason for not completing (n = 22) was not having the time once the interview was complete. A link to the survey was sent to any provider not completing at the time of the interview, with 2 follow-up reminders. The majority of providers were between the ages of 31 and 50 years (46.4%), female (71.4%), and white (66.1%) (Table 4). None were of Hispanic, Latinx, or Spanish origin. Thirty-six were physicians (64.3%), and 16 were allied health professionals (28.6%). Of the 56 providers, 32 indicated they had expertise caring for patients with SCD (57.1%), 14 were ED providers (25%), and 5 were primary care providers. Most of the providers practiced in an urban setting (91.1%).

Barriers to Care: ED Provider Perspectives. Nine of 14 ED providers interviewed completed the survey on their perspectives regarding barriers to care in the ED, difficulty with follow-ups, ED training resources, and pain control for patients with SCD. ED providers (n = 8) indicated that “provider attitudes” were a barrier to care delivery in the ED for patients with SCD. Some providers (n = 7) indicated that “implicit bias,” “opioid epidemic,” “concern about addiction,” and “patient behavior” were barriers. Respondents indicated that “overcrowding” (n = 6) and “lack of care pathway/protocol” (n = 5) were barriers. When asked to express their level of agreement with statements about SCD care in the ED, respondents disagreed/strongly disagreed (n = 5) that they were “able to make a follow-up appointment” with a sickle cell specialist or primary care provider upon discharge from the ED, and others disagreed/strongly disagreed (n = 4) that they were able to make a “referral to a case management program.”

ED training and resources. Providers agreed/strongly agreed (n = 8) that they had the knowledge and training to care for patients with SCD, that they had access to needed medications, and that they had access to knowledgeable nursing staff with expertise in SCD care. All 9 ED providers indicated that they had sufficient physician/provider staffing to provide good pain management to persons with SCD in the ED.

Pain control in the ED. Seven ED providers indicated that their ED used individualized dosing protocols to treat sickle cell pain, and 5 respondents indicated their ED had a protocol for treating sickle cell pain. Surprisingly, only 3 indicated that they were aware of the NHLBI recommendations for the treatment of vaso-occlusive pain.

Barriers to Care: Primary Care Provider Perspectives. Twenty providers completed the SCD provider section of the survey, including 17 multidisciplinary SCD providers from 4 sickle cell special care centers and 3 community primary care providers. Of the 20, 12 were primary care providers for patients with SCD (Table 4).

Patient needs. Six primary care providers indicated that the medical needs of patients with SCD were being met, but none indicated that the behavioral health or mental health needs were being met.

Managing SCD comorbidities. Five primary care providers indicated they were very comfortable providing preventive ambulatory care to patients with SCD. Six indicated they were very comfortable managing acute pain episodes, but none were very comfortable managing comorbidities such as pulmonary hypertension, diabetes, or chronic pain.

Barriers to opioid use. Only 3 of 12 providers reviewing a list of 15 potential barriers to the use of opioids for SCD pain management indicated a perceived lack of efficacy of opioids, development of tolerance and dependence, and concerns about community perceptions as barriers. Two providers selected potential for diversion as a moderate barrier to opioid use.

Barriers to hydroxyurea use. Eight of 12 providers indicated that the common reasons that patients/families refuse hydroxyurea were “worry about side effects”; 7 chose “don’t want to take another medicine,” and 6 chose “worry about carcinogenic potential.” Others (n = 10) indicated that “patient/family adherence with hydroxyurea” and “patient/family adherence with required blood tests” were important barriers to hydroxyurea use. Eight of the 12 providers indicated that they were comfortable with managing hydroxyurea in patients with SCD.

Care redesign. Twenty SCD and primary care providers completed the Care Redesign section of the survey. Respondents (n = 11) indicated that they would see more patients with SCD if they had accessible case management services available without charge or if patient access to transportation to clinic was also available. Ten indicated that they would see more patients with SCD if they had an accessible community health worker (who understands patient’s/family’s social situation) and access to a pain management specialist on call to answer questions and who would manage chronic pain. All (n = 20) were willing to see more patients with SCD in their practices. Most reported that a clinical decision-support tool for SCD treatment (n = 13) and avoidance of complications (n = 12) would be useful.

Discussion

We evaluated access and barriers to care, quality of care, care coordination, and provider communication from the perspectives of adolescents and adults with SCD, their care providers, and community stakeholders, within the Solberg conceptual model for quality improvement. We found that barriers within the care process content domain (context and systems) were most salient for this population of adolescents and adults with SCD, with lack of provider knowledge and poor attitudes toward adolescents and adults with SCD, particularly in the ED, cited consistently by participant groups. Stigmatization and lack of provider compassion that affected the quality of care were particularly problematic. These findings are consistent with previous reports.^42,43 Adult health care (particularly ED) provider biases and negative attitudes have been recognized as major barriers to optimal pain management in SCD.^8,11,44,45 Interestingly, ED providers in our needs assessment indicated that they felt they had the training and resources to manage patients with SCD. However, only a few actually reported knowing about the NHLBI recommendations for the treatment of vaso-occlusive pain.

Within the care process content domain, we also found that SCD-related complications and associated emotions (fear, worry, anxiety), compounded by lack of access to knowledgeable and compassionate providers, pose a significant burden. Negative encounters with the health care system contributed to a striking 84% of patient participants choosing to manage severe pain at home, with pain seriously interfering with their ability to function on a daily basis. ED providers agreed that provider attitudes and implicit bias pose important barriers to care for adolescents and adults with SCD. Adolescents and adults with SCD wanted, and understood the need, to enhance self-management skills. Both they and their providers agreed that barriers to hydroxyurea uptake included worries about potential side effects, challenges with adherence to repeated laboratory testing, and support with remembering to take the medicine. However, providers uniformly expressed that access to behavioral and mental health services were, if not nonexistent, impossible to access.

Participants with SCD and their providers reported infrastructural challenges (change process capability), as manifested in limitations with accessing acute and preventive care due to transportation- and insurance- related issues. There were health system barriers that were particularly encountered during the transition from pediatric to adult care. These findings are consistent with previous reports that have found fewer interdisciplinary services available in the adult care settings compared with pediatrics.^46,47 Furthermore, adult care providers were less willing to accept adults with SCD because of the complexity of their management, for which the providers did not have the necessary expertise.^3,48-50 In addition, both adolescents and adults with SCD and primary care providers highlighted the inadequacies of the current system in addressing the chronic pain needs of this population. Linking back to the Solberg conceptual framework, our needs assessment results confirm the important role of establishing SCD care as a priority within a health care system—this requires leadership and vision. The vision and priorities must be implemented by effective health care teams. Multilevel approaches or interventions, when implemented, will lead to the desired outcomes.

Findings from our needs assessment within our 5-county region mirror needs assessment results from the broader consortium.⁵¹ The SCDIC has prioritized developing an intervention that addresses the challenges identified within the care process domain by directly enhancing provider access to patient individualized care plans in the electronic health record in the ED. Importantly, ED providers will be asked to view a short video that directly challenges bias and stigma in the ED. Previous studies have indeed found that attitudes can be improved by providers viewing short video segments of adults with SCD discussing their experiences.^36,52 This ED protocol will be one of the interventions that we will roll out in Northern California, given the significance of negative ED encounters reported by needs assessment participants. An additional feature of the intervention is a script for adults with SCD that guides them through introducing their individualized pain plan to their ED providers, thereby enhancing their self-efficacy in a situation that has been so overwhelmingly challenging.

We will implement a second SCDIC intervention that utilizes a mobile app to support self-management on the part of the patient, by supporting motivation and adherence with hydroxyurea.⁵³ A companion app supports hydroxyurea guideline adherence on the part of the provider, in keeping with one of our findings that providers are in need of decision-support tools. Elements of the intervention also align with our findings related to the importance of a support system in managing SCD, in that participants will identify a supportive partner who will play a specific role in supporting their adherence with hydroxyurea.

On our local level, we have, by necessity, partnered with leaders and community stakeholders throughout the region to ensure that these interventions to improve SCD care are prioritized. Grant funds provide initial resources for the SCDIC interventions, but our partnering health care administrators and medical directors must ensure that participating ED and hematology providers are free from competing priorities in order to implement the changes. We have partnered with a SCD community-based organization that is designing additional educational presentations for local emergency medicine providers, with the goal to bring to life very personal stories of bias and stigma within the EDs that directly contribute to decisions to avoid ED care despite severe symptoms.

Although we attempted to obtain samples of adolescents and adults with SCD and their providers that were representative across the 5-county region, the larger proportion of respondents were from 1 county. We did not assess concerns of age- and race-matched adults in our catchment area, so we cannot definitively say that our findings are unique to SCD. However, our results are consistent with findings from the national sample of adults with SCD who participated in the ASCQ-Me field test, and with results from the SCDIC needs assessment.^33,51 Interviews and surveys are subject to self-report bias and, therefore, may or may not reflect the actual behaviors or thoughts of participants. Confidence is increased in our results given the triangulation of expressed concerns across participant groups and across data collection strategies. The majority of adolescents and adults with SCD (95%) completed both the interview and survey, while 64% of ED providers interviewed completed the survey, compared with 54% of SCD specialists and primary care providers. These response rates are more than acceptable within the realm of survey response rates.^54,55

Although we encourage examining issues with care delivery within the conceptual framework for quality improvement presented, we recognize that grant funding allowed us to conduct an in-depth needs assessment that might not be feasible in other settings. Still, we would like readers to understand the importance of gathering data for improvement in a systematic manner across a range of participant groups, to ultimately inform the development of interventions and provide for evaluation of outcomes as a result of the interventions. This is particularly important for a disease, such as SCD, that is both medically and sociopolitically complex.

Conclusion

Our needs assessment brought into focus the multiple factors contributing to the disparities in health care experienced by adolescents and adults with SCD on our local level, and within the context of inequities in health resources and outcomes on the national level. We propose solutions that include specific interventions developed by a consortium of SCD and implementation science experts. We utilize a quality improvement framework to ensure that the elements of the interventions also address the barriers identified by our local providers and patients that are unique to our community. The pervasive challenges in SCD care, coupled with its medical complexities, may seem insurmountable, but our survey and qualitative results provide us with a road map for the way forward.

Acknowledgments: The authors thank the adolescents and adults with sickle cell disease, the providers, and the community stakeholders who completed the interviews and surveys. The authors also acknowledge the SCCCI co-investigators for their contributions to this project, including Michael Bell, MD, Ward Hagar, MD, Christine Hoehner, FNP, Kimberly Major, MSW, Anne Marsh, MD, Lynne Neumayr, MD, and Ted Wun, MD. We also thank Kamilah Bailey, Jameelah Hodge, Jennifer Kim, Michael Rowland, Adria Stauber, Amber Fearon, and Shanda Robertson, and the Sickle Cell Data Collection Program for their contributions.

Corresponding author: Marsha J. Treadwell, PhD, University of California San Francisco Benioff Children’s Hospital Oakland, 747 52nd St., Oakland, CA 94609; [email protected].

Financial disclosures: None.

Funding/support: This work was supported by grant # 1U01HL134007 from the National Heart, Lung, and Blood Institute to the University of California San Francisco Benioff Children’s Hospital Oakland.

From the University of California San Francisco (Dr. Treadwell, Dr. Hessler, Yumei Chen, Swapandeep Mushiana, Dr. Potter, and Dr. Vichinsky), the University of California Los Angeles (Dr. Jacob), and the University of California Berkeley (Alex Chen).

Abstract

• Objective: Adolescents and adults with sickle cell disease (SCD) face pervasive disparities in health resources and outcomes. We explored barriers to and facilitators of care to identify opportunities to support implementation of evidence-based interventions aimed at improving care quality for patients with SCD.
• Methods: We engaged a representative sample of adolescents and adults with SCD (n = 58), health care providers (n = 51), and community stakeholders (health care administrators and community-based organization leads (n = 5) in Northern California in a community-based needs assessment. We conducted group interviews separately with participant groups to obtain in-depth perspectives. Adolescents and adults with SCD completed validated measures of pain interference, quality of care, self-efficacy, and barriers to care. Providers and community stakeholders completed surveys about barriers to SCD care.
• Results: We triangulated qualitative and quantitative data and found that participants with SCD (mean age, 31 ± 8.6 years), providers, and community stakeholders emphasized the social and emotional burden of SCD as barriers. Concrete barriers agreed upon included insurance and lack of resources for addressing pain impact. Adolescents and adults with SCD identified provider issues (lack of knowledge, implicit bias), transportation, and limited social support as barriers. Negative encounters with the health care system contributed to 84% of adolescents and adults with SCD reporting they chose to manage severe pain at home. Providers focused on structural barriers: lack of access to care guidelines, comfort level with and knowledge of SCD management, and poor care coordination.
• Conclusion: Strategies for improving access to compassionate, evidence-based quality care, as well as strategies for minimizing the burden of having SCD, are warranted for this medically complex population.

Keywords: barriers to care; quality of care; care access; care coordination.

Sickle cell disease (SCD), an inherited chronic medical condition, affects about 100,000 individuals in the United States, a population that is predominantly African American.¹ These individuals experience multiple serious and life-threatening complications, most frequently recurrent vaso-occlusive pain episodes,² and they require interactions with multidisciplinary specialists from childhood. Because of advances in treatments, the majority are reaching adulthood; however, there is a dearth of adult health care providers with the training and expertise to manage their complex medical needs.³ Other concrete barriers to adequate SCD care include insurance and distance to comprehensive SCD centers.^4,5

Social, behavioral, and emotional factors may also contribute to challenges with SCD management. SCD may limit daily functional abilities and lead to diminished overall quality of life.^6,7 Some adolescents and adults may require high doses of opioids, which contributes to health care providers’ perceptions that there is a high prevalence of drug addiction in the population.^8,9 These providers express negative attitudes towards adults with SCD, and, consequently, delay medication administration when it is acutely needed and provide otherwise suboptimal treatment.^8,10,11 Adult care providers may also be uncomfortable with prescribing and managing disease-modifying therapies (blood transfusion, hydroxyurea) that have established efficacy.^12-17

As 1 of 8 programs funded by the National Heart, Lung, and Blood Institute’s (NHLBI) Sickle Cell Disease Implementation Consortium (SCDIC), we are using implementation science to reduce barriers to care and improve quality of care and health care outcomes in SCD.^18,19 Given that adolescents and adults with SCD experience high mortality, severe pain, and progressive decline in their ability to function day to day, and also face lack of access to knowledgeable, compassionate providers in primary and emergency settings, the SCDIC focuses on individuals aged 15 to 45 years.^6,8,9,11,12

Our regional SCDIC program, the Sickle Cell Care Coordination Initiative (SCCCI), brings together researchers, clinicians, adolescents, and adults with SCD and their families, dedicated community members, policy makers, and administrators to identify and address barriers to health care within 5 counties in Northern California. One of our first steps was to conduct a community-based needs assessment, designed to inform implementation of evidence-based interventions, accounting for unique contextual factors in our region.

Conceptual Framework for Improving Medical Practice

Our needs assessment is guided by Solberg’s Conceptual Framework for Improving Medical Practice (Figure 1).²⁰ Consistent with the overarching principles of the SCDIC, this conceptual framework focuses on the inadequate implementation of evidence-based guidelines, and on the need to first understand multifactorial facilitators and barriers to guideline implementation in order to effect change. The framework identifies 3 main elements that must be present to ensure improvements in quality-of-care processes and patient outcomes: priority, change process capability, and care process content. Priority refers to ample resource allocation for the specific change, as well as freedom from competing priorities for those implementing the change. Change process capability includes strong, effective leadership, adequate infrastructure for managing change (including resources and time), change management skills at all levels, and an established clinical information system. Care process content refers to context and systems-level changes, such as delivery system redesign as needed, support for self-management to lessen the impact of the disease, and decision support.^21-23

The purpose of our community-based needs assessment was to evaluate barriers to care and quality of care in SCD, within Solberg’s conceptual model for improving medical practice. The specific aims were to evaluate access and barriers to care (eg, lack of provider expertise and training, health care system barriers such as poor care coordination and provider communication); evaluate quality of care; and assess patient needs related to pain, pain interference, self-efficacy, and self-management for adolescents and adults with SCD. We gathered the perspectives of a representative community of adolescents and adults with SCD, their providers, and community stakeholders in order to examine barriers, quality of life and care, and patient experiences in our region.

Methods

Design

In this cross-sectional study, adolescents and adults with SCD, their providers, and community stakeholders participated in group or individual qualitative interviews and completed surveys between October 2017 and March 2018.

Setting and Sample

Recruitment flyers were posted on a regional SCD-focused website, and clinical providers or a study coordinator introduced information about the needs assessment to potential participants with SCD during clinic visits at the participating centers. Participants with SCD were eligible if they had any diagnosis of SCD, were aged 15 to 48 years, and received health services within 5 Northern California counties (Alameda, Contra Costa, Sacramento, San Francisco, and Solano). They were excluded if they did not have a SCD diagnosis or had not received health services within the catchment area. As the project proceeded, participants were asked to refer other adolescents and adults with SCD for the interviews and surveys (snowball sampling). Our goal was to recruit 50 adolescents and adults with SCD into the study, aiming for 10 representatives from each county.

Providers and community stakeholders were recruited via emails, letters and informational flyers. We engaged our partner, the Sickle Cell Data Collection Program,² to generate a list of providers and institutions that had seen patients with SCD in primary, emergency, or inpatient settings in the region. We contacted these institutions to describe the SCCCI and invite participation in the needs assessment. We also invited community-based organization leads and health care administrators who worked with SCD to participate. Providers accessed confidential surveys via a secure link on the study website or completed paper versions. Common data collected across providers included demographics and descriptions of practice settings.

Participants were eligible to be part of the study if they were health care providers (physicians and nurses) representing hematology, primary care, family medicine, internal medicine, or emergency medicine; ancillary staff (social work, psychology, child life); or leaders or administrators of clinical or sickle cell community-based organizations in Northern California (recruitment goal of n = 50). Providers were excluded if they practiced in specialties other than those noted or did not practice within the region.

Data Collection Procedures

After providing assent/consent, participating adolescents and adults with SCD took part in individual and group interviews and completed survey questionnaires. All procedures were conducted in a private space in the sickle cell center or community. Adolescents and adults with SCD completed the survey questionnaire on a tablet, with responses recorded directly in a REDCap (Research Electronic Data Capture) database,²⁴ or on a paper version. Interviews lasted 60 (individual) to 90 (group) minutes, while survey completion time was 20 to 25 minutes. Each participant received a gift card upon completion as an expression of appreciation. All procedures were approved by the institutional review boards of the participating health care facilities.

Group and Individual Interviews

Participants with SCD and providers were invited to participate in a semi-structured qualitative interview prior to being presented with the surveys. Adolescents and adults with SCD were interviewed about barriers to care, quality of care, and pain-related experiences. Providers were asked about barriers to care and treatments. Interview guides were modified for community-based organization leaders and health care administrators who did not provide clinical services. Interview guides can be found in the Appendix. Interviews were conducted by research coordinators trained in qualitative research methods by the first author (MT). As appropriate with semi-structured interviews, the interviewers could word questions spontaneously, change the order of questions for ease of flow of conversation, and inform simultaneous coding of interviews with new themes as those might arise, as long as they touched on all topics within the interview guide.²⁵ The interview guides were written, per qualitative research standards, based on the aims and purpose of the research,²⁶ and were informed by existing literature on access and barriers to care in SCD, quality of care, and the needs of individuals with SCD, including in relation to impact of the disease, self-efficacy, and self-management.

Interviewees participated in either individual or group interviews, but not both. The decision for which type of interview an individual participated in was based on 2 factors: if there were not comparable participants for group interviews (eg, health care administrator and community-based organization lead), these interviews were done individually; and given that we were drawing participants from a 5-county area in Northern California, scheduling was challenging for individuals with SCD with regard to aligning schedules and traveling to a central location where the group interviews were conducted. Provider group interviews were easier to arrange because we could schedule them at the same time as regularly scheduled meetings at the participants’ health care institutions.

Interview Data Gathering and Analysis

Digital recordings of the interviews were cleaned of any participant identifying data and sent for transcription to an outside service. Transcripts were reviewed for completeness and imported into NVivo (www.qsrinternational.com), a qualitative data management program.

A thematic content analysis and deductive and inductive approaches were used to analyze the verbatim transcripts generated from the interviews. The research team was trained in the use of NVivo software to facilitate the coding process. A deductive coding scheme was initially used based on existing concepts in the literature regarding challenges to optimal SCD care, with new codes added as the thematic content analyses progressed. The initial coding, pattern coding, and use of displays to examine the relationships between different categories were conducted simultaneously.^27,28 Using the constant comparative method, new concepts from participants with SCD and providers could be incorporated into subsequent interviews with other participants. For this study, the only additional concepts added were in relation to participant recruitment and retention in the SCDIC Registry. Research team members coded transcripts separately and came together weekly, constantly comparing codes and developing the consensus coding scheme. Where differences between coders existed, code meanings were discussed and clarified until consensus was reached.²⁹

Quantitative data were analyzed using SPSS (v. 25, Chicago, IL). Descriptive statistics (means, standard deviations, frequencies, percentages) were used to summarize demographics (eg, age, gender, and race), economic status, and type of SCD. No systematic differences were detected from cases with missing values. Scale reliabilities (ie, Cronbach α) were evaluated for self-report measures.

Measurement

Adolescents and adults with SCD completed items from the PhenX Toolkit (consensus measures for Phenotypes and eXposures), assessing sociodemographics (age, sex, race, ethnicity, educational attainment, occupation, marital status, annual income, insurance), and clinical characteristics (sickle cell diagnosis and emergency department [ED] and hospital utilization for pain).³⁰

Pain Interference Short Form (Patient-Reported Outcomes Measurement Information System [PROMIS]). The Pain Interference Form consists of 8 items that assess the degree to which pain interfered with day-to-day activities in the previous 7 days at home, including impacts on social, cognitive, emotional, and physical functioning; household chores and recreational activities; sleep; and enjoyment in life. Reliability and validity of the PROMIS Pain Interference Scale has been demonstrated, with strong negative correlations with Physical Function Scales (r = 0.717, P < 0.01), indicating that higher scores are associated with lower function (β = 0.707, P < 0.001).³¹ The Cronbach α estimate for the other items on the pain interference scale was 0.99. Validity analysis indicated strong correlations with pain-related domains: BPI Interference Subscale (rho = 0.90), SF-36 Bodily Pain Subscale (rho = –0.84), and 0–10 Numerical Rating of Pain Intensity (rho = 0.48).³²

Adult Sickle Cell Quality of Life Measurement Information System (ASCQ-Me) Quality of Care (QOC). ASCQ-Me QOC consists of 27 items that measure the quality of care that adults with SCD have received from health care providers.³³ There are 3 composites: provider communication (quality of patient and provider communication), ED care (quality of care in the ED), and access (to routine and emergency care). Internal consistency reliability for all 3 composites is greater than 0.70. Strong correlations of the provider communication composite with overall ratings of routine care (r = 0.65) and overall provider ratings (r = 0.83) provided evidence of construct validity. Similarly, the ED care composite was strongly correlated with overall ratings of QOC in the ED, and the access composite was highly correlated with overall evaluations of ED care (r = 0.70). Access, provider interaction, and ED care composites were reliable (Cronbach α, 0.70–0.83) and correlated with ratings of global care (r = 0.32–0.83), further indicating construct validity.³³

Sickle Cell Self-Efficacy Scale (SCSES). The SCSES is a 9-item, self-administered questionnaire measuring perceptions of the ability to manage day-to-day issues resulting from SCD. SCSES items are scored on a 5-point scale ranging from Not sure at all (1) to Very sure (5). Individual item responses are summed to give an overall score, with higher scores indicating greater self-efficacy. The SCSES has acceptable reliability (r = 0.45, P < 0.001) and validity (α = 0.89).^34,35

Sickle Cell Disease Barriers Checklist. This checklist consists of 53 items organized into 8 categories: insurance, transportation, accommodations and accessibility, provider knowledge and attitudes, social support, individual barriers such as forgetting or difficulties understanding instructions, emotional barriers (fear, anger), and disease-related barriers. Participants check applicable barriers, with a total score range of 0 to 53 and higher scores indicating more barriers to care. The SCD Barriers Checklist has demonstrated face validity and test-retest reliability (Pearson r = 0.74, P < 0.05).⁵

ED Provider Checklist. The ED provider survey is a checklist of 14 statements pertaining to issues regarding patient care, with which the provider rates level of agreement. Items representing the attitudes and beliefs of providers towards patients with SCD are rated on a Likert-type scale, with level of agreement indicated as 1 (strongly disagree) to 6 (strongly agree). The positive attitudes subscale consists of 4 items (Cronbach α= 0.85), and the negative attitudes subscale consists of 6 items (Cronbach α = 0.89). The Red-Flag Behaviors subscale includes 4 items that indicate behavior concerns about drug-seeking, such as requesting specific narcotics and changing behavior when the provider walks in.^8,36,37

Sickle cell and primary care providers also completed a survey consisting of sets of items compiled from existing provider surveys; this survey consisted of a list of 16 barriers to using opioids, which the providers rated on a 5-point Likert-type scale (1, not a barrier; 5, complete barrier).^13,16,38 Providers indicated their level of experience with caring for patients with SCD; care provided, such as routine health screenings; and comfort level with providing preventive care, managing comorbidities, and managing acute and chronic pain. Providers were asked what potential facilitators might improve care for patients with SCD, including higher reimbursement, case management services, access to pain management specialists, and access to clinical decision-support tools. Providers responded to specific questions about management with hydroxyurea (eg, criteria for, barriers to, and comfort level with prescribing).³⁹ The surveys are included in the Appendix.

Triangulation

Data from the interviews and surveys were triangulated to enhance understanding of results generated from the different data sources.⁴⁰ Convergence of findings, different facets of the same phenomenon, or new perspectives were examined.

Qualitative Data

Adolescents and adults with SCD (n = 55) and health care providers and community stakeholders (n = 56) participated in group or individual interviews to help us gain an in-depth understanding of the needs and barriers related to SCD care in our 5-county region. Participants with SCD described their experiences, which included stigma, racism, labeling, and, consequently, stress. They also identified barriers such as lack of transportation, challenges with insurance, and lack of access to providers who were competent with pain management. They reported that having SCD in a health care system that was unable to meet their needs was burdensome.

Barriers to Care and Treatments. Adolescents and adults indicated that SCD and its sequelae posed significant barriers to health care. Feelings of tiredness and pain make it more difficult for them to seek care. The emotional burden of SCD (fear and anger) was a frequently cited barrier, which was fueled by previous negative encounters with the health care system. All adolescents and adults with SCD reported that they knew of stigma in relation to seeking pain management that was pervasive and long-standing, and the majority reported they had directly experienced stigma. They reported that being labeled as “drug-seekers” was typical when in the ED for pain management. Participants articulated unconscious bias or overt racism among providers: “people with sickle cell are Black ... and Black pain is never as valuable as White pain” (25-year-old male). Respondents with SCD described challenges to the credibility of their pain reports in the ED. They reported that ED providers expressed doubts regarding the existence and/or severity of their pain, consequently creating a feeling of disrespect for patients seeking pain relief. The issue of stigma was mentioned by only 2 of 56 providers during their interviews.

Lack of Access to Knowledgeable, Compassionate Providers. Lack of access to knowledgeable care providers was another prevalent theme expressed by adolescents and adults with SCD. Frustration occurred when providers did not have knowledge of SCD and its management, particularly pain assessment. Adolescents and adults with SCD noted the lack of compassion among providers: “I’ve been kicked out of the hospital because they felt like okay, well we gave you enough medication, you should be all right” (29-year-old female). Providers specifically mentioned lack of compassion and knowledge as barriers to SCD care much less often during their interviews compared with the adolescents and adults with SCD.

Health Care System Barriers. Patient participants often expressed concerns about concrete and structural aspects of care. Getting to their appointments was a challenge for half of the interviewees, as they either did not have access to a vehicle or could not afford to travel the needed distance to obtain quality care. Even when hospitals were accessible by public transportation, those with excruciating pain understandably preferred a more comfortable and private way to travel: “I would like to change that, something that will be much easier, convenient for sickle cell patients that do suffer with pain, that they don’t have to travel always to see the doctor” (30-year-old male).

Insurance and other financial barriers also played an important role in influencing decisions to seek health care services. Medical expenses were not covered, or co-pays were too high. The Medicaid managed care system could prevent access to knowledgeable providers who were not within network. Such a lack of access discouraged some adolescents and adults with SCD from seeking acute and preventive care.

Transition From Pediatric to Adult Care. Interviewees with SCD expressed distress about the gap between pediatric and adult care. They described how they had a long-standing relationship with their medical providers, who were familiar with their medical background and history from childhood. Adolescent interviewees reported an understanding of their own pain management as well as adherence to and satisfaction with their individualized pain plans. However, adults noted that satisfaction plummeted with increasing age due to the limited number of experienced adult SCD providers, which was compounded by negative experiences (stigma, racism, drug-seeking label).

One interviewee emphasized the difficulty of finding knowledgeable providers after transition: “When you’re a pediatric sickle cell [patient], you have the doctors there every step of the way, but not with adult sickle cell… I know when I first transitioned I never felt more alone in my life… you look at that ER doctor kind of with the same mindset as you would your hematologist who just hand walked you through everything. And adult care providers were a lot more blunt and cold and they’re like… ‘I don’t know; I’m not really educated in sickle cell.’” A sickle cell provider shared his insight about the problem of transitioning: “I think it’s particularly challenging because we, as a community, don’t really set them up for success. It’s different from other chronic conditions [in that] it’s much harder to find an adult sickle cell provider. There’s not a lot of adult hematologists that will take care of our adult patients, and so I know statistically, there’s like a drop-down in the overall outcomes of our kids after they age out of our pediatric program.”

Self-Management, Supporting Hydroxyurea Use. Interview participants with SCD reported using a variety of methods to manage pain at home and chose to go to the ED only when the pain became intolerable. Patients and providers expressed awareness of different resources for managing pain at home, yet they also indicated that these resources have not been consolidated in an accessible way for patients and families. Some resources cited included heat therapy, acupuncture, meditation, medical marijuana, virtual reality devices, and pain medications other than opioids.

Patients and providers expressed the need for increasing awareness and education about hydroxyurea. Many interview participants with SCD were concerned about side effects, multiple visits with a provider during dose titration, and ongoing laboratory monitoring. They also expressed difficulties with scheduling multiple appointments, depending on access to transportation and limited provider clinic hours. They were aware of strategies for improving adherence with hydroxyurea, including setting phone alarms, educating family members about hydroxyurea, and eliciting family support, but expressed needing help to consistently implement these strategies.

Safe Opioid Prescribing. Adult care providers expressed concerns about safe opioid prescribing for patients with SCD. They were reluctant to prescribe opioid doses needed to adequately control SCD pain. Providers expressed uncertainty and fear or concern about medical/legal liability or about their judgment about what’s safe and not safe for patients with chronic use/very high doses of opioids. “I know we’re in like this opiate epidemic here in this country but I feel like these patients don’t really fit under that umbrella that the problem is coming from so [I am] just trying to learn more about how to take care of them.”

Care Coordination and Provider Communication. Adolescents and adults with SCD reported having positive experiences—good communication, established trust, and compassionate care—with their usual providers. However, they perceived that ED physicians and nurses did not really care about them. Both interviewees with SCD and providers recognized the importance of good communication in all settings as the key to overcoming barriers to receiving quality care. All agreed on the importance of using individual pain plans so that all providers, especially ED providers, can be more at ease with treating adolescents and adults with SCD.

Quantitative Data: Adolescents and Adults With SCD

Fifty-eight adolescents and adults with SCD (aged 15 to 48 years) completed the survey. Three additional individuals who did not complete the interview completed the survey. Reasons for not completing the interview included scheduling challenges (n = 2) or a sickle cell pain episode (n = 1). The average age of participants was 31 years ± 8.6, more than half (57%) were female, and the majority (93%) were African American (Table 1). Most (71%) had never been married. Half (50%) had some college or an associate degree, and 40% were employed and reported an annual household income of less than $30,000. Insurance coverage was predominantly Medi-Cal (Medicaid, 69%). The majority of participants resided in Alameda (34.5%) or Contra Costa (21%) counties. The majority of sickle cell care was received in Alameda County, whether outpatient (52%), inpatient (40%), or ED care (41%). The majority (71%) had a diagnosis of SCD hemoglobin SS.

Pain. More than one-third of individuals with SCD reported 1 or 2 ED visits for pain in the previous 6 months (34%), and more than 3 hospitalizations (36%) related to pain in the previous year (Table 2). The majority (85%) reported having severe pain at home in the previous 6 months that they did not seek health care for, consistent with their reports in the qualitative interviews. More than half (59%) reported 4 or more of these severe pain episodes that led to inability to perform daily activities for 1 week or more. While pain interference on the PROMIS Pain Interference Short Form on average (T-score, 59.6 ± 8.6) was similar to that of the general population (T-score, 50 ± 10), a higher proportion of patients with SCD reported pain interference compared with the general population. The mean self-efficacy (confidence in ability to manage complications of SCD) score on the SCSES of 30.0 ± 7.3 (range, 9–45) was similar to that of other adults with SCD (mean, 32.2 ± 7.0). Twenty-five percent of the present sample had a low self-efficacy score (< 25).

Barriers to Care and Treatments. Consistent with the qualitative data, SCD-related symptoms such as tiredness (64%) and pain (62%) were reported most often as barriers to care (Table 3). Emotions (> 25%) such as worry/fear, frustration/anger, and lack of confidence were other important barriers to care. Provider knowledge and attitudes were cited next most often, with 38% of the sample indicating “Providers accuse me of drug-seeking” and “It is hard for me to find a provider who has enough experiences with or knowledge about SCD.” Participants expressed that they were not believed when in pain and “I am treated differently from other patients.” Almost half of respondents cited “I am not seen quickly enough when I am in pain” as a barrier to their care.

Consistent with the qualitative data, transportation barriers (not having a vehicle, costs of transportation, public transit not easy to get to) were cited by 55% of participants. About half of participants reported that insurance was an important barrier, with high co-pays and medications and other services not covered. In addition, gathering approvals was a long and fragmented process, particularly for consultations among providers (hematology, primary care provider, pain specialist). Furthermore, insurance provided limited choices about location for services.

Participants reported social support system burnout (22%), help needed with daily activities (21%), and social isolation or generally not having enough support (33%) as ongoing barriers. Difficulties were encountered with self-management (eg, taking medications on time or making follow-up appointments, 19%), with 22% of participants finding the health care system confusing or hard to understand. Thirty percent reported “Places for me to go to learn how to stay well are not close by or easy to get to.” ”Worry about side effects” (33%) was a common barrier to hydroxyurea use. Participants described “forgetting to take the medicine,” “tried before but it did not work,” “heard scary things” about hydroxyurea, and “not interested in taking another medicine” as barriers.

Quality of Care. More than half (51%) of the 53 participants who had accessed health care in the previous year rated their overall health care as poor on the ASCQ-Me QOC measure. This was significantly higher compared to the reports from more than 47,000 adults with Medicaid in 2017 (16%),⁴¹ and to the 2008-2009 report from 556 adults with SCD from across the United States (37%, Figure 2).³³ The major contributor to these poor ratings for participants in our sample was low satisfaction with ED care.

Sixty percent of the 42 participants who had accessed ED care in the past year indicated “never” or “sometimes” to the question “When you went to the ED for care, how often did you get it as soon as you wanted?” compared with only 16% of the 2017 adult Medicaid population responding (n = 25,789) (Figure 3). Forty-seven percent of those with an ED visit indicated that, in the previous 12 months, they had been made to wait “more than 2 hours before receiving treatment for acute pain in the ED.” However, in the previous 12 months, 39% reported that their wait time in the ED had been only “between five minutes and one hour.”

On the ASCQ-Me QOC Access to Care composite measure, 33% of 42 participants responding reported they were seen at a routine appointment as soon as they would have liked. This is significantly lower compared to 56% of the adult Medicaid population responding to the same question. Reports of provider communication (Provider Communication composite) for adolescents and adults with SCD were comparable to reports of adults with SCD from the ASCQ-Me field test,³³ but adults with Medicaid reported higher ratings of quality communication behaviors (Figure 4).^33,41 Nearly 60% of both groups with SCD reported that providers “always” performed quality communication behaviors—listened carefully, spent enough time, treated them with respect, and explained things well—compared with more than 70% of adults with Medicaid.

Participants from all counties reported the same number of barriers to care on average (3.3 ± 2.1). Adolescents and adults who reported more barriers to care also reported lower satisfaction with care (r = –0.47, P < 0.01) and less confidence in their ability to manage their SCD (self-efficacy, r = – 0.36, P < 0.05). Female participants reported more barriers to care on average compared with male participants (2.6 ± 2.4 vs 1.4 ± 2.0, P = 0.05). Participants with higher self-efficacy reported lower pain ratings (r = –0.47, P < 0.001).

Quantitative Data: Health Care Providers

Providers (n = 56) and community stakeholders (2 leaders of community-based organizations and 3 health care administrators) were interviewed, with 29 also completing the survey. The reason for not completing (n = 22) was not having the time once the interview was complete. A link to the survey was sent to any provider not completing at the time of the interview, with 2 follow-up reminders. The majority of providers were between the ages of 31 and 50 years (46.4%), female (71.4%), and white (66.1%) (Table 4). None were of Hispanic, Latinx, or Spanish origin. Thirty-six were physicians (64.3%), and 16 were allied health professionals (28.6%). Of the 56 providers, 32 indicated they had expertise caring for patients with SCD (57.1%), 14 were ED providers (25%), and 5 were primary care providers. Most of the providers practiced in an urban setting (91.1%).

Barriers to Care: ED Provider Perspectives. Nine of 14 ED providers interviewed completed the survey on their perspectives regarding barriers to care in the ED, difficulty with follow-ups, ED training resources, and pain control for patients with SCD. ED providers (n = 8) indicated that “provider attitudes” were a barrier to care delivery in the ED for patients with SCD. Some providers (n = 7) indicated that “implicit bias,” “opioid epidemic,” “concern about addiction,” and “patient behavior” were barriers. Respondents indicated that “overcrowding” (n = 6) and “lack of care pathway/protocol” (n = 5) were barriers. When asked to express their level of agreement with statements about SCD care in the ED, respondents disagreed/strongly disagreed (n = 5) that they were “able to make a follow-up appointment” with a sickle cell specialist or primary care provider upon discharge from the ED, and others disagreed/strongly disagreed (n = 4) that they were able to make a “referral to a case management program.”

ED training and resources. Providers agreed/strongly agreed (n = 8) that they had the knowledge and training to care for patients with SCD, that they had access to needed medications, and that they had access to knowledgeable nursing staff with expertise in SCD care. All 9 ED providers indicated that they had sufficient physician/provider staffing to provide good pain management to persons with SCD in the ED.

Pain control in the ED. Seven ED providers indicated that their ED used individualized dosing protocols to treat sickle cell pain, and 5 respondents indicated their ED had a protocol for treating sickle cell pain. Surprisingly, only 3 indicated that they were aware of the NHLBI recommendations for the treatment of vaso-occlusive pain.

Barriers to Care: Primary Care Provider Perspectives. Twenty providers completed the SCD provider section of the survey, including 17 multidisciplinary SCD providers from 4 sickle cell special care centers and 3 community primary care providers. Of the 20, 12 were primary care providers for patients with SCD (Table 4).

Patient needs. Six primary care providers indicated that the medical needs of patients with SCD were being met, but none indicated that the behavioral health or mental health needs were being met.

Managing SCD comorbidities. Five primary care providers indicated they were very comfortable providing preventive ambulatory care to patients with SCD. Six indicated they were very comfortable managing acute pain episodes, but none were very comfortable managing comorbidities such as pulmonary hypertension, diabetes, or chronic pain.

Barriers to opioid use. Only 3 of 12 providers reviewing a list of 15 potential barriers to the use of opioids for SCD pain management indicated a perceived lack of efficacy of opioids, development of tolerance and dependence, and concerns about community perceptions as barriers. Two providers selected potential for diversion as a moderate barrier to opioid use.

Barriers to hydroxyurea use. Eight of 12 providers indicated that the common reasons that patients/families refuse hydroxyurea were “worry about side effects”; 7 chose “don’t want to take another medicine,” and 6 chose “worry about carcinogenic potential.” Others (n = 10) indicated that “patient/family adherence with hydroxyurea” and “patient/family adherence with required blood tests” were important barriers to hydroxyurea use. Eight of the 12 providers indicated that they were comfortable with managing hydroxyurea in patients with SCD.

Care redesign. Twenty SCD and primary care providers completed the Care Redesign section of the survey. Respondents (n = 11) indicated that they would see more patients with SCD if they had accessible case management services available without charge or if patient access to transportation to clinic was also available. Ten indicated that they would see more patients with SCD if they had an accessible community health worker (who understands patient’s/family’s social situation) and access to a pain management specialist on call to answer questions and who would manage chronic pain. All (n = 20) were willing to see more patients with SCD in their practices. Most reported that a clinical decision-support tool for SCD treatment (n = 13) and avoidance of complications (n = 12) would be useful.

Discussion

We evaluated access and barriers to care, quality of care, care coordination, and provider communication from the perspectives of adolescents and adults with SCD, their care providers, and community stakeholders, within the Solberg conceptual model for quality improvement. We found that barriers within the care process content domain (context and systems) were most salient for this population of adolescents and adults with SCD, with lack of provider knowledge and poor attitudes toward adolescents and adults with SCD, particularly in the ED, cited consistently by participant groups. Stigmatization and lack of provider compassion that affected the quality of care were particularly problematic. These findings are consistent with previous reports.^42,43 Adult health care (particularly ED) provider biases and negative attitudes have been recognized as major barriers to optimal pain management in SCD.^8,11,44,45 Interestingly, ED providers in our needs assessment indicated that they felt they had the training and resources to manage patients with SCD. However, only a few actually reported knowing about the NHLBI recommendations for the treatment of vaso-occlusive pain.

Within the care process content domain, we also found that SCD-related complications and associated emotions (fear, worry, anxiety), compounded by lack of access to knowledgeable and compassionate providers, pose a significant burden. Negative encounters with the health care system contributed to a striking 84% of patient participants choosing to manage severe pain at home, with pain seriously interfering with their ability to function on a daily basis. ED providers agreed that provider attitudes and implicit bias pose important barriers to care for adolescents and adults with SCD. Adolescents and adults with SCD wanted, and understood the need, to enhance self-management skills. Both they and their providers agreed that barriers to hydroxyurea uptake included worries about potential side effects, challenges with adherence to repeated laboratory testing, and support with remembering to take the medicine. However, providers uniformly expressed that access to behavioral and mental health services were, if not nonexistent, impossible to access.

Participants with SCD and their providers reported infrastructural challenges (change process capability), as manifested in limitations with accessing acute and preventive care due to transportation- and insurance- related issues. There were health system barriers that were particularly encountered during the transition from pediatric to adult care. These findings are consistent with previous reports that have found fewer interdisciplinary services available in the adult care settings compared with pediatrics.^46,47 Furthermore, adult care providers were less willing to accept adults with SCD because of the complexity of their management, for which the providers did not have the necessary expertise.^3,48-50 In addition, both adolescents and adults with SCD and primary care providers highlighted the inadequacies of the current system in addressing the chronic pain needs of this population. Linking back to the Solberg conceptual framework, our needs assessment results confirm the important role of establishing SCD care as a priority within a health care system—this requires leadership and vision. The vision and priorities must be implemented by effective health care teams. Multilevel approaches or interventions, when implemented, will lead to the desired outcomes.

Findings from our needs assessment within our 5-county region mirror needs assessment results from the broader consortium.⁵¹ The SCDIC has prioritized developing an intervention that addresses the challenges identified within the care process domain by directly enhancing provider access to patient individualized care plans in the electronic health record in the ED. Importantly, ED providers will be asked to view a short video that directly challenges bias and stigma in the ED. Previous studies have indeed found that attitudes can be improved by providers viewing short video segments of adults with SCD discussing their experiences.^36,52 This ED protocol will be one of the interventions that we will roll out in Northern California, given the significance of negative ED encounters reported by needs assessment participants. An additional feature of the intervention is a script for adults with SCD that guides them through introducing their individualized pain plan to their ED providers, thereby enhancing their self-efficacy in a situation that has been so overwhelmingly challenging.

We will implement a second SCDIC intervention that utilizes a mobile app to support self-management on the part of the patient, by supporting motivation and adherence with hydroxyurea.⁵³ A companion app supports hydroxyurea guideline adherence on the part of the provider, in keeping with one of our findings that providers are in need of decision-support tools. Elements of the intervention also align with our findings related to the importance of a support system in managing SCD, in that participants will identify a supportive partner who will play a specific role in supporting their adherence with hydroxyurea.

On our local level, we have, by necessity, partnered with leaders and community stakeholders throughout the region to ensure that these interventions to improve SCD care are prioritized. Grant funds provide initial resources for the SCDIC interventions, but our partnering health care administrators and medical directors must ensure that participating ED and hematology providers are free from competing priorities in order to implement the changes. We have partnered with a SCD community-based organization that is designing additional educational presentations for local emergency medicine providers, with the goal to bring to life very personal stories of bias and stigma within the EDs that directly contribute to decisions to avoid ED care despite severe symptoms.

Although we attempted to obtain samples of adolescents and adults with SCD and their providers that were representative across the 5-county region, the larger proportion of respondents were from 1 county. We did not assess concerns of age- and race-matched adults in our catchment area, so we cannot definitively say that our findings are unique to SCD. However, our results are consistent with findings from the national sample of adults with SCD who participated in the ASCQ-Me field test, and with results from the SCDIC needs assessment.^33,51 Interviews and surveys are subject to self-report bias and, therefore, may or may not reflect the actual behaviors or thoughts of participants. Confidence is increased in our results given the triangulation of expressed concerns across participant groups and across data collection strategies. The majority of adolescents and adults with SCD (95%) completed both the interview and survey, while 64% of ED providers interviewed completed the survey, compared with 54% of SCD specialists and primary care providers. These response rates are more than acceptable within the realm of survey response rates.^54,55

Although we encourage examining issues with care delivery within the conceptual framework for quality improvement presented, we recognize that grant funding allowed us to conduct an in-depth needs assessment that might not be feasible in other settings. Still, we would like readers to understand the importance of gathering data for improvement in a systematic manner across a range of participant groups, to ultimately inform the development of interventions and provide for evaluation of outcomes as a result of the interventions. This is particularly important for a disease, such as SCD, that is both medically and sociopolitically complex.

Conclusion

Our needs assessment brought into focus the multiple factors contributing to the disparities in health care experienced by adolescents and adults with SCD on our local level, and within the context of inequities in health resources and outcomes on the national level. We propose solutions that include specific interventions developed by a consortium of SCD and implementation science experts. We utilize a quality improvement framework to ensure that the elements of the interventions also address the barriers identified by our local providers and patients that are unique to our community. The pervasive challenges in SCD care, coupled with its medical complexities, may seem insurmountable, but our survey and qualitative results provide us with a road map for the way forward.

Acknowledgments: The authors thank the adolescents and adults with sickle cell disease, the providers, and the community stakeholders who completed the interviews and surveys. The authors also acknowledge the SCCCI co-investigators for their contributions to this project, including Michael Bell, MD, Ward Hagar, MD, Christine Hoehner, FNP, Kimberly Major, MSW, Anne Marsh, MD, Lynne Neumayr, MD, and Ted Wun, MD. We also thank Kamilah Bailey, Jameelah Hodge, Jennifer Kim, Michael Rowland, Adria Stauber, Amber Fearon, and Shanda Robertson, and the Sickle Cell Data Collection Program for their contributions.

Corresponding author: Marsha J. Treadwell, PhD, University of California San Francisco Benioff Children’s Hospital Oakland, 747 52nd St., Oakland, CA 94609; [email protected].

Financial disclosures: None.

Funding/support: This work was supported by grant # 1U01HL134007 from the National Heart, Lung, and Blood Institute to the University of California San Francisco Benioff Children’s Hospital Oakland.

Annually, more than 40 million noncardiac surgeries take place in the US,¹ with 1%-3% of patients experiencing a major adverse cardiovascular event (MACE) such as acute myocardial infarction (AMI) or cardiac arrest postoperatively.² Such patients are at markedly increased risk of both perioperative and long-term death.^2-5

Over the past 40 years, efforts to model the risk of cardiac complications after noncardiac surgery have examined relationships between preoperative risk factors and postoperative cardiovascular events. The resulting risk-stratification tools, such as the Lee Revised Cardiac Risk Index (RCRI), have been used to inform perioperative care, including strategies for risk factor management prior to surgery, testing for cardiac events after surgery, and decisions regarding postoperative disposition.⁶ However, tools used in practice have not incorporated intraoperative data on hemodynamics or medication administration in the transition to postoperative care, which is often provided by nonsurgical clinicians such as hospitalists. Presently, there is active debate about the optimal approach to postoperative evaluation and management of MACE, particularly with regard to indications for cardiac biomarker testing after surgery in patients without signs or symptoms of acute cardiac syndromes. The lack of consensus is reflected in differences among guidelines for postoperative cardiac biomarker testing across professional societies in Europe, Canada, and the United States.^7-9

In this study, we examined whether the addition of intraoperative data to preoperative data (together, perioperative data) improved prediction of MACE after noncardiac surgery when compared with RCRI. Additionally, to investigate how such a model could be applied in practice, we compared risk stratification based on our model to a published risk factor–based guideline algorithm for postoperative cardiac biomarker testing.⁷ In particular, we evaluated to what extent patients recommended for postoperative cardiac biomarkers under the risk factor–based guideline algorithm would be reclassified as low risk by the model using perioperative data. Conducting biomarker tests on these patients would potentially represent low-value care. We hypothesized that adding intraoperative data would (a) lead to improved prediction of MACE complications when compared with RCRI and (b) more effectively identify, compared with a risk factor–based guideline algorithm, patients for whom cardiac biomarker testing would or would not be clinically meaningful.

We followed the Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis (TRIPOD) reporting guideline.¹⁰

Study Data

Baseline, preoperative, and intraoperative data were collected for patients undergoing surgery between January 2014 and April 2018 within the University of Pennsylvania Health System (UPHS) electronic health record (EHR), and these data were then integrated into a comprehensive perioperative dataset (data containing administrative, preoperative, intraoperative, and postoperative information related to surgeries) created through a collaboration with the Multicenter Perioperative Outcomes Group.¹¹ The University of Pennsylvania Institutional Review Board approved this study.

Study Population

Patients aged 18 years or older who underwent inpatient major noncardiac surgery across four tertiary academic medical centers within UPHS in Pennsylvania during the study period were included in the cohort (see Appendix for inclusion/exclusion criteria).^12,13 Noncardiac surgery was identified using primary Current Procedural Terminology (CPT) code specification ranges for noncardiac surgeries 10021-32999 and 34001-69990. The study sample was divided randomly into a training set (60%), validation (20%), and test set (20%),¹⁴ with similar rates of MACE in the resulting sets. We used a holdout test set for all final analyses to avoid overfitting during model selection.

Outcomes

The composite outcome used to develop the risk-stratification models was in-hospital MACE after major noncardiac surgery. Following prior literature, MACE was defined using billing codes for ST-elevation/non–ST-elevation myocardial infarction (STEMI/NSTEMI, ICD-9-CM 410.xx, ICD-10-CM I21.xx), cardiac arrest (ICD-9-CM 427.5, ICD-10-CM I46.x, I97.121), or all-cause in-hospital death.^2,15-17

Variables

Variables were selected from baseline administrative, preoperative clinical, and intraoperative clinical data sources (full list in Appendix). Baseline variables included demographics, insurance type, and Elixhauser comorbidities.^18,19 Preoperative variables included surgery type, laboratory results, and American Society of Anesthesiologists (ASA) Physical Status classification.²⁰ Intraoperative variables included vital signs, estimated blood loss, fluid administration, and vasopressor use. We winsorized outlier values and used multiple imputation to address missingness. Rates of missing data can be found in Appendix Table 1.

Risk-Stratification Models Used as Comparisons

Briefly, RCRI variables include the presence of high-risk surgery,²¹ comorbid cardiovascular diseases (ie, ischemic heart disease, congestive heart failure, and cerebrovascular disease), preoperative use of insulin, and elevated preoperative serum creatinine.⁶ RCRI uses the inputs to calculate a point score that equates to different risk strata and is based on a stepwise logistic regression model with postoperative cardiovascular complications as the dependent outcome variable. For this study, we implemented the weighted version of the RCRI algorithm and computed the point scores (Appendix).^6,7,22

We also applied a risk factor–based algorithm for postoperative cardiac biomarker testing published in 2017 by the Canadian Cardiovascular Society (CCS) guidelines to each patient in the study sample.⁷ Specifically, this algorithm recommends daily troponin surveillance for 48 to 72 hours after surgery among patients who have (1) an elevated NT-proBNP/BNP measurement or no NT-proBNP/BNP measurement before surgery, (2) have a Revised Cardiac Risk Index score of 1 or greater, (3) are aged 65 years and older, (4) are aged 45 to 64 years with significant cardiovascular disease undergoing elective surgery, or (5) are aged 18 to 64 years with significant cardiovascular disease undergoing semiurgent, urgent, or emergent surgery.

Statistical Analysis

We compared patient characteristics and outcomes between those who did and those who did not experience MACE during hospitalization. Chi-square tests were used to compare categorical variables and Mann Whitney tests were used to compare continuous variables.

To create the perioperative risk-stratification model based on baseline, preoperative, and intraoperative data, we used a logistic regression with elastic net selection using a dichotomous dependent variable indicating MACE and independent variables described earlier. This perioperative model was fit on the training set and the model coefficients were then applied to the patients in the test set. The area under the receiver operating characteristic curve (AUC) was reported and the outcomes were reported by predicted risk decile, with higher deciles indicating higher risk (ie, higher numbers of patients with MACE outcomes in higher deciles implied better risk stratification). Because predicted risk of postoperative MACE may not have been distributed evenly across deciles, we also examined the distribution of the predicted probability of MACE and examined the number of patients below thresholds of risk corresponding to 0.1% or less, 0.25% or less, 0.5% or less, and 1% or less. These thresholds were chosen because they were close to the overall rate of MACE within our cohort.

We tested for differences in predictive performance between the RCRI logistic regression model AUC and the perioperative model AUC using DeLong’s test.²³ Additionally, we illustrated differences between the perioperative and RCRI models’ performance in two ways by stratifying patients into deciles based on predicted risk. First, we compared rates of MACE and MACE component events by predicted decile of the perioperative and RCRI models. Second, we further classified patients as RCRI high or low risk (per RCRI score classification in which RCRI score of 1 or greater is high risk and RCRI score of 0 is low risk) and examined numbers of surgical cases and MACE complications within these categories stratified by perioperative model predicted decile.

To compare the perioperative model’s performance with that of a risk factor–based guideline algorithm, we classified patients according to CCS guidelines as high risk (those for whom the CCS guidelines algorithm would recommend postoperative troponin surveillance testing) and low risk (those for whom the CCS guidelines algorithm would not recommend surveillance testing). We also used a logistic regression to examine if the predicted risk from our model was independently associated with MACE above and beyond the testing recommendation of the CCS guidelines algorithm. This model used MACE as the dependent variable and model-predicted risk and a CCS guidelines–defined high-risk indicator as predictors. We computed the association between a 10 percentage–point increase in predicted risk on observed MACE outcome rates.²⁴

In sensitivity analyses, we used a random forest machine learning classifier to test an alternate model specification, used complete case analysis, varied RCRI thresholds, and limited to patients aged 50 years or older. We also varied the penalty parameter in the elastic net model and plotted AUC versus the number of variables included to examine parsimonious models. SAS v9.4 (SAS Institute Inc) was used for main analyses. Data preparations and sensitivity analysis were done in Python v3.6 with Pandas v0.24.2 and Scikit-learn v0.19.1.

Study Sample

Patients who underwent major noncardiac surgery in our sample (n = 72,909) were approximately a mean age of 56 years, 58% female, 66% of White race and 26% of Black race, and most likely to have received orthopedic surgery (33%) or general surgery (20%). Those who experienced MACE (n = 558; 0.77%) differed along several characteristics (Table 1). For example, those with MACE were older (mean age, 65.4 vs 55.4 years; P < .001) and less likely to be female (41.9% vs 58.3%; P < .001).

Model Performance After Intraoperative Data Inclusion

In the perioperative model combining preoperative and intraoperative data, 26 variables were included after elastic net selection (Appendix Table 2). Model discrimination in the test set of patients demonstrated an AUC of 0.88 (95% CI, 0.85-0.92; Figure). When examining outcome rates by predicted decile, the outcome rates of in-hospital MACE complications were higher in the highest decile than in the lowest decile, notably with 58 of 92 (63%) cases with MACE complications within the top decile of predicted risk (Table 2). The majority of patients had low predicted risk of MACE, with 5,309 (36.1%), 8,796 (59.7%), 11,335 (77.0%), and 12,972 (88.1%) below the risk thresholds of to 0.1%, 0.25%, 0.5%, and 1.0% respectively. The associated MACE rates were 0.04%, 0.10%, 0.17%, and 0.25% (average rate in sample was 0.63%) (Appendix Table 3).

Model Performance Comparisons

The perioperative model AUC of 0.88 was higher when compared with RCRI’s AUC of 0.79 (95% CI, 0.74-0.84; P < .001). The number of MACE complications was more concentrated in the top decile of predicted risk of the perioperative model than it was in that of the RCRI model (58 vs 43 of 92 events, respectively; 63% vs 47%; Table 2). Furthermore, there were fewer cases with MACE complications in the low-risk deciles (ie, deciles 1 to 5) of the perioperative model than in the those of the RCRI model. These relative differences were consistent for MACE component outcomes of STEMI/NSTEMI, cardiac arrest, and in-hospital death, as well.

There was substantial heterogeneity in the perioperative model predicted risk of patients classified as either RCRI low risk or high risk (ie, each category included patients with low and high predicted risk) categories (Table 3). Patients in the bottom (low-risk) five deciles of the perioperative model’s predicted risk who were in the RCRI model’s high-risk group were very unlikely to experience MACE complications (3 out of 722 cases; 0.42%). Furthermore, among those classified as low risk by the RCRI model but were in the top decile of the perioperative model’s predicted risk, the MACE complication rate was 3.5% (8 out of 229), which was 6 times the sample mean MACE complication rate.

The perioperative model identified more patients as low risk than did the CCS guidelines’ risk factor–based algorithm (Table 3). For example, 2,341 of the patients the CCS guidelines algorithm identified as high risk were in the bottom 50% of the perioperative model’s predicted risk for experiencing MACE (below a 0.18% chance of a MACE complication); only four of these patients (0.17%) actually experienced MACE. This indicates that the 2,341 of 7,597 (31%) high-risk patients identified as low risk in the perioperative model would have been recommended for postoperative troponin testing by CCS guidelines based on preoperative risk factors alone—but did not go on to experience a MACE. Regression results indicated that both CCS guidelines risk-factor classification and the perioperative model’s predicted risk were predictive of MACE outcomes. A change in the perioperative model’s predicted risk of 10 percentage points was associated with an increase in the probability of a MACE outcomes of 0.45 percentage points (95% CI, 0.35-0.55 percentage points; P < .001) and moving from CCS guidelines’ low- to high-risk categories was associated with an increased probability of MACE by 0.96 percentage points (95% CI, 0.75-1.16 percentage points; P < .001).

Results were consistent with the main analysis across all sensitivity analyses (Appendix Tables 4-7). Parsimonious models with variables as few as eight variables retained strong predictive power (AUC, 0.870; Appendix Figure 1 and Table 8).

In this study, the addition of intraoperative data improved risk stratification for MACE complications when compared with standard risk tools such as RCRI. This approach also outperformed a guidelines-based approach and identified additional patients at low risk of cardiovascular complications. This study has three main implications.

First, this study demonstrated the additional value of combining intraoperative data with preoperative data in risk prediction for postoperative cardiovascular events. The intraoperative data most strongly associated with MACE, which likely were responsible for the performance improvement, included administration of medications (eg, sodium bicarbonate or calcium chloride) and blood products (eg, platelets and packed red blood cells), vitals (ie, heart rate), and intraoperative procedures (ie, arterial line placement); all model variables and coefficients are reported in Appendix Table 9. The risk-stratification model using intraoperative clinical data outperformed validated standard models such as RCRI. While this model should not be used in causal inference and cannot be used to inform decisions about risk-benefit tradeoffs of undergoing surgery, its improved performance relative to prior models highlights the potential in using real-time data. Preliminary illustrative analysis demonstrated that parsimonious models with as few as eight variables perform well, whose implementation as risk scores in EHRs is likely straightforward (Appendix Table 8). This is particularly important for longitudinal care in the hospital, in which patients frequently are cared for by multiple clinical services and experience handoffs. For example, many orthopedic surgery patients with significant medical comorbidity are managed postoperatively by hospitalist physicians after initial surgical care.

Second, our study aligns well with the cardiac risk-stratification literature more broadly. For example, the patient characteristics and clinical variables most associated with cardiovascular complications were age, history of ischemic heart disease, American Society of Anesthesiologists physical status, use of intraoperative sodium bicarbonate or vasopressors, lowest intraoperative heart rate measured, and lowest intraoperative mean arterial pressure measured. While many of these variables overlap with those included in the RCRI model, others (such as American Society of Anesthesiologists physical status) are not included in RCRI but have been shown to be important in risk prediction in other studies using different data variables.^6,25,26

Third, we illustrated a clinical application of this model in identifying patients at low risk of cardiovascular complications, although benefit may extend to other patients as well. This is particularly germane to clinicians who frequently manage patients in the postsurgical or postprocedural setting. Moreover, the clinical relevance to these clinicians is underscored by the lack of consensus among professional societies across Europe, Canada, and the United States about which subgroups of patients undergoing noncardiac surgery should receive postoperative cardiac biomarker surveillance testing in the 48 to 72 hours after surgery.^6-9 This may be in part caused by differences in clinical objectives. For example, the CCS guidelines in part aim to detect myocardial injury after noncardiac surgery (MINS) up to 30 days after surgery, which may be more sensitive to myocardial injury but less strongly associated with outcomes like MACE. The results of this study suggest that adopting such risk factor–based testing would likely lead to additional testing of low risk patients, which may represent low value surveillance tests. For example, there were 2,257 patients without postoperative cardiac biomarker testing in our data who would have been categorized as high risk by risk factor guidelines and therefore recommended to receive at least one postoperative cardiac biomarker surveillance test but were classified as low-risk individuals using a predicted probability of MACE less than 0.18% per our perioperative risk stratification model (Appendix Table 4). If each of these patients received one troponin biomarker test, the associated cost increase would be $372,405 (using the $165 cost per test reported at our institution). These costs would multiply if daily surveillance troponin biomarker tests were ordered for 48 to 72 hours after surgery, as recommended by the risk factor–based testing guidelines. This would be a departure from testing among patients using clinician discretion that may avoid low-value testing.

Applying the perioperative model developed in this paper to clinical practice still requires several steps. The technical aspects of finding a parsimonious model that can be implemented in the EHR is likely quite straightforward. Our preliminary analysis illustrates that doing so will not require accessing large numbers of intraoperative variables. Perhaps more important steps include prospective validation of the safety, usability, and clinical benefit of such an algorithm-based risk score.²⁷

The study has several limitations. First, it was an observational study using EHR data subject to missingness and data quality issues that may have persisted despite our methods. Furthermore, EHR data is not generated randomly, and unmeasured variables observed by clinicians but not by researchers could confound the results. However, our approach used the statistical model to examine risk, not causal inference. Second, this is a single institution study and the availability of EHR data, as well as practice patterns, may vary at other institutions. Furthermore, it is possible that performance of the RCRI score, the model fitting RCRI classification of high vs low risk on the sample data, and our model’s performance may not generalize to other clinical settings. However, we utilized data from multiple hospitals within a health system with different surgery and anesthesia groups and providers, and a similar AUC was reported for RCRI in original validation study.⁶ Third, our follow up period was limited to the hospital setting and we do not capture longitudinal outcomes, such as 30-day MACE. This may impact the ability to risk stratify for other important longer-term outcomes, limit clinical utility, and hinder comparability to other studies. Fourth, results may vary for other important cardiovascular outcomes that may be more sensitive to myocardial injury, such as MINS. Fifth, we used a limited number of modeling strategies.

Addition of intraoperative data to preoperative data improves prediction of cardiovascular complications after noncardiac surgery. Improving the identification of patients at low risk for such complications could potentially be applied to reduce unnecessary postoperative cardiac biomarker testing after noncardiac surgery, but it will require further validation in prospective clinical settings.

Dr Navathe reports grants from the following entities: Hawaii Medical Service Association, Anthem Public Policy Institute, Commonwealth Fund, Oscar Health, Cigna Corporation, Robert Wood Johnson Foundation, Donaghue Foundation, Pennsylvania Department of Health, Ochsner Health System, United Healthcare, Blue Cross Blue Shield of NC, Blue Shield of CA; personal fees from the following: Navvis Healthcare, Agathos, Inc, Navahealth, YNHHSC/CORE, Maine Health Accountable Care Organization, Maine Department of Health and Human Services, National University Health System - Singapore, Ministry of Health - Singapore, Social Security Administration - France, Elsevier Press, Medicare Payment Advisory Commission, Cleveland Clinic, Embedded Healthcare; and other support from Integrated Services, Inc, outside of the submitted work. Dr Volpp reports grants from Humana during the conduct of the study; grants from Hawaii Medical Services Agency, Discovery (South Africa), Merck, Weight Watchers, and CVS outside of the submitted work; he has received consulting income from CVS and VALHealth and is a principal in VALHealth, a behavioral economics consulting firm. Dr Holmes receives funding from the Pennsylvania Department of Health, US Public Health Service, and the Cardiovascular Medicine Research and Education Foundation. All other authors declare no conflicts of interest.

2019 Academy Health Annual Research Meeting, Poster Abstract Presentation, June 2 to June 4, 2019, Washington, DC.

This project was funded, in part, under a grant with the Pennsylvania Department of Health. This research was independent from the funder. The funder had no role in the study design; in the collection, analysis, and interpretation of data; in the writing of the report; or in the decision to submit the article for publication. The department specifically disclaims responsibility for any analyses, interpretations, or conclusions.

Annually, more than 40 million noncardiac surgeries take place in the US,¹ with 1%-3% of patients experiencing a major adverse cardiovascular event (MACE) such as acute myocardial infarction (AMI) or cardiac arrest postoperatively.² Such patients are at markedly increased risk of both perioperative and long-term death.^2-5

Over the past 40 years, efforts to model the risk of cardiac complications after noncardiac surgery have examined relationships between preoperative risk factors and postoperative cardiovascular events. The resulting risk-stratification tools, such as the Lee Revised Cardiac Risk Index (RCRI), have been used to inform perioperative care, including strategies for risk factor management prior to surgery, testing for cardiac events after surgery, and decisions regarding postoperative disposition.⁶ However, tools used in practice have not incorporated intraoperative data on hemodynamics or medication administration in the transition to postoperative care, which is often provided by nonsurgical clinicians such as hospitalists. Presently, there is active debate about the optimal approach to postoperative evaluation and management of MACE, particularly with regard to indications for cardiac biomarker testing after surgery in patients without signs or symptoms of acute cardiac syndromes. The lack of consensus is reflected in differences among guidelines for postoperative cardiac biomarker testing across professional societies in Europe, Canada, and the United States.^7-9

In this study, we examined whether the addition of intraoperative data to preoperative data (together, perioperative data) improved prediction of MACE after noncardiac surgery when compared with RCRI. Additionally, to investigate how such a model could be applied in practice, we compared risk stratification based on our model to a published risk factor–based guideline algorithm for postoperative cardiac biomarker testing.⁷ In particular, we evaluated to what extent patients recommended for postoperative cardiac biomarkers under the risk factor–based guideline algorithm would be reclassified as low risk by the model using perioperative data. Conducting biomarker tests on these patients would potentially represent low-value care. We hypothesized that adding intraoperative data would (a) lead to improved prediction of MACE complications when compared with RCRI and (b) more effectively identify, compared with a risk factor–based guideline algorithm, patients for whom cardiac biomarker testing would or would not be clinically meaningful.

We followed the Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis (TRIPOD) reporting guideline.¹⁰

Study Data

Baseline, preoperative, and intraoperative data were collected for patients undergoing surgery between January 2014 and April 2018 within the University of Pennsylvania Health System (UPHS) electronic health record (EHR), and these data were then integrated into a comprehensive perioperative dataset (data containing administrative, preoperative, intraoperative, and postoperative information related to surgeries) created through a collaboration with the Multicenter Perioperative Outcomes Group.¹¹ The University of Pennsylvania Institutional Review Board approved this study.

Study Population

Patients aged 18 years or older who underwent inpatient major noncardiac surgery across four tertiary academic medical centers within UPHS in Pennsylvania during the study period were included in the cohort (see Appendix for inclusion/exclusion criteria).^12,13 Noncardiac surgery was identified using primary Current Procedural Terminology (CPT) code specification ranges for noncardiac surgeries 10021-32999 and 34001-69990. The study sample was divided randomly into a training set (60%), validation (20%), and test set (20%),¹⁴ with similar rates of MACE in the resulting sets. We used a holdout test set for all final analyses to avoid overfitting during model selection.

Outcomes

The composite outcome used to develop the risk-stratification models was in-hospital MACE after major noncardiac surgery. Following prior literature, MACE was defined using billing codes for ST-elevation/non–ST-elevation myocardial infarction (STEMI/NSTEMI, ICD-9-CM 410.xx, ICD-10-CM I21.xx), cardiac arrest (ICD-9-CM 427.5, ICD-10-CM I46.x, I97.121), or all-cause in-hospital death.^2,15-17

Variables

Variables were selected from baseline administrative, preoperative clinical, and intraoperative clinical data sources (full list in Appendix). Baseline variables included demographics, insurance type, and Elixhauser comorbidities.^18,19 Preoperative variables included surgery type, laboratory results, and American Society of Anesthesiologists (ASA) Physical Status classification.²⁰ Intraoperative variables included vital signs, estimated blood loss, fluid administration, and vasopressor use. We winsorized outlier values and used multiple imputation to address missingness. Rates of missing data can be found in Appendix Table 1.

Risk-Stratification Models Used as Comparisons

Briefly, RCRI variables include the presence of high-risk surgery,²¹ comorbid cardiovascular diseases (ie, ischemic heart disease, congestive heart failure, and cerebrovascular disease), preoperative use of insulin, and elevated preoperative serum creatinine.⁶ RCRI uses the inputs to calculate a point score that equates to different risk strata and is based on a stepwise logistic regression model with postoperative cardiovascular complications as the dependent outcome variable. For this study, we implemented the weighted version of the RCRI algorithm and computed the point scores (Appendix).^6,7,22

We also applied a risk factor–based algorithm for postoperative cardiac biomarker testing published in 2017 by the Canadian Cardiovascular Society (CCS) guidelines to each patient in the study sample.⁷ Specifically, this algorithm recommends daily troponin surveillance for 48 to 72 hours after surgery among patients who have (1) an elevated NT-proBNP/BNP measurement or no NT-proBNP/BNP measurement before surgery, (2) have a Revised Cardiac Risk Index score of 1 or greater, (3) are aged 65 years and older, (4) are aged 45 to 64 years with significant cardiovascular disease undergoing elective surgery, or (5) are aged 18 to 64 years with significant cardiovascular disease undergoing semiurgent, urgent, or emergent surgery.

Statistical Analysis

We compared patient characteristics and outcomes between those who did and those who did not experience MACE during hospitalization. Chi-square tests were used to compare categorical variables and Mann Whitney tests were used to compare continuous variables.

To create the perioperative risk-stratification model based on baseline, preoperative, and intraoperative data, we used a logistic regression with elastic net selection using a dichotomous dependent variable indicating MACE and independent variables described earlier. This perioperative model was fit on the training set and the model coefficients were then applied to the patients in the test set. The area under the receiver operating characteristic curve (AUC) was reported and the outcomes were reported by predicted risk decile, with higher deciles indicating higher risk (ie, higher numbers of patients with MACE outcomes in higher deciles implied better risk stratification). Because predicted risk of postoperative MACE may not have been distributed evenly across deciles, we also examined the distribution of the predicted probability of MACE and examined the number of patients below thresholds of risk corresponding to 0.1% or less, 0.25% or less, 0.5% or less, and 1% or less. These thresholds were chosen because they were close to the overall rate of MACE within our cohort.

We tested for differences in predictive performance between the RCRI logistic regression model AUC and the perioperative model AUC using DeLong’s test.²³ Additionally, we illustrated differences between the perioperative and RCRI models’ performance in two ways by stratifying patients into deciles based on predicted risk. First, we compared rates of MACE and MACE component events by predicted decile of the perioperative and RCRI models. Second, we further classified patients as RCRI high or low risk (per RCRI score classification in which RCRI score of 1 or greater is high risk and RCRI score of 0 is low risk) and examined numbers of surgical cases and MACE complications within these categories stratified by perioperative model predicted decile.

To compare the perioperative model’s performance with that of a risk factor–based guideline algorithm, we classified patients according to CCS guidelines as high risk (those for whom the CCS guidelines algorithm would recommend postoperative troponin surveillance testing) and low risk (those for whom the CCS guidelines algorithm would not recommend surveillance testing). We also used a logistic regression to examine if the predicted risk from our model was independently associated with MACE above and beyond the testing recommendation of the CCS guidelines algorithm. This model used MACE as the dependent variable and model-predicted risk and a CCS guidelines–defined high-risk indicator as predictors. We computed the association between a 10 percentage–point increase in predicted risk on observed MACE outcome rates.²⁴

In sensitivity analyses, we used a random forest machine learning classifier to test an alternate model specification, used complete case analysis, varied RCRI thresholds, and limited to patients aged 50 years or older. We also varied the penalty parameter in the elastic net model and plotted AUC versus the number of variables included to examine parsimonious models. SAS v9.4 (SAS Institute Inc) was used for main analyses. Data preparations and sensitivity analysis were done in Python v3.6 with Pandas v0.24.2 and Scikit-learn v0.19.1.

Study Sample

Patients who underwent major noncardiac surgery in our sample (n = 72,909) were approximately a mean age of 56 years, 58% female, 66% of White race and 26% of Black race, and most likely to have received orthopedic surgery (33%) or general surgery (20%). Those who experienced MACE (n = 558; 0.77%) differed along several characteristics (Table 1). For example, those with MACE were older (mean age, 65.4 vs 55.4 years; P < .001) and less likely to be female (41.9% vs 58.3%; P < .001).

Model Performance After Intraoperative Data Inclusion

In the perioperative model combining preoperative and intraoperative data, 26 variables were included after elastic net selection (Appendix Table 2). Model discrimination in the test set of patients demonstrated an AUC of 0.88 (95% CI, 0.85-0.92; Figure). When examining outcome rates by predicted decile, the outcome rates of in-hospital MACE complications were higher in the highest decile than in the lowest decile, notably with 58 of 92 (63%) cases with MACE complications within the top decile of predicted risk (Table 2). The majority of patients had low predicted risk of MACE, with 5,309 (36.1%), 8,796 (59.7%), 11,335 (77.0%), and 12,972 (88.1%) below the risk thresholds of to 0.1%, 0.25%, 0.5%, and 1.0% respectively. The associated MACE rates were 0.04%, 0.10%, 0.17%, and 0.25% (average rate in sample was 0.63%) (Appendix Table 3).

Model Performance Comparisons

The perioperative model AUC of 0.88 was higher when compared with RCRI’s AUC of 0.79 (95% CI, 0.74-0.84; P < .001). The number of MACE complications was more concentrated in the top decile of predicted risk of the perioperative model than it was in that of the RCRI model (58 vs 43 of 92 events, respectively; 63% vs 47%; Table 2). Furthermore, there were fewer cases with MACE complications in the low-risk deciles (ie, deciles 1 to 5) of the perioperative model than in the those of the RCRI model. These relative differences were consistent for MACE component outcomes of STEMI/NSTEMI, cardiac arrest, and in-hospital death, as well.

There was substantial heterogeneity in the perioperative model predicted risk of patients classified as either RCRI low risk or high risk (ie, each category included patients with low and high predicted risk) categories (Table 3). Patients in the bottom (low-risk) five deciles of the perioperative model’s predicted risk who were in the RCRI model’s high-risk group were very unlikely to experience MACE complications (3 out of 722 cases; 0.42%). Furthermore, among those classified as low risk by the RCRI model but were in the top decile of the perioperative model’s predicted risk, the MACE complication rate was 3.5% (8 out of 229), which was 6 times the sample mean MACE complication rate.

The perioperative model identified more patients as low risk than did the CCS guidelines’ risk factor–based algorithm (Table 3). For example, 2,341 of the patients the CCS guidelines algorithm identified as high risk were in the bottom 50% of the perioperative model’s predicted risk for experiencing MACE (below a 0.18% chance of a MACE complication); only four of these patients (0.17%) actually experienced MACE. This indicates that the 2,341 of 7,597 (31%) high-risk patients identified as low risk in the perioperative model would have been recommended for postoperative troponin testing by CCS guidelines based on preoperative risk factors alone—but did not go on to experience a MACE. Regression results indicated that both CCS guidelines risk-factor classification and the perioperative model’s predicted risk were predictive of MACE outcomes. A change in the perioperative model’s predicted risk of 10 percentage points was associated with an increase in the probability of a MACE outcomes of 0.45 percentage points (95% CI, 0.35-0.55 percentage points; P < .001) and moving from CCS guidelines’ low- to high-risk categories was associated with an increased probability of MACE by 0.96 percentage points (95% CI, 0.75-1.16 percentage points; P < .001).

Results were consistent with the main analysis across all sensitivity analyses (Appendix Tables 4-7). Parsimonious models with variables as few as eight variables retained strong predictive power (AUC, 0.870; Appendix Figure 1 and Table 8).

In this study, the addition of intraoperative data improved risk stratification for MACE complications when compared with standard risk tools such as RCRI. This approach also outperformed a guidelines-based approach and identified additional patients at low risk of cardiovascular complications. This study has three main implications.

First, this study demonstrated the additional value of combining intraoperative data with preoperative data in risk prediction for postoperative cardiovascular events. The intraoperative data most strongly associated with MACE, which likely were responsible for the performance improvement, included administration of medications (eg, sodium bicarbonate or calcium chloride) and blood products (eg, platelets and packed red blood cells), vitals (ie, heart rate), and intraoperative procedures (ie, arterial line placement); all model variables and coefficients are reported in Appendix Table 9. The risk-stratification model using intraoperative clinical data outperformed validated standard models such as RCRI. While this model should not be used in causal inference and cannot be used to inform decisions about risk-benefit tradeoffs of undergoing surgery, its improved performance relative to prior models highlights the potential in using real-time data. Preliminary illustrative analysis demonstrated that parsimonious models with as few as eight variables perform well, whose implementation as risk scores in EHRs is likely straightforward (Appendix Table 8). This is particularly important for longitudinal care in the hospital, in which patients frequently are cared for by multiple clinical services and experience handoffs. For example, many orthopedic surgery patients with significant medical comorbidity are managed postoperatively by hospitalist physicians after initial surgical care.

Second, our study aligns well with the cardiac risk-stratification literature more broadly. For example, the patient characteristics and clinical variables most associated with cardiovascular complications were age, history of ischemic heart disease, American Society of Anesthesiologists physical status, use of intraoperative sodium bicarbonate or vasopressors, lowest intraoperative heart rate measured, and lowest intraoperative mean arterial pressure measured. While many of these variables overlap with those included in the RCRI model, others (such as American Society of Anesthesiologists physical status) are not included in RCRI but have been shown to be important in risk prediction in other studies using different data variables.^6,25,26

Third, we illustrated a clinical application of this model in identifying patients at low risk of cardiovascular complications, although benefit may extend to other patients as well. This is particularly germane to clinicians who frequently manage patients in the postsurgical or postprocedural setting. Moreover, the clinical relevance to these clinicians is underscored by the lack of consensus among professional societies across Europe, Canada, and the United States about which subgroups of patients undergoing noncardiac surgery should receive postoperative cardiac biomarker surveillance testing in the 48 to 72 hours after surgery.^6-9 This may be in part caused by differences in clinical objectives. For example, the CCS guidelines in part aim to detect myocardial injury after noncardiac surgery (MINS) up to 30 days after surgery, which may be more sensitive to myocardial injury but less strongly associated with outcomes like MACE. The results of this study suggest that adopting such risk factor–based testing would likely lead to additional testing of low risk patients, which may represent low value surveillance tests. For example, there were 2,257 patients without postoperative cardiac biomarker testing in our data who would have been categorized as high risk by risk factor guidelines and therefore recommended to receive at least one postoperative cardiac biomarker surveillance test but were classified as low-risk individuals using a predicted probability of MACE less than 0.18% per our perioperative risk stratification model (Appendix Table 4). If each of these patients received one troponin biomarker test, the associated cost increase would be $372,405 (using the $165 cost per test reported at our institution). These costs would multiply if daily surveillance troponin biomarker tests were ordered for 48 to 72 hours after surgery, as recommended by the risk factor–based testing guidelines. This would be a departure from testing among patients using clinician discretion that may avoid low-value testing.

Applying the perioperative model developed in this paper to clinical practice still requires several steps. The technical aspects of finding a parsimonious model that can be implemented in the EHR is likely quite straightforward. Our preliminary analysis illustrates that doing so will not require accessing large numbers of intraoperative variables. Perhaps more important steps include prospective validation of the safety, usability, and clinical benefit of such an algorithm-based risk score.²⁷

The study has several limitations. First, it was an observational study using EHR data subject to missingness and data quality issues that may have persisted despite our methods. Furthermore, EHR data is not generated randomly, and unmeasured variables observed by clinicians but not by researchers could confound the results. However, our approach used the statistical model to examine risk, not causal inference. Second, this is a single institution study and the availability of EHR data, as well as practice patterns, may vary at other institutions. Furthermore, it is possible that performance of the RCRI score, the model fitting RCRI classification of high vs low risk on the sample data, and our model’s performance may not generalize to other clinical settings. However, we utilized data from multiple hospitals within a health system with different surgery and anesthesia groups and providers, and a similar AUC was reported for RCRI in original validation study.⁶ Third, our follow up period was limited to the hospital setting and we do not capture longitudinal outcomes, such as 30-day MACE. This may impact the ability to risk stratify for other important longer-term outcomes, limit clinical utility, and hinder comparability to other studies. Fourth, results may vary for other important cardiovascular outcomes that may be more sensitive to myocardial injury, such as MINS. Fifth, we used a limited number of modeling strategies.

Addition of intraoperative data to preoperative data improves prediction of cardiovascular complications after noncardiac surgery. Improving the identification of patients at low risk for such complications could potentially be applied to reduce unnecessary postoperative cardiac biomarker testing after noncardiac surgery, but it will require further validation in prospective clinical settings.

Dr Navathe reports grants from the following entities: Hawaii Medical Service Association, Anthem Public Policy Institute, Commonwealth Fund, Oscar Health, Cigna Corporation, Robert Wood Johnson Foundation, Donaghue Foundation, Pennsylvania Department of Health, Ochsner Health System, United Healthcare, Blue Cross Blue Shield of NC, Blue Shield of CA; personal fees from the following: Navvis Healthcare, Agathos, Inc, Navahealth, YNHHSC/CORE, Maine Health Accountable Care Organization, Maine Department of Health and Human Services, National University Health System - Singapore, Ministry of Health - Singapore, Social Security Administration - France, Elsevier Press, Medicare Payment Advisory Commission, Cleveland Clinic, Embedded Healthcare; and other support from Integrated Services, Inc, outside of the submitted work. Dr Volpp reports grants from Humana during the conduct of the study; grants from Hawaii Medical Services Agency, Discovery (South Africa), Merck, Weight Watchers, and CVS outside of the submitted work; he has received consulting income from CVS and VALHealth and is a principal in VALHealth, a behavioral economics consulting firm. Dr Holmes receives funding from the Pennsylvania Department of Health, US Public Health Service, and the Cardiovascular Medicine Research and Education Foundation. All other authors declare no conflicts of interest.

2019 Academy Health Annual Research Meeting, Poster Abstract Presentation, June 2 to June 4, 2019, Washington, DC.

This project was funded, in part, under a grant with the Pennsylvania Department of Health. This research was independent from the funder. The funder had no role in the study design; in the collection, analysis, and interpretation of data; in the writing of the report; or in the decision to submit the article for publication. The department specifically disclaims responsibility for any analyses, interpretations, or conclusions.

Annually, more than 40 million noncardiac surgeries take place in the US,¹ with 1%-3% of patients experiencing a major adverse cardiovascular event (MACE) such as acute myocardial infarction (AMI) or cardiac arrest postoperatively.² Such patients are at markedly increased risk of both perioperative and long-term death.^2-5

Over the past 40 years, efforts to model the risk of cardiac complications after noncardiac surgery have examined relationships between preoperative risk factors and postoperative cardiovascular events. The resulting risk-stratification tools, such as the Lee Revised Cardiac Risk Index (RCRI), have been used to inform perioperative care, including strategies for risk factor management prior to surgery, testing for cardiac events after surgery, and decisions regarding postoperative disposition.⁶ However, tools used in practice have not incorporated intraoperative data on hemodynamics or medication administration in the transition to postoperative care, which is often provided by nonsurgical clinicians such as hospitalists. Presently, there is active debate about the optimal approach to postoperative evaluation and management of MACE, particularly with regard to indications for cardiac biomarker testing after surgery in patients without signs or symptoms of acute cardiac syndromes. The lack of consensus is reflected in differences among guidelines for postoperative cardiac biomarker testing across professional societies in Europe, Canada, and the United States.^7-9

In this study, we examined whether the addition of intraoperative data to preoperative data (together, perioperative data) improved prediction of MACE after noncardiac surgery when compared with RCRI. Additionally, to investigate how such a model could be applied in practice, we compared risk stratification based on our model to a published risk factor–based guideline algorithm for postoperative cardiac biomarker testing.⁷ In particular, we evaluated to what extent patients recommended for postoperative cardiac biomarkers under the risk factor–based guideline algorithm would be reclassified as low risk by the model using perioperative data. Conducting biomarker tests on these patients would potentially represent low-value care. We hypothesized that adding intraoperative data would (a) lead to improved prediction of MACE complications when compared with RCRI and (b) more effectively identify, compared with a risk factor–based guideline algorithm, patients for whom cardiac biomarker testing would or would not be clinically meaningful.

We followed the Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis (TRIPOD) reporting guideline.¹⁰

Study Data

Baseline, preoperative, and intraoperative data were collected for patients undergoing surgery between January 2014 and April 2018 within the University of Pennsylvania Health System (UPHS) electronic health record (EHR), and these data were then integrated into a comprehensive perioperative dataset (data containing administrative, preoperative, intraoperative, and postoperative information related to surgeries) created through a collaboration with the Multicenter Perioperative Outcomes Group.¹¹ The University of Pennsylvania Institutional Review Board approved this study.

Study Population

Patients aged 18 years or older who underwent inpatient major noncardiac surgery across four tertiary academic medical centers within UPHS in Pennsylvania during the study period were included in the cohort (see Appendix for inclusion/exclusion criteria).^12,13 Noncardiac surgery was identified using primary Current Procedural Terminology (CPT) code specification ranges for noncardiac surgeries 10021-32999 and 34001-69990. The study sample was divided randomly into a training set (60%), validation (20%), and test set (20%),¹⁴ with similar rates of MACE in the resulting sets. We used a holdout test set for all final analyses to avoid overfitting during model selection.

Outcomes

The composite outcome used to develop the risk-stratification models was in-hospital MACE after major noncardiac surgery. Following prior literature, MACE was defined using billing codes for ST-elevation/non–ST-elevation myocardial infarction (STEMI/NSTEMI, ICD-9-CM 410.xx, ICD-10-CM I21.xx), cardiac arrest (ICD-9-CM 427.5, ICD-10-CM I46.x, I97.121), or all-cause in-hospital death.^2,15-17

Variables

Variables were selected from baseline administrative, preoperative clinical, and intraoperative clinical data sources (full list in Appendix). Baseline variables included demographics, insurance type, and Elixhauser comorbidities.^18,19 Preoperative variables included surgery type, laboratory results, and American Society of Anesthesiologists (ASA) Physical Status classification.²⁰ Intraoperative variables included vital signs, estimated blood loss, fluid administration, and vasopressor use. We winsorized outlier values and used multiple imputation to address missingness. Rates of missing data can be found in Appendix Table 1.

Risk-Stratification Models Used as Comparisons

Briefly, RCRI variables include the presence of high-risk surgery,²¹ comorbid cardiovascular diseases (ie, ischemic heart disease, congestive heart failure, and cerebrovascular disease), preoperative use of insulin, and elevated preoperative serum creatinine.⁶ RCRI uses the inputs to calculate a point score that equates to different risk strata and is based on a stepwise logistic regression model with postoperative cardiovascular complications as the dependent outcome variable. For this study, we implemented the weighted version of the RCRI algorithm and computed the point scores (Appendix).^6,7,22

We also applied a risk factor–based algorithm for postoperative cardiac biomarker testing published in 2017 by the Canadian Cardiovascular Society (CCS) guidelines to each patient in the study sample.⁷ Specifically, this algorithm recommends daily troponin surveillance for 48 to 72 hours after surgery among patients who have (1) an elevated NT-proBNP/BNP measurement or no NT-proBNP/BNP measurement before surgery, (2) have a Revised Cardiac Risk Index score of 1 or greater, (3) are aged 65 years and older, (4) are aged 45 to 64 years with significant cardiovascular disease undergoing elective surgery, or (5) are aged 18 to 64 years with significant cardiovascular disease undergoing semiurgent, urgent, or emergent surgery.

Statistical Analysis

We compared patient characteristics and outcomes between those who did and those who did not experience MACE during hospitalization. Chi-square tests were used to compare categorical variables and Mann Whitney tests were used to compare continuous variables.

To create the perioperative risk-stratification model based on baseline, preoperative, and intraoperative data, we used a logistic regression with elastic net selection using a dichotomous dependent variable indicating MACE and independent variables described earlier. This perioperative model was fit on the training set and the model coefficients were then applied to the patients in the test set. The area under the receiver operating characteristic curve (AUC) was reported and the outcomes were reported by predicted risk decile, with higher deciles indicating higher risk (ie, higher numbers of patients with MACE outcomes in higher deciles implied better risk stratification). Because predicted risk of postoperative MACE may not have been distributed evenly across deciles, we also examined the distribution of the predicted probability of MACE and examined the number of patients below thresholds of risk corresponding to 0.1% or less, 0.25% or less, 0.5% or less, and 1% or less. These thresholds were chosen because they were close to the overall rate of MACE within our cohort.

We tested for differences in predictive performance between the RCRI logistic regression model AUC and the perioperative model AUC using DeLong’s test.²³ Additionally, we illustrated differences between the perioperative and RCRI models’ performance in two ways by stratifying patients into deciles based on predicted risk. First, we compared rates of MACE and MACE component events by predicted decile of the perioperative and RCRI models. Second, we further classified patients as RCRI high or low risk (per RCRI score classification in which RCRI score of 1 or greater is high risk and RCRI score of 0 is low risk) and examined numbers of surgical cases and MACE complications within these categories stratified by perioperative model predicted decile.

To compare the perioperative model’s performance with that of a risk factor–based guideline algorithm, we classified patients according to CCS guidelines as high risk (those for whom the CCS guidelines algorithm would recommend postoperative troponin surveillance testing) and low risk (those for whom the CCS guidelines algorithm would not recommend surveillance testing). We also used a logistic regression to examine if the predicted risk from our model was independently associated with MACE above and beyond the testing recommendation of the CCS guidelines algorithm. This model used MACE as the dependent variable and model-predicted risk and a CCS guidelines–defined high-risk indicator as predictors. We computed the association between a 10 percentage–point increase in predicted risk on observed MACE outcome rates.²⁴

In sensitivity analyses, we used a random forest machine learning classifier to test an alternate model specification, used complete case analysis, varied RCRI thresholds, and limited to patients aged 50 years or older. We also varied the penalty parameter in the elastic net model and plotted AUC versus the number of variables included to examine parsimonious models. SAS v9.4 (SAS Institute Inc) was used for main analyses. Data preparations and sensitivity analysis were done in Python v3.6 with Pandas v0.24.2 and Scikit-learn v0.19.1.

Study Sample

Patients who underwent major noncardiac surgery in our sample (n = 72,909) were approximately a mean age of 56 years, 58% female, 66% of White race and 26% of Black race, and most likely to have received orthopedic surgery (33%) or general surgery (20%). Those who experienced MACE (n = 558; 0.77%) differed along several characteristics (Table 1). For example, those with MACE were older (mean age, 65.4 vs 55.4 years; P < .001) and less likely to be female (41.9% vs 58.3%; P < .001).

Model Performance After Intraoperative Data Inclusion

In the perioperative model combining preoperative and intraoperative data, 26 variables were included after elastic net selection (Appendix Table 2). Model discrimination in the test set of patients demonstrated an AUC of 0.88 (95% CI, 0.85-0.92; Figure). When examining outcome rates by predicted decile, the outcome rates of in-hospital MACE complications were higher in the highest decile than in the lowest decile, notably with 58 of 92 (63%) cases with MACE complications within the top decile of predicted risk (Table 2). The majority of patients had low predicted risk of MACE, with 5,309 (36.1%), 8,796 (59.7%), 11,335 (77.0%), and 12,972 (88.1%) below the risk thresholds of to 0.1%, 0.25%, 0.5%, and 1.0% respectively. The associated MACE rates were 0.04%, 0.10%, 0.17%, and 0.25% (average rate in sample was 0.63%) (Appendix Table 3).

Model Performance Comparisons

The perioperative model AUC of 0.88 was higher when compared with RCRI’s AUC of 0.79 (95% CI, 0.74-0.84; P < .001). The number of MACE complications was more concentrated in the top decile of predicted risk of the perioperative model than it was in that of the RCRI model (58 vs 43 of 92 events, respectively; 63% vs 47%; Table 2). Furthermore, there were fewer cases with MACE complications in the low-risk deciles (ie, deciles 1 to 5) of the perioperative model than in the those of the RCRI model. These relative differences were consistent for MACE component outcomes of STEMI/NSTEMI, cardiac arrest, and in-hospital death, as well.

There was substantial heterogeneity in the perioperative model predicted risk of patients classified as either RCRI low risk or high risk (ie, each category included patients with low and high predicted risk) categories (Table 3). Patients in the bottom (low-risk) five deciles of the perioperative model’s predicted risk who were in the RCRI model’s high-risk group were very unlikely to experience MACE complications (3 out of 722 cases; 0.42%). Furthermore, among those classified as low risk by the RCRI model but were in the top decile of the perioperative model’s predicted risk, the MACE complication rate was 3.5% (8 out of 229), which was 6 times the sample mean MACE complication rate.

The perioperative model identified more patients as low risk than did the CCS guidelines’ risk factor–based algorithm (Table 3). For example, 2,341 of the patients the CCS guidelines algorithm identified as high risk were in the bottom 50% of the perioperative model’s predicted risk for experiencing MACE (below a 0.18% chance of a MACE complication); only four of these patients (0.17%) actually experienced MACE. This indicates that the 2,341 of 7,597 (31%) high-risk patients identified as low risk in the perioperative model would have been recommended for postoperative troponin testing by CCS guidelines based on preoperative risk factors alone—but did not go on to experience a MACE. Regression results indicated that both CCS guidelines risk-factor classification and the perioperative model’s predicted risk were predictive of MACE outcomes. A change in the perioperative model’s predicted risk of 10 percentage points was associated with an increase in the probability of a MACE outcomes of 0.45 percentage points (95% CI, 0.35-0.55 percentage points; P < .001) and moving from CCS guidelines’ low- to high-risk categories was associated with an increased probability of MACE by 0.96 percentage points (95% CI, 0.75-1.16 percentage points; P < .001).

Results were consistent with the main analysis across all sensitivity analyses (Appendix Tables 4-7). Parsimonious models with variables as few as eight variables retained strong predictive power (AUC, 0.870; Appendix Figure 1 and Table 8).

In this study, the addition of intraoperative data improved risk stratification for MACE complications when compared with standard risk tools such as RCRI. This approach also outperformed a guidelines-based approach and identified additional patients at low risk of cardiovascular complications. This study has three main implications.

First, this study demonstrated the additional value of combining intraoperative data with preoperative data in risk prediction for postoperative cardiovascular events. The intraoperative data most strongly associated with MACE, which likely were responsible for the performance improvement, included administration of medications (eg, sodium bicarbonate or calcium chloride) and blood products (eg, platelets and packed red blood cells), vitals (ie, heart rate), and intraoperative procedures (ie, arterial line placement); all model variables and coefficients are reported in Appendix Table 9. The risk-stratification model using intraoperative clinical data outperformed validated standard models such as RCRI. While this model should not be used in causal inference and cannot be used to inform decisions about risk-benefit tradeoffs of undergoing surgery, its improved performance relative to prior models highlights the potential in using real-time data. Preliminary illustrative analysis demonstrated that parsimonious models with as few as eight variables perform well, whose implementation as risk scores in EHRs is likely straightforward (Appendix Table 8). This is particularly important for longitudinal care in the hospital, in which patients frequently are cared for by multiple clinical services and experience handoffs. For example, many orthopedic surgery patients with significant medical comorbidity are managed postoperatively by hospitalist physicians after initial surgical care.

Second, our study aligns well with the cardiac risk-stratification literature more broadly. For example, the patient characteristics and clinical variables most associated with cardiovascular complications were age, history of ischemic heart disease, American Society of Anesthesiologists physical status, use of intraoperative sodium bicarbonate or vasopressors, lowest intraoperative heart rate measured, and lowest intraoperative mean arterial pressure measured. While many of these variables overlap with those included in the RCRI model, others (such as American Society of Anesthesiologists physical status) are not included in RCRI but have been shown to be important in risk prediction in other studies using different data variables.^6,25,26

Third, we illustrated a clinical application of this model in identifying patients at low risk of cardiovascular complications, although benefit may extend to other patients as well. This is particularly germane to clinicians who frequently manage patients in the postsurgical or postprocedural setting. Moreover, the clinical relevance to these clinicians is underscored by the lack of consensus among professional societies across Europe, Canada, and the United States about which subgroups of patients undergoing noncardiac surgery should receive postoperative cardiac biomarker surveillance testing in the 48 to 72 hours after surgery.^6-9 This may be in part caused by differences in clinical objectives. For example, the CCS guidelines in part aim to detect myocardial injury after noncardiac surgery (MINS) up to 30 days after surgery, which may be more sensitive to myocardial injury but less strongly associated with outcomes like MACE. The results of this study suggest that adopting such risk factor–based testing would likely lead to additional testing of low risk patients, which may represent low value surveillance tests. For example, there were 2,257 patients without postoperative cardiac biomarker testing in our data who would have been categorized as high risk by risk factor guidelines and therefore recommended to receive at least one postoperative cardiac biomarker surveillance test but were classified as low-risk individuals using a predicted probability of MACE less than 0.18% per our perioperative risk stratification model (Appendix Table 4). If each of these patients received one troponin biomarker test, the associated cost increase would be $372,405 (using the $165 cost per test reported at our institution). These costs would multiply if daily surveillance troponin biomarker tests were ordered for 48 to 72 hours after surgery, as recommended by the risk factor–based testing guidelines. This would be a departure from testing among patients using clinician discretion that may avoid low-value testing.

Applying the perioperative model developed in this paper to clinical practice still requires several steps. The technical aspects of finding a parsimonious model that can be implemented in the EHR is likely quite straightforward. Our preliminary analysis illustrates that doing so will not require accessing large numbers of intraoperative variables. Perhaps more important steps include prospective validation of the safety, usability, and clinical benefit of such an algorithm-based risk score.²⁷

The study has several limitations. First, it was an observational study using EHR data subject to missingness and data quality issues that may have persisted despite our methods. Furthermore, EHR data is not generated randomly, and unmeasured variables observed by clinicians but not by researchers could confound the results. However, our approach used the statistical model to examine risk, not causal inference. Second, this is a single institution study and the availability of EHR data, as well as practice patterns, may vary at other institutions. Furthermore, it is possible that performance of the RCRI score, the model fitting RCRI classification of high vs low risk on the sample data, and our model’s performance may not generalize to other clinical settings. However, we utilized data from multiple hospitals within a health system with different surgery and anesthesia groups and providers, and a similar AUC was reported for RCRI in original validation study.⁶ Third, our follow up period was limited to the hospital setting and we do not capture longitudinal outcomes, such as 30-day MACE. This may impact the ability to risk stratify for other important longer-term outcomes, limit clinical utility, and hinder comparability to other studies. Fourth, results may vary for other important cardiovascular outcomes that may be more sensitive to myocardial injury, such as MINS. Fifth, we used a limited number of modeling strategies.

Addition of intraoperative data to preoperative data improves prediction of cardiovascular complications after noncardiac surgery. Improving the identification of patients at low risk for such complications could potentially be applied to reduce unnecessary postoperative cardiac biomarker testing after noncardiac surgery, but it will require further validation in prospective clinical settings.

Dr Navathe reports grants from the following entities: Hawaii Medical Service Association, Anthem Public Policy Institute, Commonwealth Fund, Oscar Health, Cigna Corporation, Robert Wood Johnson Foundation, Donaghue Foundation, Pennsylvania Department of Health, Ochsner Health System, United Healthcare, Blue Cross Blue Shield of NC, Blue Shield of CA; personal fees from the following: Navvis Healthcare, Agathos, Inc, Navahealth, YNHHSC/CORE, Maine Health Accountable Care Organization, Maine Department of Health and Human Services, National University Health System - Singapore, Ministry of Health - Singapore, Social Security Administration - France, Elsevier Press, Medicare Payment Advisory Commission, Cleveland Clinic, Embedded Healthcare; and other support from Integrated Services, Inc, outside of the submitted work. Dr Volpp reports grants from Humana during the conduct of the study; grants from Hawaii Medical Services Agency, Discovery (South Africa), Merck, Weight Watchers, and CVS outside of the submitted work; he has received consulting income from CVS and VALHealth and is a principal in VALHealth, a behavioral economics consulting firm. Dr Holmes receives funding from the Pennsylvania Department of Health, US Public Health Service, and the Cardiovascular Medicine Research and Education Foundation. All other authors declare no conflicts of interest.

2019 Academy Health Annual Research Meeting, Poster Abstract Presentation, June 2 to June 4, 2019, Washington, DC.

This project was funded, in part, under a grant with the Pennsylvania Department of Health. This research was independent from the funder. The funder had no role in the study design; in the collection, analysis, and interpretation of data; in the writing of the report; or in the decision to submit the article for publication. The department specifically disclaims responsibility for any analyses, interpretations, or conclusions.

In recent years, mounting evidence has emerged questioning the practice of using prolonged intravenous antibiotic therapy to treat certain serious bacterial infections in children, including complicated appendicitis, osteomyelitis, and complicated pneumonia. Historically, treatment of these conditions was often completed intravenously after hospital discharge using peripherally inserted central catheters (PICCs). Line infections, clots, mechanical problems, and general discomfort complicate PICCs, which led to their removal in more than 20% of children in one study.¹ Oral antibiotics avoid these complications and are less burdensome to families.² Recently, a series of multicenter studies showed no difference in outcomes between oral and postdischarge intravenous antibiotic therapy (PD-IV) for complicated appendicitis, osteomyelitis, and complicated pneumonia.^3-5

Despite a growing body of evidence suggesting that oral therapy ought to be the default treatment strategy rather than PD-IV, the extent to which practices have changed is unknown. In this study, we measured national trends in PD-IV use and variation by hospital for complicated appendicitis, osteomyelitis, and complicated pneumonia.

We performed a retrospective cohort study of children discharged from hospitals that contributed data to the Pediatric Health Information System (PHIS) database from January 2000 through December 2018. PHIS is an administrative database of children’s hospitals managed by the Children’s Hospital Association (Lenexa, Kansas) and contains deidentified patient-­level demographic data, discharge diagnosis and procedure codes, and detailed billing information, including medical supply charges.

The cohorts were defined using International Classification of Diseases, 9th and 10th Revisions (ICD-9 and ICD-10) discharge diagnosis and procedure codes. Patients admitted through September 2015 were identified using ICD-9 codes and patients admitted from October 2015 through December 2018 were identified using ICD-10 codes. The Centers for Medicaid & Medicare Services crosswalk was used to align ICD-9 and ICD-10 codes.⁶ Inclusion and exclusion criteria identifying cohorts of children hospitalized for complicated appendicitis, osteomyelitis, or complicated pneumonia were based on prior studies using the PHIS database.^3-5 These studies augmented the PHIS administrative dataset with local chart review to identify patients from 2009-2012 with the following inclusion and exclusion criteria: Patients with complicated appendicitis were defined by a diagnosis code for acute appendicitis and a procedure code for appendectomy, with postoperative length of stay lasting between 3 and 7 days. Patients with osteomyelitis had a diagnosis code of acute or unspecified osteomyelitis with a hospital length of stay between 2 and 14 days. Patients with complicated pneumonia were defined by a diagnosis code for both pneumonia and pleural effusion with one of these as the primary diagnosis. Patients were excluded if they were older than 18 years or if they were younger than 2 months for osteomyelitis and complicated pneumonia or younger than 3 years for appendicitis. For all three conditions, children with a complex chronic condition⁷ were excluded. Only the index encounter meeting inclusion and exclusion criteria for each patient was included. PD-IV therapy was defined using procedure codes and hospital charges during the index hospitalization. This definition for PD-IV therapy has been validated among children with complicated pneumonia, demonstrating positive and negative predictive values for PICC exposure of 85% and 99%, respectively.⁸

Trends in the percentage of patients receiving PD-IV were adjusted for age, race, insurance type, intensive care unit days, and hospital-level case mix index with use of Poisson regression. Calculated risk ratios represent the change in PD-IV across the entire 19-year study period for each condition (as opposed to an annual rate of change). An inflection point for each condition was identified using piecewise linear regression in which the line slope has one value up to a point in time and a second value after that point. The transition point is determined by maximizing model fit.

Some hospitals were added to the database throughout the time period and therefore did not have data for all years of the study. To account for the possibility of a group of high– or low–PD-IV use hospitals entering the cohort and biasing the overall trend, we performed a sensitivity analysis restricted to hospitals continuously contributing data to PHIS every year between 2004 (when a majority of hospitals joined PHIS) and 2018. Significance testing for individual hospital trends was conducted among continuously contributing hospitals, with each hospital tested in the above Poisson model independently.

For the most recent year of 2018, we reported the distribution of adjusted percentages of PD-IV at the individual hospital level. Only hospitals with at least five patients for a given condition are included in the percent PD-IV calculations for 2018. To examine the extent to which an individual hospital might be a low– or high–PD-IV user across conditions, we divided hospitals into quartiles based on PD-IV use for each condition in 2017-2018 and calculated the percent of hospitals in the lowest- and highest-use quartiles for all three conditions. All statistics were performed using Stata 15 (StataCorp).

Among 52 hospitals over a 19-year study period, there were 60,575 hospitalizations for complicated appendicitis, 24,753 hospitalizations for osteomyelitis, and 13,700 hospitalizations for complicated pneumonia. From 2000 to 2018, PD-IV decreased from 13% to 2% (RR, 0.15; 95% CI, 0.14-0.16) for complicated appendicitis, from 61% to 22% (RR, 0.41; 95% CI, 0.39-0.43) for osteomyelitis, and from 29% to 19% (RR, 0.63; 95% CI, 0.58-0.69) for complicated pneumonia (Figure 1). The inflection points occurred in 2009 for complicated appendicitis, 2009 for complicated pneumonia, and 2010 for osteomyelitis. The sensitivity analysis included 31 hospitals that contributed data to PHIS for every year between 2004-2018 and revealed similar findings for all three conditions: Complicated appendicitis had an RR of 0.15 (95% CI, 0.14-0.17), osteomyelitis had an RR of 0.34 (95% CI, 0.32-0.36), and complicated pneumonia had an RR of 0.55 (95% CI, 0.49-0.61). Most individual hospitals decreased PD-IV use (complicated appendicitis: 21 decreased, 8 no change, 2 increased; osteomyelitis: 25 decreased, 6 no change; complicated pneumonia: 14 decreased, 16 no change, 1 increased). While overall decreases in PD-IV were observed for all three conditions, considerable variation remained in 2018 for use of PD-IV (Figure 2), particularly for osteomyelitis (median, 18%; interquartile range [IQR] 9%-40%) and complicated pneumonia (median, 13%; IQR, 3%-30%). In 2017-2018, 1 out of 52 hospitals was in the lowest PD-IV–use quartile for all three conditions, and three hospitals were in the highest-use quartile for all three conditions.

Over a 19-year period, we observed a national decline in use of PD-IV for three serious and common bacterial infections. The decline in PD-IV is notable given that it has occurred largely in the absence of nationally coordinated guidelines or improvement efforts. Despite the overall declines, substantial variation in the use of PD-IV for these conditions persists across children’s hospitals.

The observed decrease in PD-IV use is a natural example of deimplementation, the abandonment of medical practices found to be harmful or ineffective.⁹ What is most compelling about the deimplementation of PD-IV for these infectious conditions is the seemingly organic motivation that propelled it. Studies of physician practice patterns for interventions that have undergone evidence reversals demonstrate that physicians might readily implement new interventions with an early evidence base but be less willing to deimplement them when more definitive evidence later questions their efficacy.¹⁰ Therefore, concerted improvement efforts backed by national guidelines are often needed to reduce the use of a widely accepted medical practice. For example, as evidence questioning the efficacy of steroid use in bronchiolitis mounted,¹¹ bronchiolitis guidelines recommended against steroid use¹² and a national quality improvement effort led to reductions in exposure to steroids among patients hospitalized with bronchiolitis.¹³ Complicated intra-abdominal infection guidelines acknowledge oral antibiotic therapy as an option,¹⁴ but no such national guidelines or improvement projects exist for osteomyelitis or complicated pneumonia PD-IV.

What is it about PD-IV for complicated appendicitis, osteomyelitis, and complicated pneumonia that fostered the observed organic deimplementation? Our findings that few hospitals were in the top or bottom quartile of PD-IV across all three conditions suggest that the impetus to decrease PD-IV was not likely the product of a broad hospital-wide practice shift. Most deimplementation frameworks suggest that successful deimplementation must be supported by high-quality evidence that the intervention is not only ineffective, but also harmful.¹⁵ In this case, the inflection point for osteomyelitis occurred in 2009, the same year that the first large multicenter study suggesting efficacy and decreased complications of early oral therapy for osteomyelitis was published.¹⁶ A direct link between a publication and inflection points for complicated pneumonia and appendicitis is less clear. It is possible that growth of the field of pediatric hospital medicine,¹⁷ with a stated emphasis on healthcare value,¹⁸ played a role. Greater understanding of the drivers and barriers to deimplementation in this and similar contexts will be important.

Our study has some important limitations. While inclusion and exclusion criteria were consistent over the study period, practice patterns (ie, length of stay in uncomplicated patients) change and could alter the case-mix of patients over time. Additionally, the PHIS database largely comprises children’s hospitals, and the trends we observed in PD-IV may not generalize to community settings.

The degree of deimplementation of PD-IV observed across children’s hospitals is impressive, but opportunity for further improvement likely remains. We found that marked hospital-­level variation in use of PD-IV still exists, with some hospitals almost never using PD-IV and others using it for most patients. While the ideal amount of PD-IV is probably not zero, a portion of the observed variation likely represents overuse of PD-IV. To reduce costs and complications associated with antibiotic therapy, national guidelines and a targeted national improvement collaborative may be necessary to achieve further reductions in PD-IV.

In recent years, mounting evidence has emerged questioning the practice of using prolonged intravenous antibiotic therapy to treat certain serious bacterial infections in children, including complicated appendicitis, osteomyelitis, and complicated pneumonia. Historically, treatment of these conditions was often completed intravenously after hospital discharge using peripherally inserted central catheters (PICCs). Line infections, clots, mechanical problems, and general discomfort complicate PICCs, which led to their removal in more than 20% of children in one study.¹ Oral antibiotics avoid these complications and are less burdensome to families.² Recently, a series of multicenter studies showed no difference in outcomes between oral and postdischarge intravenous antibiotic therapy (PD-IV) for complicated appendicitis, osteomyelitis, and complicated pneumonia.^3-5

Despite a growing body of evidence suggesting that oral therapy ought to be the default treatment strategy rather than PD-IV, the extent to which practices have changed is unknown. In this study, we measured national trends in PD-IV use and variation by hospital for complicated appendicitis, osteomyelitis, and complicated pneumonia.

We performed a retrospective cohort study of children discharged from hospitals that contributed data to the Pediatric Health Information System (PHIS) database from January 2000 through December 2018. PHIS is an administrative database of children’s hospitals managed by the Children’s Hospital Association (Lenexa, Kansas) and contains deidentified patient-­level demographic data, discharge diagnosis and procedure codes, and detailed billing information, including medical supply charges.

The cohorts were defined using International Classification of Diseases, 9th and 10th Revisions (ICD-9 and ICD-10) discharge diagnosis and procedure codes. Patients admitted through September 2015 were identified using ICD-9 codes and patients admitted from October 2015 through December 2018 were identified using ICD-10 codes. The Centers for Medicaid & Medicare Services crosswalk was used to align ICD-9 and ICD-10 codes.⁶ Inclusion and exclusion criteria identifying cohorts of children hospitalized for complicated appendicitis, osteomyelitis, or complicated pneumonia were based on prior studies using the PHIS database.^3-5 These studies augmented the PHIS administrative dataset with local chart review to identify patients from 2009-2012 with the following inclusion and exclusion criteria: Patients with complicated appendicitis were defined by a diagnosis code for acute appendicitis and a procedure code for appendectomy, with postoperative length of stay lasting between 3 and 7 days. Patients with osteomyelitis had a diagnosis code of acute or unspecified osteomyelitis with a hospital length of stay between 2 and 14 days. Patients with complicated pneumonia were defined by a diagnosis code for both pneumonia and pleural effusion with one of these as the primary diagnosis. Patients were excluded if they were older than 18 years or if they were younger than 2 months for osteomyelitis and complicated pneumonia or younger than 3 years for appendicitis. For all three conditions, children with a complex chronic condition⁷ were excluded. Only the index encounter meeting inclusion and exclusion criteria for each patient was included. PD-IV therapy was defined using procedure codes and hospital charges during the index hospitalization. This definition for PD-IV therapy has been validated among children with complicated pneumonia, demonstrating positive and negative predictive values for PICC exposure of 85% and 99%, respectively.⁸

Trends in the percentage of patients receiving PD-IV were adjusted for age, race, insurance type, intensive care unit days, and hospital-level case mix index with use of Poisson regression. Calculated risk ratios represent the change in PD-IV across the entire 19-year study period for each condition (as opposed to an annual rate of change). An inflection point for each condition was identified using piecewise linear regression in which the line slope has one value up to a point in time and a second value after that point. The transition point is determined by maximizing model fit.

Some hospitals were added to the database throughout the time period and therefore did not have data for all years of the study. To account for the possibility of a group of high– or low–PD-IV use hospitals entering the cohort and biasing the overall trend, we performed a sensitivity analysis restricted to hospitals continuously contributing data to PHIS every year between 2004 (when a majority of hospitals joined PHIS) and 2018. Significance testing for individual hospital trends was conducted among continuously contributing hospitals, with each hospital tested in the above Poisson model independently.

For the most recent year of 2018, we reported the distribution of adjusted percentages of PD-IV at the individual hospital level. Only hospitals with at least five patients for a given condition are included in the percent PD-IV calculations for 2018. To examine the extent to which an individual hospital might be a low– or high–PD-IV user across conditions, we divided hospitals into quartiles based on PD-IV use for each condition in 2017-2018 and calculated the percent of hospitals in the lowest- and highest-use quartiles for all three conditions. All statistics were performed using Stata 15 (StataCorp).

Among 52 hospitals over a 19-year study period, there were 60,575 hospitalizations for complicated appendicitis, 24,753 hospitalizations for osteomyelitis, and 13,700 hospitalizations for complicated pneumonia. From 2000 to 2018, PD-IV decreased from 13% to 2% (RR, 0.15; 95% CI, 0.14-0.16) for complicated appendicitis, from 61% to 22% (RR, 0.41; 95% CI, 0.39-0.43) for osteomyelitis, and from 29% to 19% (RR, 0.63; 95% CI, 0.58-0.69) for complicated pneumonia (Figure 1). The inflection points occurred in 2009 for complicated appendicitis, 2009 for complicated pneumonia, and 2010 for osteomyelitis. The sensitivity analysis included 31 hospitals that contributed data to PHIS for every year between 2004-2018 and revealed similar findings for all three conditions: Complicated appendicitis had an RR of 0.15 (95% CI, 0.14-0.17), osteomyelitis had an RR of 0.34 (95% CI, 0.32-0.36), and complicated pneumonia had an RR of 0.55 (95% CI, 0.49-0.61). Most individual hospitals decreased PD-IV use (complicated appendicitis: 21 decreased, 8 no change, 2 increased; osteomyelitis: 25 decreased, 6 no change; complicated pneumonia: 14 decreased, 16 no change, 1 increased). While overall decreases in PD-IV were observed for all three conditions, considerable variation remained in 2018 for use of PD-IV (Figure 2), particularly for osteomyelitis (median, 18%; interquartile range [IQR] 9%-40%) and complicated pneumonia (median, 13%; IQR, 3%-30%). In 2017-2018, 1 out of 52 hospitals was in the lowest PD-IV–use quartile for all three conditions, and three hospitals were in the highest-use quartile for all three conditions.

Over a 19-year period, we observed a national decline in use of PD-IV for three serious and common bacterial infections. The decline in PD-IV is notable given that it has occurred largely in the absence of nationally coordinated guidelines or improvement efforts. Despite the overall declines, substantial variation in the use of PD-IV for these conditions persists across children’s hospitals.

The observed decrease in PD-IV use is a natural example of deimplementation, the abandonment of medical practices found to be harmful or ineffective.⁹ What is most compelling about the deimplementation of PD-IV for these infectious conditions is the seemingly organic motivation that propelled it. Studies of physician practice patterns for interventions that have undergone evidence reversals demonstrate that physicians might readily implement new interventions with an early evidence base but be less willing to deimplement them when more definitive evidence later questions their efficacy.¹⁰ Therefore, concerted improvement efforts backed by national guidelines are often needed to reduce the use of a widely accepted medical practice. For example, as evidence questioning the efficacy of steroid use in bronchiolitis mounted,¹¹ bronchiolitis guidelines recommended against steroid use¹² and a national quality improvement effort led to reductions in exposure to steroids among patients hospitalized with bronchiolitis.¹³ Complicated intra-abdominal infection guidelines acknowledge oral antibiotic therapy as an option,¹⁴ but no such national guidelines or improvement projects exist for osteomyelitis or complicated pneumonia PD-IV.

What is it about PD-IV for complicated appendicitis, osteomyelitis, and complicated pneumonia that fostered the observed organic deimplementation? Our findings that few hospitals were in the top or bottom quartile of PD-IV across all three conditions suggest that the impetus to decrease PD-IV was not likely the product of a broad hospital-wide practice shift. Most deimplementation frameworks suggest that successful deimplementation must be supported by high-quality evidence that the intervention is not only ineffective, but also harmful.¹⁵ In this case, the inflection point for osteomyelitis occurred in 2009, the same year that the first large multicenter study suggesting efficacy and decreased complications of early oral therapy for osteomyelitis was published.¹⁶ A direct link between a publication and inflection points for complicated pneumonia and appendicitis is less clear. It is possible that growth of the field of pediatric hospital medicine,¹⁷ with a stated emphasis on healthcare value,¹⁸ played a role. Greater understanding of the drivers and barriers to deimplementation in this and similar contexts will be important.

Our study has some important limitations. While inclusion and exclusion criteria were consistent over the study period, practice patterns (ie, length of stay in uncomplicated patients) change and could alter the case-mix of patients over time. Additionally, the PHIS database largely comprises children’s hospitals, and the trends we observed in PD-IV may not generalize to community settings.

The degree of deimplementation of PD-IV observed across children’s hospitals is impressive, but opportunity for further improvement likely remains. We found that marked hospital-­level variation in use of PD-IV still exists, with some hospitals almost never using PD-IV and others using it for most patients. While the ideal amount of PD-IV is probably not zero, a portion of the observed variation likely represents overuse of PD-IV. To reduce costs and complications associated with antibiotic therapy, national guidelines and a targeted national improvement collaborative may be necessary to achieve further reductions in PD-IV.

In recent years, mounting evidence has emerged questioning the practice of using prolonged intravenous antibiotic therapy to treat certain serious bacterial infections in children, including complicated appendicitis, osteomyelitis, and complicated pneumonia. Historically, treatment of these conditions was often completed intravenously after hospital discharge using peripherally inserted central catheters (PICCs). Line infections, clots, mechanical problems, and general discomfort complicate PICCs, which led to their removal in more than 20% of children in one study.¹ Oral antibiotics avoid these complications and are less burdensome to families.² Recently, a series of multicenter studies showed no difference in outcomes between oral and postdischarge intravenous antibiotic therapy (PD-IV) for complicated appendicitis, osteomyelitis, and complicated pneumonia.^3-5

Despite a growing body of evidence suggesting that oral therapy ought to be the default treatment strategy rather than PD-IV, the extent to which practices have changed is unknown. In this study, we measured national trends in PD-IV use and variation by hospital for complicated appendicitis, osteomyelitis, and complicated pneumonia.

We performed a retrospective cohort study of children discharged from hospitals that contributed data to the Pediatric Health Information System (PHIS) database from January 2000 through December 2018. PHIS is an administrative database of children’s hospitals managed by the Children’s Hospital Association (Lenexa, Kansas) and contains deidentified patient-­level demographic data, discharge diagnosis and procedure codes, and detailed billing information, including medical supply charges.

The cohorts were defined using International Classification of Diseases, 9th and 10th Revisions (ICD-9 and ICD-10) discharge diagnosis and procedure codes. Patients admitted through September 2015 were identified using ICD-9 codes and patients admitted from October 2015 through December 2018 were identified using ICD-10 codes. The Centers for Medicaid & Medicare Services crosswalk was used to align ICD-9 and ICD-10 codes.⁶ Inclusion and exclusion criteria identifying cohorts of children hospitalized for complicated appendicitis, osteomyelitis, or complicated pneumonia were based on prior studies using the PHIS database.^3-5 These studies augmented the PHIS administrative dataset with local chart review to identify patients from 2009-2012 with the following inclusion and exclusion criteria: Patients with complicated appendicitis were defined by a diagnosis code for acute appendicitis and a procedure code for appendectomy, with postoperative length of stay lasting between 3 and 7 days. Patients with osteomyelitis had a diagnosis code of acute or unspecified osteomyelitis with a hospital length of stay between 2 and 14 days. Patients with complicated pneumonia were defined by a diagnosis code for both pneumonia and pleural effusion with one of these as the primary diagnosis. Patients were excluded if they were older than 18 years or if they were younger than 2 months for osteomyelitis and complicated pneumonia or younger than 3 years for appendicitis. For all three conditions, children with a complex chronic condition⁷ were excluded. Only the index encounter meeting inclusion and exclusion criteria for each patient was included. PD-IV therapy was defined using procedure codes and hospital charges during the index hospitalization. This definition for PD-IV therapy has been validated among children with complicated pneumonia, demonstrating positive and negative predictive values for PICC exposure of 85% and 99%, respectively.⁸

Trends in the percentage of patients receiving PD-IV were adjusted for age, race, insurance type, intensive care unit days, and hospital-level case mix index with use of Poisson regression. Calculated risk ratios represent the change in PD-IV across the entire 19-year study period for each condition (as opposed to an annual rate of change). An inflection point for each condition was identified using piecewise linear regression in which the line slope has one value up to a point in time and a second value after that point. The transition point is determined by maximizing model fit.

Some hospitals were added to the database throughout the time period and therefore did not have data for all years of the study. To account for the possibility of a group of high– or low–PD-IV use hospitals entering the cohort and biasing the overall trend, we performed a sensitivity analysis restricted to hospitals continuously contributing data to PHIS every year between 2004 (when a majority of hospitals joined PHIS) and 2018. Significance testing for individual hospital trends was conducted among continuously contributing hospitals, with each hospital tested in the above Poisson model independently.

For the most recent year of 2018, we reported the distribution of adjusted percentages of PD-IV at the individual hospital level. Only hospitals with at least five patients for a given condition are included in the percent PD-IV calculations for 2018. To examine the extent to which an individual hospital might be a low– or high–PD-IV user across conditions, we divided hospitals into quartiles based on PD-IV use for each condition in 2017-2018 and calculated the percent of hospitals in the lowest- and highest-use quartiles for all three conditions. All statistics were performed using Stata 15 (StataCorp).

Among 52 hospitals over a 19-year study period, there were 60,575 hospitalizations for complicated appendicitis, 24,753 hospitalizations for osteomyelitis, and 13,700 hospitalizations for complicated pneumonia. From 2000 to 2018, PD-IV decreased from 13% to 2% (RR, 0.15; 95% CI, 0.14-0.16) for complicated appendicitis, from 61% to 22% (RR, 0.41; 95% CI, 0.39-0.43) for osteomyelitis, and from 29% to 19% (RR, 0.63; 95% CI, 0.58-0.69) for complicated pneumonia (Figure 1). The inflection points occurred in 2009 for complicated appendicitis, 2009 for complicated pneumonia, and 2010 for osteomyelitis. The sensitivity analysis included 31 hospitals that contributed data to PHIS for every year between 2004-2018 and revealed similar findings for all three conditions: Complicated appendicitis had an RR of 0.15 (95% CI, 0.14-0.17), osteomyelitis had an RR of 0.34 (95% CI, 0.32-0.36), and complicated pneumonia had an RR of 0.55 (95% CI, 0.49-0.61). Most individual hospitals decreased PD-IV use (complicated appendicitis: 21 decreased, 8 no change, 2 increased; osteomyelitis: 25 decreased, 6 no change; complicated pneumonia: 14 decreased, 16 no change, 1 increased). While overall decreases in PD-IV were observed for all three conditions, considerable variation remained in 2018 for use of PD-IV (Figure 2), particularly for osteomyelitis (median, 18%; interquartile range [IQR] 9%-40%) and complicated pneumonia (median, 13%; IQR, 3%-30%). In 2017-2018, 1 out of 52 hospitals was in the lowest PD-IV–use quartile for all three conditions, and three hospitals were in the highest-use quartile for all three conditions.

Over a 19-year period, we observed a national decline in use of PD-IV for three serious and common bacterial infections. The decline in PD-IV is notable given that it has occurred largely in the absence of nationally coordinated guidelines or improvement efforts. Despite the overall declines, substantial variation in the use of PD-IV for these conditions persists across children’s hospitals.

The observed decrease in PD-IV use is a natural example of deimplementation, the abandonment of medical practices found to be harmful or ineffective.⁹ What is most compelling about the deimplementation of PD-IV for these infectious conditions is the seemingly organic motivation that propelled it. Studies of physician practice patterns for interventions that have undergone evidence reversals demonstrate that physicians might readily implement new interventions with an early evidence base but be less willing to deimplement them when more definitive evidence later questions their efficacy.¹⁰ Therefore, concerted improvement efforts backed by national guidelines are often needed to reduce the use of a widely accepted medical practice. For example, as evidence questioning the efficacy of steroid use in bronchiolitis mounted,¹¹ bronchiolitis guidelines recommended against steroid use¹² and a national quality improvement effort led to reductions in exposure to steroids among patients hospitalized with bronchiolitis.¹³ Complicated intra-abdominal infection guidelines acknowledge oral antibiotic therapy as an option,¹⁴ but no such national guidelines or improvement projects exist for osteomyelitis or complicated pneumonia PD-IV.

What is it about PD-IV for complicated appendicitis, osteomyelitis, and complicated pneumonia that fostered the observed organic deimplementation? Our findings that few hospitals were in the top or bottom quartile of PD-IV across all three conditions suggest that the impetus to decrease PD-IV was not likely the product of a broad hospital-wide practice shift. Most deimplementation frameworks suggest that successful deimplementation must be supported by high-quality evidence that the intervention is not only ineffective, but also harmful.¹⁵ In this case, the inflection point for osteomyelitis occurred in 2009, the same year that the first large multicenter study suggesting efficacy and decreased complications of early oral therapy for osteomyelitis was published.¹⁶ A direct link between a publication and inflection points for complicated pneumonia and appendicitis is less clear. It is possible that growth of the field of pediatric hospital medicine,¹⁷ with a stated emphasis on healthcare value,¹⁸ played a role. Greater understanding of the drivers and barriers to deimplementation in this and similar contexts will be important.

Our study has some important limitations. While inclusion and exclusion criteria were consistent over the study period, practice patterns (ie, length of stay in uncomplicated patients) change and could alter the case-mix of patients over time. Additionally, the PHIS database largely comprises children’s hospitals, and the trends we observed in PD-IV may not generalize to community settings.

The degree of deimplementation of PD-IV observed across children’s hospitals is impressive, but opportunity for further improvement likely remains. We found that marked hospital-­level variation in use of PD-IV still exists, with some hospitals almost never using PD-IV and others using it for most patients. While the ideal amount of PD-IV is probably not zero, a portion of the observed variation likely represents overuse of PD-IV. To reduce costs and complications associated with antibiotic therapy, national guidelines and a targeted national improvement collaborative may be necessary to achieve further reductions in PD-IV.

Healthcare quality is defined as the extent to which healthcare services result in desired outcomes.¹ Quality of care depends on how the healthcare system’s various components, including healthcare practitioners, interact to meet each patient’s needs.² These components can be shaped to achieve desired outcomes through rules, incentives, and other approaches, but influencing the behaviors of each component, such as the performance of hospitalists, requires defining goals for performance and implementing measurement approaches to assess progress toward these goals.

One set of principles to define goals for quality and guide assessment of desired behaviors is the multidimensional STEEEP framework. This framework, created by the Institute of Medicine, identifies six domains of quality: Safe, Timely, Effective, Efficient, Equitable, and Patient Centered.² Briefly, “Safe” means avoiding injuries to patients, “Timely” means reducing waits and delays in care, “Effective” means providing care based on evidence, “Efficient” means avoiding waste, “Equitable” means ensuring quality does not vary based on personal characteristics such as race and gender, and “Patient Centered” means providing care that is responsive to patients’ values and preferences. The STEEEP domains are not coequal; rather, they ensure that quality is considered broadly, while avoiding errors such as measuring only an intervention’s impact on effectiveness but not assessing its impact on multiple domains of quality, such as how patient centered, efficient (cost effective), or equitable the resulting care is.

Based on our review of the literature, a multidimensional framework like STEEEP has not been used in defining and assessing the quality of individual hospitalists’ performance. Some quality metrics at the hospital level impact several dimensions simultaneously, such as door to balloon time for acute myocardial infarction, which measures effectiveness and timeliness of care. Programs like pay-for-performance, Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS), and the Merit-Based Incentive Payment System (MIPS) have tied reimbursement to assessments aligned with several STEEEP domains at both individual and institutional levels but lack a holistic approach to quality.^3-6 The every-­other-year State of Hospital Medicine Report, the most widely used description of individual hospitalist performance, reports group-level performance including relative value units and whether groups are accountable for measures of quality such as performance on core measures, timely documentation, and “citizenship” (eg, committee participation or academic work).⁷ While these are useful benchmarks, the report focuses on performance at the group level. Concurrently, several academic groups have described more complete dashboards or scorecards to assess individual hospitalist performance, primarily designed to facilitate comparison across hospitalist groups or to incentivize overall group performance.^8-10 However, these efforts are not guided by an overarching framework and are structured after traditional academic models with components related to teaching and scholarship, which may not translate to nonacademic environments. Finally, the Core Competencies for Hospital Medicine outlines some goals for hospitalist performance but does not speak to specific measurement approaches.¹¹

Overall, assessing individual hospitalist performance is hindered by lack of consensus on important concepts to measure, a limited number of valid measures, and challenges in data collection such as resource limitations and feasibility. Developing and refining measures grounded in the STEEEP framework may provide a more comprehensive assessment of hospitalist quality and identify approaches to improve overall health outcomes. Comparative data could help individual hospitalists improve performance; leaders of hospitalist groups could use this data to guide faculty development and advancement as they ensure quality care at the individual, group, and system levels.

To better inform quality measurement of individual hospitalists, we sought to identify existing publications on individual hospitalist quality. Our goal was to define the published literature about quality measurement at the individual hospitalist level, relate these publications to domains of quality defined by the STEEEP framework, and identify directions for assessment or further research that could affect the overall quality of care.

We conducted a scoping review following methods outlined by Arksey and O’Malley¹² and Tricco.¹³ The goal of a scoping review is to map the extent of research within a specific field. This methodology is well suited to characterizing the existing research related to the quality of hospitalist care at the individual level. A protocol for the scoping review was not registered.

Evidence Search

A systematic search for published, English-language literature on hospitalist care was conducted in Medline (Ovid; 1946 - June 4, 2019) on June 5, 2019. The search used a combination of keywords and controlled vocabulary for the concept of hospitalists or hospital medicine. The search strategy used in this review is described in the Appendix. In addition, a hand search of reference lists of articles was used to discover publications not identified in the database searches.

Study Selection

All references were uploaded to Covidence systematic review software (www.covidence.org; Covidence), and duplicates were removed. Four reviewers (A.D., B.C., L.H., R.Q.) conducted title and abstract, as well as full-text, review to identify studies that measured differences in the performance of hospitalists at the individual level. Any disagreements among reviewers were resolved by consensus. Articles included both adult and pediatric populations. Articles that focused on group-level outcomes could be included if nonpooled data at the individual level was also reported. Studies were excluded if they did not focus on individual quality of care indicators or were not published in English.

Data Charting and Synthesis

We extracted the following information using a standardized data collection form: author, title, year of publication, study design, intervention, and outcome measures. Original manuscripts were accessed as needed to supplement analysis. Critical appraisal of individual studies was not conducted in this review because the goal of this review was to analyze which quality indicators have been studied and how they were measured. Articles were then coded for their alignment to the STEEEP framework by two reviewers (AD and BC). After initial coding was conducted, the reviewers met to consolidate codes and resolve any disagreement by consensus. The results of the analysis were summarized in both text and tabular format with studies grouped by focus of assessment with each one’s methods of assessment listed.

Results of the search strategy are shown in the Figure. The search retrieved a total of 2,363 references of which 113 were duplicates, leaving 2,250 to be screened. After title and abstract and full-text screening, 42 studies were included in the review. The final 42 studies were coded for alignment with the STEEEP framework. The Table displays the focus of assessment and methods of assessment within each STEEEP domain.

Eighteen studies were coded into a single domain while the rest were coded into at least two domains. The domain Patient Centered was coded as having the most studies (n = 23), followed by the domain of Safe (n = 15). Timely, Effective, and Efficient domains had 11, 9, and 12 studies, respectively. No studies were coded into the domain of Equitable.

Safe

Nearly all studies coded into the Safe domain focused on transitions of care. These included transfers into a hospital from other hospitals,¹⁴ transitions of care to cross-covering providers^15,16 and new primary providers,¹⁷ and transition out from the acute care setting.^18-28 Measures of hospital discharge included measures of both processes^18-22 and outcomes.^23-27 Methods of assessment varied from use of trained observers or scorers to surveys of individuals and colleagues about performance. Though a few leveraged informatics,^22,27 all approaches relied on human interaction, and none were automated.

Timely

All studies coded into the Timely domain were coded into at least one other domain. For example, Anderson et al looked at how hospitalists communicated about potential life-limiting illness at the time of hospital admission and the subsequent effects on plans of care²⁹; this was coded as both Timely and Patient Centered. Likewise, another group of studies centered on application of evidence-based guidelines, such as giving antibiotics within a certain time interval for sepsis and were coded as both Timely and Effective. Another set of authors described dashboards or scorecards that captured a number of group-level metrics of processes of care that span STEEEP domains and may be applicable to individuals, including Fox et al for pediatrics⁸ and Hwa et al for an adult academic hospitalist group.⁹ Methods of assessment varied widely across studies and included observations in the clinical environment,^28,30,31 performance in simulations,³² and surveys about performance.^22-26 A handful of approaches were more automated and made use of informatics^8,9,22 or data collected for other health system purposes.^8,9

Effective

Effectiveness was most often assessed through adherence to consensus and evidence-based guidelines. Examples included processes of care related to sepsis, venous thromboembolism prophylaxis, COPD, heart failure, pediatric asthma, and antibiotic appropriateness.^8,9,23,32-36 Through the review, multiple other studies that included group-level measures of effectiveness for a variety of health conditions were excluded because data on individual-level variation were not reported. Methods of assessment included expert review of cases or discharge summaries, compliance with core measures, performance in simulation, and self-assessment on practice behaviors. Other than those efforts aligned with institutional data collection, most approaches were resource intensive.

Efficient

As with those in the Timely domain, most studies coded into the Efficient domain were coded into at least one other domain. One exception measured unnecessary daily lab work and both showed provider-level variation and demonstrated improvement in quality based on an intervention.³⁷ Another paper coded into the Effective domain evaluated adherence to components of the Choosing Wisely® recommendations.³⁴ In addition to these two studies focusing on cost efficacy, other studies coded to this domain assessed concepts such as ensuring more efficient care from other providers by optimizing transitions of care^15-17 and clarifying patients’ goals for care.³⁸ Although integrating insurer information into care plans is emphasized in the Core Competencies of Hospital Medicine,¹¹ this concept was not represented in any of the identified articles. Methods of assessment varied and mostly relied on observation of behaviors or survey of providers. Several approaches were more automated or used Medicare claims data to assess the efficiency of individual providers relative to peers.^34,37,39

Equitable

Among the studies reviewed, none were coded into the Equitable domain despite care of vulnerable populations being identified as a core competency of hospital medicine.⁴⁰

Patient Centered

Studies coded to the Patient Centered domain assessed hospitalist performance through ratings of patient satisfaction,^8,9,41-44 rating of communication between hospitalists and patients,^{19-21,29,45-51} identification of patient preferences,^38,52 outcomes of patient-centered care activities,^27,28 and peer ratings.^53,54 Authors applied several theoretical constructs to these assessments including shared decision-making,⁵⁰ etiquette-based medicine,^47,48 empathetic responsiveness,⁴⁵ agreement about the goals of care between the patient and healthcare team members,⁵² and lapses in professionalism.⁵³ Studies often crossed STEEEP domains, such as those assessing quality of discharge information provided to patients, which were coded as both Safe and Patient Centered.^19-21 In addition to coded or observed performance in the clinical setting, studies in this domain also used patient ratings as a method of assessment.^{8,9,28,41-44,49,50} Only a few of these approaches aligned with existing performance measures of health systems and were more automated.^8,9

This scoping review of performance data for individual hospitalists coded to the STEEEP framework identified robust areas in the published literature, as well as opportunities to develop new approaches or refine existing measures. Transitions of care, both intrahospital and at discharge, and adherence to evidence-based guidelines are areas for which current research has created a foundation for care that is Safe, Timely, Effective, and Efficient. The Patient Centered domain also has several measures described, though the conceptual underpinnings are heterogeneous, and consensus appears necessary to compare performance across groups. No studies were coded to the Equitable domain. Across domains, approaches to measurement varied in resource intensity from simple ones, like integrating existing data collected by hospitals, to more complex ones, like shadowing physicians or coding interactions.

Methods of assessment coded into the Safe domain focused on communication and, less so, patient outcomes around transitions of care. Transitions of care that were evaluated included transfer of patients into a new facility, sign-out to new physicians for both cross-cover responsibilities and for newly assuming the role of primary attending, and discharge from the hospital. Most measures rated the quality of communication, although several^23-27 examined patient outcomes. Approaches that survey individuals downstream from a transition of care^15,17,24-26 may be the simplest and most feasible approach to implement in the future but, as described to date, do not include all transitions of care and may miss patient outcomes. Important core competencies for hospital medicine under the Safe domain that were not identified in this review include areas such as diagnostic error, hospital-acquired infections, error reporting, and medication safety.¹¹ These are potential areas for future measure development.

The assessments in many studies were coded across more than one domain; for example, measures of the application of evidence-based guidelines were coded into domains of Effective, Timely, Efficient, and others. Applying the six domains of the STEEEP framework revealed the multidimensional outcomes of hospitalist work and could guide more meaningful quality assessments of individual hospitalist performance. For example, assessing adherence to evidence-based guidelines, as well as consideration of the Core Competencies of Hospital Medicine and recommendations of the Choosing Wisely® campaign, are promising areas for measurement and may align with existing hospital metrics. Notably, several reviewed studies measured group-level adherence to guidelines but were excluded because they did not examine variation at the individual level. Future measures based on evidence-based guidelines could center on the Effective domain while also integrating assessment of domains such as Efficient, Timely, and Patient Centered and, in so doing, provide a richer assessment of the diverse aspects of quality.

Several other approaches in the domains of Timely, Effective, and Efficient were described only in a few studies yet deserve consideration for further development. Two time-­motion studies^30,31 were coded into the domains of Timely and Efficient and would be cumbersome in regular practice but, with advances in wearable technology and electronic health records, could become more feasible in the future. Another approach used Medicare payment data to detect provider-level variation.³⁹ Potentially, “big data” could be analyzed in other ways to compare the performance of individual hospitalists.

The lack of studies coded into the Equitable domain may seem surprising, but the Institute for Healthcare Improvement identifies Equitable as the “forgotten aim” of the STEEEP framework. This organization has developed a guide for health care organizations to promote equitable care.⁵⁵ While this guide focuses mostly on organizational-level actions, some are focused on individual providers, such as training in implicit bias. Future research should seek to identify disparities in care by individual providers and develop interventions to address any discovered gaps.

The “Patient Centered” domain was the most frequently coded and had the most heterogeneous underpinnings for assessment. Studies varied widely in terminology and conceptual foundations. The field would benefit from future work to identify how “Patient Centered” care might be more clearly conceptualized, guided by comparative studies among different assessment approaches to define those most valid and feasible.

The overarching goal for measuring individual hospitalist quality should be to improve the delivery of patient care in a supportive and formative way. To further this goal, adding or expanding on metrics identified in this article may provide a more complete description of performance. As a future direction, groups should consider partnering with one another to define measurement approaches, collaborate with existing data sources, and even share deidentified individual data to establish performance benchmarks at the individual and group levels.

While this study used broad search terms to support completeness, the search process could have missed important studies. Grey literature, non–English language studies, and industry reports were not included in this review. Groups may also be using other assessments of individual hospitalist performance that are not published in the peer-reviewed literature. Coding of study assessments was achieved through consensus reconciliation; other coders might have classified studies differently.

This scoping review describes the peer-reviewed literature of individual hospitalist performance and is the first to link it to the STEEEP quality framework. Assessments of transitions of care, evidence-based care, and cost-effective care are exemplars in the published literature. Patient-centered care is well studied but assessed in a heterogeneous fashion. Assessments of equity in care are notably absent. The STEEEP framework provides a model to structure assessment of individual performance. Future research should build on this framework to define meaningful assessment approaches that are actionable and improve the welfare of our patients and our system.

The authors have nothing to disclose.

Healthcare quality is defined as the extent to which healthcare services result in desired outcomes.¹ Quality of care depends on how the healthcare system’s various components, including healthcare practitioners, interact to meet each patient’s needs.² These components can be shaped to achieve desired outcomes through rules, incentives, and other approaches, but influencing the behaviors of each component, such as the performance of hospitalists, requires defining goals for performance and implementing measurement approaches to assess progress toward these goals.

One set of principles to define goals for quality and guide assessment of desired behaviors is the multidimensional STEEEP framework. This framework, created by the Institute of Medicine, identifies six domains of quality: Safe, Timely, Effective, Efficient, Equitable, and Patient Centered.² Briefly, “Safe” means avoiding injuries to patients, “Timely” means reducing waits and delays in care, “Effective” means providing care based on evidence, “Efficient” means avoiding waste, “Equitable” means ensuring quality does not vary based on personal characteristics such as race and gender, and “Patient Centered” means providing care that is responsive to patients’ values and preferences. The STEEEP domains are not coequal; rather, they ensure that quality is considered broadly, while avoiding errors such as measuring only an intervention’s impact on effectiveness but not assessing its impact on multiple domains of quality, such as how patient centered, efficient (cost effective), or equitable the resulting care is.

Based on our review of the literature, a multidimensional framework like STEEEP has not been used in defining and assessing the quality of individual hospitalists’ performance. Some quality metrics at the hospital level impact several dimensions simultaneously, such as door to balloon time for acute myocardial infarction, which measures effectiveness and timeliness of care. Programs like pay-for-performance, Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS), and the Merit-Based Incentive Payment System (MIPS) have tied reimbursement to assessments aligned with several STEEEP domains at both individual and institutional levels but lack a holistic approach to quality.^3-6 The every-­other-year State of Hospital Medicine Report, the most widely used description of individual hospitalist performance, reports group-level performance including relative value units and whether groups are accountable for measures of quality such as performance on core measures, timely documentation, and “citizenship” (eg, committee participation or academic work).⁷ While these are useful benchmarks, the report focuses on performance at the group level. Concurrently, several academic groups have described more complete dashboards or scorecards to assess individual hospitalist performance, primarily designed to facilitate comparison across hospitalist groups or to incentivize overall group performance.^8-10 However, these efforts are not guided by an overarching framework and are structured after traditional academic models with components related to teaching and scholarship, which may not translate to nonacademic environments. Finally, the Core Competencies for Hospital Medicine outlines some goals for hospitalist performance but does not speak to specific measurement approaches.¹¹

Overall, assessing individual hospitalist performance is hindered by lack of consensus on important concepts to measure, a limited number of valid measures, and challenges in data collection such as resource limitations and feasibility. Developing and refining measures grounded in the STEEEP framework may provide a more comprehensive assessment of hospitalist quality and identify approaches to improve overall health outcomes. Comparative data could help individual hospitalists improve performance; leaders of hospitalist groups could use this data to guide faculty development and advancement as they ensure quality care at the individual, group, and system levels.

To better inform quality measurement of individual hospitalists, we sought to identify existing publications on individual hospitalist quality. Our goal was to define the published literature about quality measurement at the individual hospitalist level, relate these publications to domains of quality defined by the STEEEP framework, and identify directions for assessment or further research that could affect the overall quality of care.

We conducted a scoping review following methods outlined by Arksey and O’Malley¹² and Tricco.¹³ The goal of a scoping review is to map the extent of research within a specific field. This methodology is well suited to characterizing the existing research related to the quality of hospitalist care at the individual level. A protocol for the scoping review was not registered.

Evidence Search

A systematic search for published, English-language literature on hospitalist care was conducted in Medline (Ovid; 1946 - June 4, 2019) on June 5, 2019. The search used a combination of keywords and controlled vocabulary for the concept of hospitalists or hospital medicine. The search strategy used in this review is described in the Appendix. In addition, a hand search of reference lists of articles was used to discover publications not identified in the database searches.

Study Selection

All references were uploaded to Covidence systematic review software (www.covidence.org; Covidence), and duplicates were removed. Four reviewers (A.D., B.C., L.H., R.Q.) conducted title and abstract, as well as full-text, review to identify studies that measured differences in the performance of hospitalists at the individual level. Any disagreements among reviewers were resolved by consensus. Articles included both adult and pediatric populations. Articles that focused on group-level outcomes could be included if nonpooled data at the individual level was also reported. Studies were excluded if they did not focus on individual quality of care indicators or were not published in English.

Data Charting and Synthesis

We extracted the following information using a standardized data collection form: author, title, year of publication, study design, intervention, and outcome measures. Original manuscripts were accessed as needed to supplement analysis. Critical appraisal of individual studies was not conducted in this review because the goal of this review was to analyze which quality indicators have been studied and how they were measured. Articles were then coded for their alignment to the STEEEP framework by two reviewers (AD and BC). After initial coding was conducted, the reviewers met to consolidate codes and resolve any disagreement by consensus. The results of the analysis were summarized in both text and tabular format with studies grouped by focus of assessment with each one’s methods of assessment listed.

Results of the search strategy are shown in the Figure. The search retrieved a total of 2,363 references of which 113 were duplicates, leaving 2,250 to be screened. After title and abstract and full-text screening, 42 studies were included in the review. The final 42 studies were coded for alignment with the STEEEP framework. The Table displays the focus of assessment and methods of assessment within each STEEEP domain.

Eighteen studies were coded into a single domain while the rest were coded into at least two domains. The domain Patient Centered was coded as having the most studies (n = 23), followed by the domain of Safe (n = 15). Timely, Effective, and Efficient domains had 11, 9, and 12 studies, respectively. No studies were coded into the domain of Equitable.

Safe

Nearly all studies coded into the Safe domain focused on transitions of care. These included transfers into a hospital from other hospitals,¹⁴ transitions of care to cross-covering providers^15,16 and new primary providers,¹⁷ and transition out from the acute care setting.^18-28 Measures of hospital discharge included measures of both processes^18-22 and outcomes.^23-27 Methods of assessment varied from use of trained observers or scorers to surveys of individuals and colleagues about performance. Though a few leveraged informatics,^22,27 all approaches relied on human interaction, and none were automated.

Timely

All studies coded into the Timely domain were coded into at least one other domain. For example, Anderson et al looked at how hospitalists communicated about potential life-limiting illness at the time of hospital admission and the subsequent effects on plans of care²⁹; this was coded as both Timely and Patient Centered. Likewise, another group of studies centered on application of evidence-based guidelines, such as giving antibiotics within a certain time interval for sepsis and were coded as both Timely and Effective. Another set of authors described dashboards or scorecards that captured a number of group-level metrics of processes of care that span STEEEP domains and may be applicable to individuals, including Fox et al for pediatrics⁸ and Hwa et al for an adult academic hospitalist group.⁹ Methods of assessment varied widely across studies and included observations in the clinical environment,^28,30,31 performance in simulations,³² and surveys about performance.^22-26 A handful of approaches were more automated and made use of informatics^8,9,22 or data collected for other health system purposes.^8,9

Effective

Effectiveness was most often assessed through adherence to consensus and evidence-based guidelines. Examples included processes of care related to sepsis, venous thromboembolism prophylaxis, COPD, heart failure, pediatric asthma, and antibiotic appropriateness.^8,9,23,32-36 Through the review, multiple other studies that included group-level measures of effectiveness for a variety of health conditions were excluded because data on individual-level variation were not reported. Methods of assessment included expert review of cases or discharge summaries, compliance with core measures, performance in simulation, and self-assessment on practice behaviors. Other than those efforts aligned with institutional data collection, most approaches were resource intensive.

Efficient

As with those in the Timely domain, most studies coded into the Efficient domain were coded into at least one other domain. One exception measured unnecessary daily lab work and both showed provider-level variation and demonstrated improvement in quality based on an intervention.³⁷ Another paper coded into the Effective domain evaluated adherence to components of the Choosing Wisely® recommendations.³⁴ In addition to these two studies focusing on cost efficacy, other studies coded to this domain assessed concepts such as ensuring more efficient care from other providers by optimizing transitions of care^15-17 and clarifying patients’ goals for care.³⁸ Although integrating insurer information into care plans is emphasized in the Core Competencies of Hospital Medicine,¹¹ this concept was not represented in any of the identified articles. Methods of assessment varied and mostly relied on observation of behaviors or survey of providers. Several approaches were more automated or used Medicare claims data to assess the efficiency of individual providers relative to peers.^34,37,39

Equitable

Among the studies reviewed, none were coded into the Equitable domain despite care of vulnerable populations being identified as a core competency of hospital medicine.⁴⁰

Patient Centered

Studies coded to the Patient Centered domain assessed hospitalist performance through ratings of patient satisfaction,^8,9,41-44 rating of communication between hospitalists and patients,^{19-21,29,45-51} identification of patient preferences,^38,52 outcomes of patient-centered care activities,^27,28 and peer ratings.^53,54 Authors applied several theoretical constructs to these assessments including shared decision-making,⁵⁰ etiquette-based medicine,^47,48 empathetic responsiveness,⁴⁵ agreement about the goals of care between the patient and healthcare team members,⁵² and lapses in professionalism.⁵³ Studies often crossed STEEEP domains, such as those assessing quality of discharge information provided to patients, which were coded as both Safe and Patient Centered.^19-21 In addition to coded or observed performance in the clinical setting, studies in this domain also used patient ratings as a method of assessment.^{8,9,28,41-44,49,50} Only a few of these approaches aligned with existing performance measures of health systems and were more automated.^8,9

This scoping review of performance data for individual hospitalists coded to the STEEEP framework identified robust areas in the published literature, as well as opportunities to develop new approaches or refine existing measures. Transitions of care, both intrahospital and at discharge, and adherence to evidence-based guidelines are areas for which current research has created a foundation for care that is Safe, Timely, Effective, and Efficient. The Patient Centered domain also has several measures described, though the conceptual underpinnings are heterogeneous, and consensus appears necessary to compare performance across groups. No studies were coded to the Equitable domain. Across domains, approaches to measurement varied in resource intensity from simple ones, like integrating existing data collected by hospitals, to more complex ones, like shadowing physicians or coding interactions.

Methods of assessment coded into the Safe domain focused on communication and, less so, patient outcomes around transitions of care. Transitions of care that were evaluated included transfer of patients into a new facility, sign-out to new physicians for both cross-cover responsibilities and for newly assuming the role of primary attending, and discharge from the hospital. Most measures rated the quality of communication, although several^23-27 examined patient outcomes. Approaches that survey individuals downstream from a transition of care^15,17,24-26 may be the simplest and most feasible approach to implement in the future but, as described to date, do not include all transitions of care and may miss patient outcomes. Important core competencies for hospital medicine under the Safe domain that were not identified in this review include areas such as diagnostic error, hospital-acquired infections, error reporting, and medication safety.¹¹ These are potential areas for future measure development.

The assessments in many studies were coded across more than one domain; for example, measures of the application of evidence-based guidelines were coded into domains of Effective, Timely, Efficient, and others. Applying the six domains of the STEEEP framework revealed the multidimensional outcomes of hospitalist work and could guide more meaningful quality assessments of individual hospitalist performance. For example, assessing adherence to evidence-based guidelines, as well as consideration of the Core Competencies of Hospital Medicine and recommendations of the Choosing Wisely® campaign, are promising areas for measurement and may align with existing hospital metrics. Notably, several reviewed studies measured group-level adherence to guidelines but were excluded because they did not examine variation at the individual level. Future measures based on evidence-based guidelines could center on the Effective domain while also integrating assessment of domains such as Efficient, Timely, and Patient Centered and, in so doing, provide a richer assessment of the diverse aspects of quality.

Several other approaches in the domains of Timely, Effective, and Efficient were described only in a few studies yet deserve consideration for further development. Two time-­motion studies^30,31 were coded into the domains of Timely and Efficient and would be cumbersome in regular practice but, with advances in wearable technology and electronic health records, could become more feasible in the future. Another approach used Medicare payment data to detect provider-level variation.³⁹ Potentially, “big data” could be analyzed in other ways to compare the performance of individual hospitalists.

The lack of studies coded into the Equitable domain may seem surprising, but the Institute for Healthcare Improvement identifies Equitable as the “forgotten aim” of the STEEEP framework. This organization has developed a guide for health care organizations to promote equitable care.⁵⁵ While this guide focuses mostly on organizational-level actions, some are focused on individual providers, such as training in implicit bias. Future research should seek to identify disparities in care by individual providers and develop interventions to address any discovered gaps.

The “Patient Centered” domain was the most frequently coded and had the most heterogeneous underpinnings for assessment. Studies varied widely in terminology and conceptual foundations. The field would benefit from future work to identify how “Patient Centered” care might be more clearly conceptualized, guided by comparative studies among different assessment approaches to define those most valid and feasible.

The overarching goal for measuring individual hospitalist quality should be to improve the delivery of patient care in a supportive and formative way. To further this goal, adding or expanding on metrics identified in this article may provide a more complete description of performance. As a future direction, groups should consider partnering with one another to define measurement approaches, collaborate with existing data sources, and even share deidentified individual data to establish performance benchmarks at the individual and group levels.

While this study used broad search terms to support completeness, the search process could have missed important studies. Grey literature, non–English language studies, and industry reports were not included in this review. Groups may also be using other assessments of individual hospitalist performance that are not published in the peer-reviewed literature. Coding of study assessments was achieved through consensus reconciliation; other coders might have classified studies differently.

This scoping review describes the peer-reviewed literature of individual hospitalist performance and is the first to link it to the STEEEP quality framework. Assessments of transitions of care, evidence-based care, and cost-effective care are exemplars in the published literature. Patient-centered care is well studied but assessed in a heterogeneous fashion. Assessments of equity in care are notably absent. The STEEEP framework provides a model to structure assessment of individual performance. Future research should build on this framework to define meaningful assessment approaches that are actionable and improve the welfare of our patients and our system.

The authors have nothing to disclose.

Healthcare quality is defined as the extent to which healthcare services result in desired outcomes.¹ Quality of care depends on how the healthcare system’s various components, including healthcare practitioners, interact to meet each patient’s needs.² These components can be shaped to achieve desired outcomes through rules, incentives, and other approaches, but influencing the behaviors of each component, such as the performance of hospitalists, requires defining goals for performance and implementing measurement approaches to assess progress toward these goals.

One set of principles to define goals for quality and guide assessment of desired behaviors is the multidimensional STEEEP framework. This framework, created by the Institute of Medicine, identifies six domains of quality: Safe, Timely, Effective, Efficient, Equitable, and Patient Centered.² Briefly, “Safe” means avoiding injuries to patients, “Timely” means reducing waits and delays in care, “Effective” means providing care based on evidence, “Efficient” means avoiding waste, “Equitable” means ensuring quality does not vary based on personal characteristics such as race and gender, and “Patient Centered” means providing care that is responsive to patients’ values and preferences. The STEEEP domains are not coequal; rather, they ensure that quality is considered broadly, while avoiding errors such as measuring only an intervention’s impact on effectiveness but not assessing its impact on multiple domains of quality, such as how patient centered, efficient (cost effective), or equitable the resulting care is.

Based on our review of the literature, a multidimensional framework like STEEEP has not been used in defining and assessing the quality of individual hospitalists’ performance. Some quality metrics at the hospital level impact several dimensions simultaneously, such as door to balloon time for acute myocardial infarction, which measures effectiveness and timeliness of care. Programs like pay-for-performance, Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS), and the Merit-Based Incentive Payment System (MIPS) have tied reimbursement to assessments aligned with several STEEEP domains at both individual and institutional levels but lack a holistic approach to quality.^3-6 The every-­other-year State of Hospital Medicine Report, the most widely used description of individual hospitalist performance, reports group-level performance including relative value units and whether groups are accountable for measures of quality such as performance on core measures, timely documentation, and “citizenship” (eg, committee participation or academic work).⁷ While these are useful benchmarks, the report focuses on performance at the group level. Concurrently, several academic groups have described more complete dashboards or scorecards to assess individual hospitalist performance, primarily designed to facilitate comparison across hospitalist groups or to incentivize overall group performance.^8-10 However, these efforts are not guided by an overarching framework and are structured after traditional academic models with components related to teaching and scholarship, which may not translate to nonacademic environments. Finally, the Core Competencies for Hospital Medicine outlines some goals for hospitalist performance but does not speak to specific measurement approaches.¹¹

Overall, assessing individual hospitalist performance is hindered by lack of consensus on important concepts to measure, a limited number of valid measures, and challenges in data collection such as resource limitations and feasibility. Developing and refining measures grounded in the STEEEP framework may provide a more comprehensive assessment of hospitalist quality and identify approaches to improve overall health outcomes. Comparative data could help individual hospitalists improve performance; leaders of hospitalist groups could use this data to guide faculty development and advancement as they ensure quality care at the individual, group, and system levels.

To better inform quality measurement of individual hospitalists, we sought to identify existing publications on individual hospitalist quality. Our goal was to define the published literature about quality measurement at the individual hospitalist level, relate these publications to domains of quality defined by the STEEEP framework, and identify directions for assessment or further research that could affect the overall quality of care.

We conducted a scoping review following methods outlined by Arksey and O’Malley¹² and Tricco.¹³ The goal of a scoping review is to map the extent of research within a specific field. This methodology is well suited to characterizing the existing research related to the quality of hospitalist care at the individual level. A protocol for the scoping review was not registered.

Evidence Search

A systematic search for published, English-language literature on hospitalist care was conducted in Medline (Ovid; 1946 - June 4, 2019) on June 5, 2019. The search used a combination of keywords and controlled vocabulary for the concept of hospitalists or hospital medicine. The search strategy used in this review is described in the Appendix. In addition, a hand search of reference lists of articles was used to discover publications not identified in the database searches.

Study Selection

All references were uploaded to Covidence systematic review software (www.covidence.org; Covidence), and duplicates were removed. Four reviewers (A.D., B.C., L.H., R.Q.) conducted title and abstract, as well as full-text, review to identify studies that measured differences in the performance of hospitalists at the individual level. Any disagreements among reviewers were resolved by consensus. Articles included both adult and pediatric populations. Articles that focused on group-level outcomes could be included if nonpooled data at the individual level was also reported. Studies were excluded if they did not focus on individual quality of care indicators or were not published in English.

Data Charting and Synthesis

We extracted the following information using a standardized data collection form: author, title, year of publication, study design, intervention, and outcome measures. Original manuscripts were accessed as needed to supplement analysis. Critical appraisal of individual studies was not conducted in this review because the goal of this review was to analyze which quality indicators have been studied and how they were measured. Articles were then coded for their alignment to the STEEEP framework by two reviewers (AD and BC). After initial coding was conducted, the reviewers met to consolidate codes and resolve any disagreement by consensus. The results of the analysis were summarized in both text and tabular format with studies grouped by focus of assessment with each one’s methods of assessment listed.

Results of the search strategy are shown in the Figure. The search retrieved a total of 2,363 references of which 113 were duplicates, leaving 2,250 to be screened. After title and abstract and full-text screening, 42 studies were included in the review. The final 42 studies were coded for alignment with the STEEEP framework. The Table displays the focus of assessment and methods of assessment within each STEEEP domain.

Eighteen studies were coded into a single domain while the rest were coded into at least two domains. The domain Patient Centered was coded as having the most studies (n = 23), followed by the domain of Safe (n = 15). Timely, Effective, and Efficient domains had 11, 9, and 12 studies, respectively. No studies were coded into the domain of Equitable.

Safe

Nearly all studies coded into the Safe domain focused on transitions of care. These included transfers into a hospital from other hospitals,¹⁴ transitions of care to cross-covering providers^15,16 and new primary providers,¹⁷ and transition out from the acute care setting.^18-28 Measures of hospital discharge included measures of both processes^18-22 and outcomes.^23-27 Methods of assessment varied from use of trained observers or scorers to surveys of individuals and colleagues about performance. Though a few leveraged informatics,^22,27 all approaches relied on human interaction, and none were automated.

Timely

All studies coded into the Timely domain were coded into at least one other domain. For example, Anderson et al looked at how hospitalists communicated about potential life-limiting illness at the time of hospital admission and the subsequent effects on plans of care²⁹; this was coded as both Timely and Patient Centered. Likewise, another group of studies centered on application of evidence-based guidelines, such as giving antibiotics within a certain time interval for sepsis and were coded as both Timely and Effective. Another set of authors described dashboards or scorecards that captured a number of group-level metrics of processes of care that span STEEEP domains and may be applicable to individuals, including Fox et al for pediatrics⁸ and Hwa et al for an adult academic hospitalist group.⁹ Methods of assessment varied widely across studies and included observations in the clinical environment,^28,30,31 performance in simulations,³² and surveys about performance.^22-26 A handful of approaches were more automated and made use of informatics^8,9,22 or data collected for other health system purposes.^8,9

Effective

Effectiveness was most often assessed through adherence to consensus and evidence-based guidelines. Examples included processes of care related to sepsis, venous thromboembolism prophylaxis, COPD, heart failure, pediatric asthma, and antibiotic appropriateness.^8,9,23,32-36 Through the review, multiple other studies that included group-level measures of effectiveness for a variety of health conditions were excluded because data on individual-level variation were not reported. Methods of assessment included expert review of cases or discharge summaries, compliance with core measures, performance in simulation, and self-assessment on practice behaviors. Other than those efforts aligned with institutional data collection, most approaches were resource intensive.

Efficient

As with those in the Timely domain, most studies coded into the Efficient domain were coded into at least one other domain. One exception measured unnecessary daily lab work and both showed provider-level variation and demonstrated improvement in quality based on an intervention.³⁷ Another paper coded into the Effective domain evaluated adherence to components of the Choosing Wisely® recommendations.³⁴ In addition to these two studies focusing on cost efficacy, other studies coded to this domain assessed concepts such as ensuring more efficient care from other providers by optimizing transitions of care^15-17 and clarifying patients’ goals for care.³⁸ Although integrating insurer information into care plans is emphasized in the Core Competencies of Hospital Medicine,¹¹ this concept was not represented in any of the identified articles. Methods of assessment varied and mostly relied on observation of behaviors or survey of providers. Several approaches were more automated or used Medicare claims data to assess the efficiency of individual providers relative to peers.^34,37,39

Equitable

Among the studies reviewed, none were coded into the Equitable domain despite care of vulnerable populations being identified as a core competency of hospital medicine.⁴⁰

Patient Centered

Studies coded to the Patient Centered domain assessed hospitalist performance through ratings of patient satisfaction,^8,9,41-44 rating of communication between hospitalists and patients,^{19-21,29,45-51} identification of patient preferences,^38,52 outcomes of patient-centered care activities,^27,28 and peer ratings.^53,54 Authors applied several theoretical constructs to these assessments including shared decision-making,⁵⁰ etiquette-based medicine,^47,48 empathetic responsiveness,⁴⁵ agreement about the goals of care between the patient and healthcare team members,⁵² and lapses in professionalism.⁵³ Studies often crossed STEEEP domains, such as those assessing quality of discharge information provided to patients, which were coded as both Safe and Patient Centered.^19-21 In addition to coded or observed performance in the clinical setting, studies in this domain also used patient ratings as a method of assessment.^{8,9,28,41-44,49,50} Only a few of these approaches aligned with existing performance measures of health systems and were more automated.^8,9

This scoping review of performance data for individual hospitalists coded to the STEEEP framework identified robust areas in the published literature, as well as opportunities to develop new approaches or refine existing measures. Transitions of care, both intrahospital and at discharge, and adherence to evidence-based guidelines are areas for which current research has created a foundation for care that is Safe, Timely, Effective, and Efficient. The Patient Centered domain also has several measures described, though the conceptual underpinnings are heterogeneous, and consensus appears necessary to compare performance across groups. No studies were coded to the Equitable domain. Across domains, approaches to measurement varied in resource intensity from simple ones, like integrating existing data collected by hospitals, to more complex ones, like shadowing physicians or coding interactions.

Methods of assessment coded into the Safe domain focused on communication and, less so, patient outcomes around transitions of care. Transitions of care that were evaluated included transfer of patients into a new facility, sign-out to new physicians for both cross-cover responsibilities and for newly assuming the role of primary attending, and discharge from the hospital. Most measures rated the quality of communication, although several^23-27 examined patient outcomes. Approaches that survey individuals downstream from a transition of care^15,17,24-26 may be the simplest and most feasible approach to implement in the future but, as described to date, do not include all transitions of care and may miss patient outcomes. Important core competencies for hospital medicine under the Safe domain that were not identified in this review include areas such as diagnostic error, hospital-acquired infections, error reporting, and medication safety.¹¹ These are potential areas for future measure development.

The assessments in many studies were coded across more than one domain; for example, measures of the application of evidence-based guidelines were coded into domains of Effective, Timely, Efficient, and others. Applying the six domains of the STEEEP framework revealed the multidimensional outcomes of hospitalist work and could guide more meaningful quality assessments of individual hospitalist performance. For example, assessing adherence to evidence-based guidelines, as well as consideration of the Core Competencies of Hospital Medicine and recommendations of the Choosing Wisely® campaign, are promising areas for measurement and may align with existing hospital metrics. Notably, several reviewed studies measured group-level adherence to guidelines but were excluded because they did not examine variation at the individual level. Future measures based on evidence-based guidelines could center on the Effective domain while also integrating assessment of domains such as Efficient, Timely, and Patient Centered and, in so doing, provide a richer assessment of the diverse aspects of quality.

Several other approaches in the domains of Timely, Effective, and Efficient were described only in a few studies yet deserve consideration for further development. Two time-­motion studies^30,31 were coded into the domains of Timely and Efficient and would be cumbersome in regular practice but, with advances in wearable technology and electronic health records, could become more feasible in the future. Another approach used Medicare payment data to detect provider-level variation.³⁹ Potentially, “big data” could be analyzed in other ways to compare the performance of individual hospitalists.

The lack of studies coded into the Equitable domain may seem surprising, but the Institute for Healthcare Improvement identifies Equitable as the “forgotten aim” of the STEEEP framework. This organization has developed a guide for health care organizations to promote equitable care.⁵⁵ While this guide focuses mostly on organizational-level actions, some are focused on individual providers, such as training in implicit bias. Future research should seek to identify disparities in care by individual providers and develop interventions to address any discovered gaps.

The “Patient Centered” domain was the most frequently coded and had the most heterogeneous underpinnings for assessment. Studies varied widely in terminology and conceptual foundations. The field would benefit from future work to identify how “Patient Centered” care might be more clearly conceptualized, guided by comparative studies among different assessment approaches to define those most valid and feasible.

The overarching goal for measuring individual hospitalist quality should be to improve the delivery of patient care in a supportive and formative way. To further this goal, adding or expanding on metrics identified in this article may provide a more complete description of performance. As a future direction, groups should consider partnering with one another to define measurement approaches, collaborate with existing data sources, and even share deidentified individual data to establish performance benchmarks at the individual and group levels.

While this study used broad search terms to support completeness, the search process could have missed important studies. Grey literature, non–English language studies, and industry reports were not included in this review. Groups may also be using other assessments of individual hospitalist performance that are not published in the peer-reviewed literature. Coding of study assessments was achieved through consensus reconciliation; other coders might have classified studies differently.

This scoping review describes the peer-reviewed literature of individual hospitalist performance and is the first to link it to the STEEEP quality framework. Assessments of transitions of care, evidence-based care, and cost-effective care are exemplars in the published literature. Patient-centered care is well studied but assessed in a heterogeneous fashion. Assessments of equity in care are notably absent. The STEEEP framework provides a model to structure assessment of individual performance. Future research should build on this framework to define meaningful assessment approaches that are actionable and improve the welfare of our patients and our system.

The authors have nothing to disclose.

Inspired by the ABIM Foundation’s Choosing Wisely^® campaign, the “Things We Do for No Reason^™” (TWDFNR) series reviews practices that have become common parts of hospital care but may provide little value to our patients. Practices reviewed in the TWDFNR series do not represent clear-cut conclusions or clinical practice standards but are meant as a starting place for research and active discussions among hospitalists and patients. We invite you to be part of that discussion.

The hospitalist admits a 52-year-old man with alcoholic cirrhosis for tense ascites and altered mentation. Home medications include furosemide, spironolactone, lactulose, and rifaximin, but his family notes he ran out last week. Although afebrile and hemodynamically stable, the patient’s coagulopathy, with an international normalized ratio (INR) of 2.3, and thrombocytopenia, with a platelet count of 37,000/μL, worries the hospitalist. The hospitalist wonders whether to transfuse fresh frozen plasma (FFP) and platelets prior to diagnostic paracentesis to reduce the risk of procedural bleeding.

Many patients undergoing paracentesis have severe liver disease and present with both thrombocytopenia and elevated INRs. While platelet count and INR serve as surrogate markers for bleeding risk in many settings, clinicians often extrapolate this concept to patients with cirrhosis. Many hospitalists routinely check INR and platelet count and administer FFP and platelets prior to diagnostic or therapeutic paracentesis to mitigate procedure-related bleeding risk. Some medical resources recommend this practice,¹ while case reports and personal experiences with bleeding in these patients create availability bias that influences perception of bleeding risk.² One recent study of patients with decompensated cirrhosis presenting to a US tertiary care center found that, of those receiving large-­volume paracentesis, 22.2% received prophylactic FFP and 17.3% received prophylactic platelets before paracentesis.³

Advances in our understanding of coagulation in cirrhosis demonstrate neither INR nor platelet count accurately predict bleeding risk in this population. Additionally, evidence demonstrates the overall safety of paracentesis in cirrhosis—even in the presence of high INR and thrombocytopenia—and the lack of benefit from prophylactic transfusions with FFP or platelets.

Substantial evidence in patients with cirrhosis demonstrates that changes in coagulation and platelet function confer a “balanced coagulopathy” in which patients oscillate between hyper- and hypocoagulable states. In a cirrhotic liver, hepatic synthetic dysfunction results in a complex milieu through reduced production and plasma concentrations of both pro- and anticoagulant factors that can lead to either bleeding or clotting.⁴ This “rebalancing” makes prothrombin time (PT) and INR unreliable indicators of bleeding or clotting risk. Similarly, in patients with cirrhosis, thrombocytopenia does not necessarily reflect impaired clotting ability. These patients experience an increase in production of von Willebrand Factor, which may compensate for low platelet counts by producing stronger platelet adhesion to collagen.⁴ Unfortunately, we currently lack a reliable test or risk score to assess true bleeding risk in patients with cirrhosis.

Observational studies support these laboratory findings. Large case series consistently demonstrate no association between INR or platelet counts and bleeding risk in either diagnostic or therapeutic paracentesis, including large-volume paracentesis (See Appendix for a list of recent representative studies).^5-10 Moreover, prophylactic transfusion of FFP or platelets does not significantly reduce bleeding risk.

In a 1991 study by McVay et al, the researchers examined bleeding outcomes of 441 paracenteses performed on hospitalized patients.¹¹ Among patients who did not receive FFP prior to paracentesis, only one required a transfusion for procedure-­related bleeding, an event rate of 0.25%. This single patient had a normal platelet count and an elevated PT to the same extent as 261 others who underwent paracentesis without complication. In a pooled analysis that included 391 paracenteses and 207 thoracenteses, the authors concluded neither PT nor platelet level predicted bleeding risk. Similarly, the largest published case series on this topic examined 4,729 paracenteses over a decade on a liver unit and found low rates of major bleeding (0.19%).⁹ Furthermore, preprocedure INR or platelet count did not correlate with bleeding risk. The authors did not report preprocedure transfusion rates, but they noted transfusions occurred only “occasionally.”

Subsequent observational studies have consistently revealed low bleeding risks even in settings of high coagulopathy prevalence. Grabau et al reviewed all large-volume paracenteses performed in a gastroenterology clinic over 7 years.¹⁰ In over 1,100 procedures, no major bleeding events occurred despite 27% of patients having INR greater than 2.0 and 54% having platelet counts less than 50,000/μL. Kurup et al examined bleeding risk among 304 procedures performed on patients with platelet counts less than 50,000/μL referred to radiology for ultrasound-guided paracentesis.⁷ Three bleeding events occurred, an overall event rate of 0.99%. They also found no association between preprocedure platelet count and bleeding risk.

In addition to observational data, one randomized, controlled trial evaluated the effects of FFP and platelet administration on bleeding risk among 60 patients with cirrhosis undergoing invasive procedures, including 19 paracenteses.⁶ Enrollment criteria included INR greater than 1.8 and/or platelet count less than 50,000/μL. One hundred percent of patients randomized to the usual care control arm received platelets or FFP as compared to 17% in the thromboelastography (TEG)–guided transfusion strategy arm. TEG assesses the viscoelastic properties of evolving clot formation in whole blood. Only one patient, a patient in the control arm who received FFP, developed procedure-related bleeding. Although receiving many fewer transfusions, the TEG-guided group experienced no bleeding.

In the presence of multiple studies demonstrating lack of benefit from FFP and platelet transfusion, guidelines published by the American Association for the Study of Liver Disease (AASLD), the American Gastroenterological Association (AGA), and the Society of Interventional Radiology (SIR) acknowledge the inaccuracy of platelet count and INR in predicting bleeding risk.^12-14 Both AASLD and AGA recommend against routine transfusion of platelets and FFP prior to paracentesis.^12,13 SIR guidelines from 2019 recommend against using an INR threshold for low-risk procedures like paracentesis and lowered their recommended platelet transfusion threshold from less than 50,000/μL to less than 20,000/μL.¹⁴ While we have limited safety data for paracentesis in patients with very low platelet counts, Kurup et al observed no bleeding events in the 19 patients in their cohort with platelets less than 20,000/μL undergoing ultrasound-guided paracentesis.⁷

In addition to lack of proven benefit, preprocedure transfusion exposes patients to objective risk. Transfusion-­related acute lung injury and transfusion-associated circulatory overload develop at a rate of 0.48 and 3.8 per 100,000 components transfused, respectively.¹⁵ FFP transfusions also risk anaphylactic reactions with incidence ranging from 1:18,000 to 1:172,000.¹⁶ Platelets carry additional risk of bacterial contamination and resultant sepsis estimated at 1:5,000 to 1:8,000 per unit.¹⁷ Volume expansion from transfusions may contribute to portal hypertension and increase risk of variceal bleeding in decompensated liver disease.

Finally, FFP and platelet transfusions carry a significant cost. Rowley et al estimated eliminating preprocedure transfusions over 2 years and 3,116 paracenteses saved their institution $816,000.⁵ Furthermore, checking and correcting INR and thrombocytopenia can lead to procedural delay. Studies have demonstrated increased mortality from delaying paracentesis.¹⁸

While most patients undergoing paracentesis have cirrhosis, patients without cirrhosis also undergo this procedure. Although several cited studies examined paracentesis among all-comers with ascites, our recommendations specifically apply to patients with ascites from cirrhosis.

Furthermore, although no paracentesis data in patients with severe coagulopathy (INR >2.5 or platelet count <20,000/μL) suggest periprocedural transfusion helps, we also lack data to prove it does not help.

Current recommendations from the AASLD suggest correcting coagulopathy in patients with clinically evident disseminated intravascular coagulation or hyperfibrinolysis prior to procedures.¹² While no clear guidance related to paracentesis exists on when to assess for these entities, we recommend evaluating for them only when the clinical situation otherwise merits doing so and not solely for the purpose of screening prior to paracentesis. Measuring fibrinogen before paracentesis to predict bleeding risk is an emerging concept, but it cannot be routinely recommended at this time.¹³ Other factors that may play an important role in bleeding risk—ultrasound guidance, operator experience, and ability to avoid epigastric vessels and collateral veins—are beyond the scope of this article.

Given that laboratory evaluations like INR and platelet count cannot predict which patients with cirrhosis will experience major bleeding complications after paracentesis and given that routinely transfusing FFP or platelets does not confer benefit and may cause serious harm, providers should avoid measuring INR or platelet count to prepare for paracentesis. Likewise, providers should avoid routinely transfusing FFP and platelets prior to paracentesis even in the presence of abnormal laboratory values because such values do not accurately reflect bleeding risk in patients with cirrhosis. Perform clinically indicated paracentesis without the delays that accompany unnecessary laboratory evaluations or transfusions.

Keep the following in mind with patients presenting with ascites from cirrhosis:

• Do not routinely use platelet count or INR when preparing for paracentesis, whether diagnostic or therapeutic, because no evidence-based “cutoff” for safe performance of paracentesis exists.
• Do not routinely transfuse FFP or platelets for prophylaxis prior to paracentesis in patients with cirrhosis.
• Reserve preprocedure transfusion of FFP or platelets for patients with disseminated intravascular coagulation, hyperfibrinolysis, or other indications for transfusion unrelated to procedural prophylaxis.

Case series representing diverse institutional experiences with thousands of patients consistently demonstrate that bleeding after paracentesis is rare (<1%), mortality from bleeding occurs very infrequently, and neither INR nor platelet counts predict bleeding risk during paracentesis in cirrhosis. These studies demonstrate that abandoning routine correction of coagulopathy does not lead to worse outcomes, can avoid potentially significant transfusion-related adverse events, and can save scarce resources.

Returning to our clinical scenario, the hospitalist should not transfuse FFP or platelets and should not delay the diagnostic paracentesis.

Do you think this is a low-value practice? Is this truly a “Thing We Do for No Reason™”? Share what you do in your practice and join in the conversation online by retweeting it on Twitter (#TWDFNR) and liking it on Facebook. We invite you to propose ideas for other “Things We Do for No Reason™” topics by emailing [email protected].

The authors wish to acknowledge James Burton, MD, H Raymond Tahhan, MD, John Hess, MD, MPH, and Terry Gernsheimer, MD, for directing the authors to useful references cited in the manuscript.

Inspired by the ABIM Foundation’s Choosing Wisely^® campaign, the “Things We Do for No Reason^™” (TWDFNR) series reviews practices that have become common parts of hospital care but may provide little value to our patients. Practices reviewed in the TWDFNR series do not represent clear-cut conclusions or clinical practice standards but are meant as a starting place for research and active discussions among hospitalists and patients. We invite you to be part of that discussion.

The hospitalist admits a 52-year-old man with alcoholic cirrhosis for tense ascites and altered mentation. Home medications include furosemide, spironolactone, lactulose, and rifaximin, but his family notes he ran out last week. Although afebrile and hemodynamically stable, the patient’s coagulopathy, with an international normalized ratio (INR) of 2.3, and thrombocytopenia, with a platelet count of 37,000/μL, worries the hospitalist. The hospitalist wonders whether to transfuse fresh frozen plasma (FFP) and platelets prior to diagnostic paracentesis to reduce the risk of procedural bleeding.

Many patients undergoing paracentesis have severe liver disease and present with both thrombocytopenia and elevated INRs. While platelet count and INR serve as surrogate markers for bleeding risk in many settings, clinicians often extrapolate this concept to patients with cirrhosis. Many hospitalists routinely check INR and platelet count and administer FFP and platelets prior to diagnostic or therapeutic paracentesis to mitigate procedure-related bleeding risk. Some medical resources recommend this practice,¹ while case reports and personal experiences with bleeding in these patients create availability bias that influences perception of bleeding risk.² One recent study of patients with decompensated cirrhosis presenting to a US tertiary care center found that, of those receiving large-­volume paracentesis, 22.2% received prophylactic FFP and 17.3% received prophylactic platelets before paracentesis.³

Advances in our understanding of coagulation in cirrhosis demonstrate neither INR nor platelet count accurately predict bleeding risk in this population. Additionally, evidence demonstrates the overall safety of paracentesis in cirrhosis—even in the presence of high INR and thrombocytopenia—and the lack of benefit from prophylactic transfusions with FFP or platelets.

Substantial evidence in patients with cirrhosis demonstrates that changes in coagulation and platelet function confer a “balanced coagulopathy” in which patients oscillate between hyper- and hypocoagulable states. In a cirrhotic liver, hepatic synthetic dysfunction results in a complex milieu through reduced production and plasma concentrations of both pro- and anticoagulant factors that can lead to either bleeding or clotting.⁴ This “rebalancing” makes prothrombin time (PT) and INR unreliable indicators of bleeding or clotting risk. Similarly, in patients with cirrhosis, thrombocytopenia does not necessarily reflect impaired clotting ability. These patients experience an increase in production of von Willebrand Factor, which may compensate for low platelet counts by producing stronger platelet adhesion to collagen.⁴ Unfortunately, we currently lack a reliable test or risk score to assess true bleeding risk in patients with cirrhosis.

Observational studies support these laboratory findings. Large case series consistently demonstrate no association between INR or platelet counts and bleeding risk in either diagnostic or therapeutic paracentesis, including large-volume paracentesis (See Appendix for a list of recent representative studies).^5-10 Moreover, prophylactic transfusion of FFP or platelets does not significantly reduce bleeding risk.

In a 1991 study by McVay et al, the researchers examined bleeding outcomes of 441 paracenteses performed on hospitalized patients.¹¹ Among patients who did not receive FFP prior to paracentesis, only one required a transfusion for procedure-­related bleeding, an event rate of 0.25%. This single patient had a normal platelet count and an elevated PT to the same extent as 261 others who underwent paracentesis without complication. In a pooled analysis that included 391 paracenteses and 207 thoracenteses, the authors concluded neither PT nor platelet level predicted bleeding risk. Similarly, the largest published case series on this topic examined 4,729 paracenteses over a decade on a liver unit and found low rates of major bleeding (0.19%).⁹ Furthermore, preprocedure INR or platelet count did not correlate with bleeding risk. The authors did not report preprocedure transfusion rates, but they noted transfusions occurred only “occasionally.”

Subsequent observational studies have consistently revealed low bleeding risks even in settings of high coagulopathy prevalence. Grabau et al reviewed all large-volume paracenteses performed in a gastroenterology clinic over 7 years.¹⁰ In over 1,100 procedures, no major bleeding events occurred despite 27% of patients having INR greater than 2.0 and 54% having platelet counts less than 50,000/μL. Kurup et al examined bleeding risk among 304 procedures performed on patients with platelet counts less than 50,000/μL referred to radiology for ultrasound-guided paracentesis.⁷ Three bleeding events occurred, an overall event rate of 0.99%. They also found no association between preprocedure platelet count and bleeding risk.

In addition to observational data, one randomized, controlled trial evaluated the effects of FFP and platelet administration on bleeding risk among 60 patients with cirrhosis undergoing invasive procedures, including 19 paracenteses.⁶ Enrollment criteria included INR greater than 1.8 and/or platelet count less than 50,000/μL. One hundred percent of patients randomized to the usual care control arm received platelets or FFP as compared to 17% in the thromboelastography (TEG)–guided transfusion strategy arm. TEG assesses the viscoelastic properties of evolving clot formation in whole blood. Only one patient, a patient in the control arm who received FFP, developed procedure-related bleeding. Although receiving many fewer transfusions, the TEG-guided group experienced no bleeding.

In the presence of multiple studies demonstrating lack of benefit from FFP and platelet transfusion, guidelines published by the American Association for the Study of Liver Disease (AASLD), the American Gastroenterological Association (AGA), and the Society of Interventional Radiology (SIR) acknowledge the inaccuracy of platelet count and INR in predicting bleeding risk.^12-14 Both AASLD and AGA recommend against routine transfusion of platelets and FFP prior to paracentesis.^12,13 SIR guidelines from 2019 recommend against using an INR threshold for low-risk procedures like paracentesis and lowered their recommended platelet transfusion threshold from less than 50,000/μL to less than 20,000/μL.¹⁴ While we have limited safety data for paracentesis in patients with very low platelet counts, Kurup et al observed no bleeding events in the 19 patients in their cohort with platelets less than 20,000/μL undergoing ultrasound-guided paracentesis.⁷

In addition to lack of proven benefit, preprocedure transfusion exposes patients to objective risk. Transfusion-­related acute lung injury and transfusion-associated circulatory overload develop at a rate of 0.48 and 3.8 per 100,000 components transfused, respectively.¹⁵ FFP transfusions also risk anaphylactic reactions with incidence ranging from 1:18,000 to 1:172,000.¹⁶ Platelets carry additional risk of bacterial contamination and resultant sepsis estimated at 1:5,000 to 1:8,000 per unit.¹⁷ Volume expansion from transfusions may contribute to portal hypertension and increase risk of variceal bleeding in decompensated liver disease.

Finally, FFP and platelet transfusions carry a significant cost. Rowley et al estimated eliminating preprocedure transfusions over 2 years and 3,116 paracenteses saved their institution $816,000.⁵ Furthermore, checking and correcting INR and thrombocytopenia can lead to procedural delay. Studies have demonstrated increased mortality from delaying paracentesis.¹⁸

While most patients undergoing paracentesis have cirrhosis, patients without cirrhosis also undergo this procedure. Although several cited studies examined paracentesis among all-comers with ascites, our recommendations specifically apply to patients with ascites from cirrhosis.

Furthermore, although no paracentesis data in patients with severe coagulopathy (INR >2.5 or platelet count <20,000/μL) suggest periprocedural transfusion helps, we also lack data to prove it does not help.

Current recommendations from the AASLD suggest correcting coagulopathy in patients with clinically evident disseminated intravascular coagulation or hyperfibrinolysis prior to procedures.¹² While no clear guidance related to paracentesis exists on when to assess for these entities, we recommend evaluating for them only when the clinical situation otherwise merits doing so and not solely for the purpose of screening prior to paracentesis. Measuring fibrinogen before paracentesis to predict bleeding risk is an emerging concept, but it cannot be routinely recommended at this time.¹³ Other factors that may play an important role in bleeding risk—ultrasound guidance, operator experience, and ability to avoid epigastric vessels and collateral veins—are beyond the scope of this article.

Given that laboratory evaluations like INR and platelet count cannot predict which patients with cirrhosis will experience major bleeding complications after paracentesis and given that routinely transfusing FFP or platelets does not confer benefit and may cause serious harm, providers should avoid measuring INR or platelet count to prepare for paracentesis. Likewise, providers should avoid routinely transfusing FFP and platelets prior to paracentesis even in the presence of abnormal laboratory values because such values do not accurately reflect bleeding risk in patients with cirrhosis. Perform clinically indicated paracentesis without the delays that accompany unnecessary laboratory evaluations or transfusions.

Keep the following in mind with patients presenting with ascites from cirrhosis:

• Do not routinely use platelet count or INR when preparing for paracentesis, whether diagnostic or therapeutic, because no evidence-based “cutoff” for safe performance of paracentesis exists.
• Do not routinely transfuse FFP or platelets for prophylaxis prior to paracentesis in patients with cirrhosis.
• Reserve preprocedure transfusion of FFP or platelets for patients with disseminated intravascular coagulation, hyperfibrinolysis, or other indications for transfusion unrelated to procedural prophylaxis.

Case series representing diverse institutional experiences with thousands of patients consistently demonstrate that bleeding after paracentesis is rare (<1%), mortality from bleeding occurs very infrequently, and neither INR nor platelet counts predict bleeding risk during paracentesis in cirrhosis. These studies demonstrate that abandoning routine correction of coagulopathy does not lead to worse outcomes, can avoid potentially significant transfusion-related adverse events, and can save scarce resources.

Returning to our clinical scenario, the hospitalist should not transfuse FFP or platelets and should not delay the diagnostic paracentesis.

Do you think this is a low-value practice? Is this truly a “Thing We Do for No Reason™”? Share what you do in your practice and join in the conversation online by retweeting it on Twitter (#TWDFNR) and liking it on Facebook. We invite you to propose ideas for other “Things We Do for No Reason™” topics by emailing [email protected].

The authors wish to acknowledge James Burton, MD, H Raymond Tahhan, MD, John Hess, MD, MPH, and Terry Gernsheimer, MD, for directing the authors to useful references cited in the manuscript.

Inspired by the ABIM Foundation’s Choosing Wisely^® campaign, the “Things We Do for No Reason^™” (TWDFNR) series reviews practices that have become common parts of hospital care but may provide little value to our patients. Practices reviewed in the TWDFNR series do not represent clear-cut conclusions or clinical practice standards but are meant as a starting place for research and active discussions among hospitalists and patients. We invite you to be part of that discussion.

The hospitalist admits a 52-year-old man with alcoholic cirrhosis for tense ascites and altered mentation. Home medications include furosemide, spironolactone, lactulose, and rifaximin, but his family notes he ran out last week. Although afebrile and hemodynamically stable, the patient’s coagulopathy, with an international normalized ratio (INR) of 2.3, and thrombocytopenia, with a platelet count of 37,000/μL, worries the hospitalist. The hospitalist wonders whether to transfuse fresh frozen plasma (FFP) and platelets prior to diagnostic paracentesis to reduce the risk of procedural bleeding.

Many patients undergoing paracentesis have severe liver disease and present with both thrombocytopenia and elevated INRs. While platelet count and INR serve as surrogate markers for bleeding risk in many settings, clinicians often extrapolate this concept to patients with cirrhosis. Many hospitalists routinely check INR and platelet count and administer FFP and platelets prior to diagnostic or therapeutic paracentesis to mitigate procedure-related bleeding risk. Some medical resources recommend this practice,¹ while case reports and personal experiences with bleeding in these patients create availability bias that influences perception of bleeding risk.² One recent study of patients with decompensated cirrhosis presenting to a US tertiary care center found that, of those receiving large-­volume paracentesis, 22.2% received prophylactic FFP and 17.3% received prophylactic platelets before paracentesis.³

Advances in our understanding of coagulation in cirrhosis demonstrate neither INR nor platelet count accurately predict bleeding risk in this population. Additionally, evidence demonstrates the overall safety of paracentesis in cirrhosis—even in the presence of high INR and thrombocytopenia—and the lack of benefit from prophylactic transfusions with FFP or platelets.

Substantial evidence in patients with cirrhosis demonstrates that changes in coagulation and platelet function confer a “balanced coagulopathy” in which patients oscillate between hyper- and hypocoagulable states. In a cirrhotic liver, hepatic synthetic dysfunction results in a complex milieu through reduced production and plasma concentrations of both pro- and anticoagulant factors that can lead to either bleeding or clotting.⁴ This “rebalancing” makes prothrombin time (PT) and INR unreliable indicators of bleeding or clotting risk. Similarly, in patients with cirrhosis, thrombocytopenia does not necessarily reflect impaired clotting ability. These patients experience an increase in production of von Willebrand Factor, which may compensate for low platelet counts by producing stronger platelet adhesion to collagen.⁴ Unfortunately, we currently lack a reliable test or risk score to assess true bleeding risk in patients with cirrhosis.

Observational studies support these laboratory findings. Large case series consistently demonstrate no association between INR or platelet counts and bleeding risk in either diagnostic or therapeutic paracentesis, including large-volume paracentesis (See Appendix for a list of recent representative studies).^5-10 Moreover, prophylactic transfusion of FFP or platelets does not significantly reduce bleeding risk.

In a 1991 study by McVay et al, the researchers examined bleeding outcomes of 441 paracenteses performed on hospitalized patients.¹¹ Among patients who did not receive FFP prior to paracentesis, only one required a transfusion for procedure-­related bleeding, an event rate of 0.25%. This single patient had a normal platelet count and an elevated PT to the same extent as 261 others who underwent paracentesis without complication. In a pooled analysis that included 391 paracenteses and 207 thoracenteses, the authors concluded neither PT nor platelet level predicted bleeding risk. Similarly, the largest published case series on this topic examined 4,729 paracenteses over a decade on a liver unit and found low rates of major bleeding (0.19%).⁹ Furthermore, preprocedure INR or platelet count did not correlate with bleeding risk. The authors did not report preprocedure transfusion rates, but they noted transfusions occurred only “occasionally.”

Subsequent observational studies have consistently revealed low bleeding risks even in settings of high coagulopathy prevalence. Grabau et al reviewed all large-volume paracenteses performed in a gastroenterology clinic over 7 years.¹⁰ In over 1,100 procedures, no major bleeding events occurred despite 27% of patients having INR greater than 2.0 and 54% having platelet counts less than 50,000/μL. Kurup et al examined bleeding risk among 304 procedures performed on patients with platelet counts less than 50,000/μL referred to radiology for ultrasound-guided paracentesis.⁷ Three bleeding events occurred, an overall event rate of 0.99%. They also found no association between preprocedure platelet count and bleeding risk.

In addition to observational data, one randomized, controlled trial evaluated the effects of FFP and platelet administration on bleeding risk among 60 patients with cirrhosis undergoing invasive procedures, including 19 paracenteses.⁶ Enrollment criteria included INR greater than 1.8 and/or platelet count less than 50,000/μL. One hundred percent of patients randomized to the usual care control arm received platelets or FFP as compared to 17% in the thromboelastography (TEG)–guided transfusion strategy arm. TEG assesses the viscoelastic properties of evolving clot formation in whole blood. Only one patient, a patient in the control arm who received FFP, developed procedure-related bleeding. Although receiving many fewer transfusions, the TEG-guided group experienced no bleeding.

In the presence of multiple studies demonstrating lack of benefit from FFP and platelet transfusion, guidelines published by the American Association for the Study of Liver Disease (AASLD), the American Gastroenterological Association (AGA), and the Society of Interventional Radiology (SIR) acknowledge the inaccuracy of platelet count and INR in predicting bleeding risk.^12-14 Both AASLD and AGA recommend against routine transfusion of platelets and FFP prior to paracentesis.^12,13 SIR guidelines from 2019 recommend against using an INR threshold for low-risk procedures like paracentesis and lowered their recommended platelet transfusion threshold from less than 50,000/μL to less than 20,000/μL.¹⁴ While we have limited safety data for paracentesis in patients with very low platelet counts, Kurup et al observed no bleeding events in the 19 patients in their cohort with platelets less than 20,000/μL undergoing ultrasound-guided paracentesis.⁷

In addition to lack of proven benefit, preprocedure transfusion exposes patients to objective risk. Transfusion-­related acute lung injury and transfusion-associated circulatory overload develop at a rate of 0.48 and 3.8 per 100,000 components transfused, respectively.¹⁵ FFP transfusions also risk anaphylactic reactions with incidence ranging from 1:18,000 to 1:172,000.¹⁶ Platelets carry additional risk of bacterial contamination and resultant sepsis estimated at 1:5,000 to 1:8,000 per unit.¹⁷ Volume expansion from transfusions may contribute to portal hypertension and increase risk of variceal bleeding in decompensated liver disease.

Finally, FFP and platelet transfusions carry a significant cost. Rowley et al estimated eliminating preprocedure transfusions over 2 years and 3,116 paracenteses saved their institution $816,000.⁵ Furthermore, checking and correcting INR and thrombocytopenia can lead to procedural delay. Studies have demonstrated increased mortality from delaying paracentesis.¹⁸

While most patients undergoing paracentesis have cirrhosis, patients without cirrhosis also undergo this procedure. Although several cited studies examined paracentesis among all-comers with ascites, our recommendations specifically apply to patients with ascites from cirrhosis.

Furthermore, although no paracentesis data in patients with severe coagulopathy (INR >2.5 or platelet count <20,000/μL) suggest periprocedural transfusion helps, we also lack data to prove it does not help.

Current recommendations from the AASLD suggest correcting coagulopathy in patients with clinically evident disseminated intravascular coagulation or hyperfibrinolysis prior to procedures.¹² While no clear guidance related to paracentesis exists on when to assess for these entities, we recommend evaluating for them only when the clinical situation otherwise merits doing so and not solely for the purpose of screening prior to paracentesis. Measuring fibrinogen before paracentesis to predict bleeding risk is an emerging concept, but it cannot be routinely recommended at this time.¹³ Other factors that may play an important role in bleeding risk—ultrasound guidance, operator experience, and ability to avoid epigastric vessels and collateral veins—are beyond the scope of this article.

Given that laboratory evaluations like INR and platelet count cannot predict which patients with cirrhosis will experience major bleeding complications after paracentesis and given that routinely transfusing FFP or platelets does not confer benefit and may cause serious harm, providers should avoid measuring INR or platelet count to prepare for paracentesis. Likewise, providers should avoid routinely transfusing FFP and platelets prior to paracentesis even in the presence of abnormal laboratory values because such values do not accurately reflect bleeding risk in patients with cirrhosis. Perform clinically indicated paracentesis without the delays that accompany unnecessary laboratory evaluations or transfusions.

Keep the following in mind with patients presenting with ascites from cirrhosis:

• Do not routinely use platelet count or INR when preparing for paracentesis, whether diagnostic or therapeutic, because no evidence-based “cutoff” for safe performance of paracentesis exists.
• Do not routinely transfuse FFP or platelets for prophylaxis prior to paracentesis in patients with cirrhosis.
• Reserve preprocedure transfusion of FFP or platelets for patients with disseminated intravascular coagulation, hyperfibrinolysis, or other indications for transfusion unrelated to procedural prophylaxis.

Case series representing diverse institutional experiences with thousands of patients consistently demonstrate that bleeding after paracentesis is rare (<1%), mortality from bleeding occurs very infrequently, and neither INR nor platelet counts predict bleeding risk during paracentesis in cirrhosis. These studies demonstrate that abandoning routine correction of coagulopathy does not lead to worse outcomes, can avoid potentially significant transfusion-related adverse events, and can save scarce resources.

Returning to our clinical scenario, the hospitalist should not transfuse FFP or platelets and should not delay the diagnostic paracentesis.

Do you think this is a low-value practice? Is this truly a “Thing We Do for No Reason™”? Share what you do in your practice and join in the conversation online by retweeting it on Twitter (#TWDFNR) and liking it on Facebook. We invite you to propose ideas for other “Things We Do for No Reason™” topics by emailing [email protected].

The authors wish to acknowledge James Burton, MD, H Raymond Tahhan, MD, John Hess, MD, MPH, and Terry Gernsheimer, MD, for directing the authors to useful references cited in the manuscript.

Inspired by the ABIM Foundation’s Choosing Wisely^® campaign, the “Things We Do for No Reason^™” (TWDFNR) series reviews practices that have become common parts of hospital care but may provide little value to our patients. Practices reviewed in the TWDFNR series do not represent  clear-cut conclusions or clinical practice standards but are meant as a starting place for research and active discussions among hospitalists and patients. We invite you to be part of that discussion.

An 88-year-old woman with a history of dementia presents to the emergency room with new-onset dyspnea following 2 days of a self-limited gastrointestinal illness associated with nausea, vomiting, and diarrhea. After noting a new supplemental oxygen requirement of 4 L and a temperature of 38.6 °C, the hospitalist’s exam finds an edentulous patient with bibasilar lung crackles and a nontender abdomen. Taking into account her elevated white blood cell count and chest radiograph with right greater than left bibasilar opacities, the admitting hospitalist diagnoses aspiration pneumonia (AP) and specifically selects an antibiotic regimen with anaerobic coverage.

Aspiration, the inhalation of oropharyngeal or gastric materials into the lung, takes one of the following three forms: (1) “microaspiration,” wherein a small number of virulent organisms from oropharynx gains entry into the alveoli, (2) “macroaspiration,” wherein a large volume of typically less virulent organisms gains entry into the airways, or (3) a combination of the two. Hospitalists may struggle to distinguish unwitnessed macroaspiration causing AP from other typical causes of pneumonia, such as community-acquired pneumonia (CAP) or hospital-acquired pneumonia (HAP).¹ A hospitalist should suspect macroaspiration—the most common cause of AP—in patients with risk factors such as dysphagia, diminished cough reflex or impaired swallowing, and infiltrates in the dependent bronchopulmonary segments, or of course, in cases of witnessed aspiration.²

Moreover, hospitalists must differentiate AP, an infectious entity, from aspiration pneumonitis, a noninfectious entity caused by macroaspiration of mostly sterile gastric content. Aspiration pneumonitis presents with acute lung injury within hours of an aspiration event, whereas AP entails a gradual onset of symptoms and signs of pneumonia.² Although aspiration pneumonitis can present dramatically with hypoxemia and pulmonary edema and may evolve into AP, patients do not initially benefit from empiric antibiotics.¹

In the 1970s, several studies of patients who were presumed to have AP because of risk factors for macroaspiration, such as alcohol use disorder, illicit drug use, and seizure disorder, identified anaerobes as major etiologic pathogens. These studies reported the presence of putrid sputum and obtained samples through invasive methods (eg, transtracheal aspirates, thoracentesis, and blood cultures).^3,4 Many of the patients studied had radiographic findings of pleuropulmonary disease. For example, in the study by Bartlett et al, 70% of patients had radiographic evidence of abscess or pulmonary necrosis. These findings led to the assumption that anaerobes play a significant role in all cases of aspiration-related pulmonary syndromes. Because anaerobic bacteria live in the gingival sulcus, with an especially high burden in dental plaques, their role as a potential pathogen in AP may seem logical.⁵ Given the backdrop of those concerns, Kioka et al found that providers treated 90% of presumed AP patients in the intensive care unit with antibiotics that have anaerobic activity despite only 30% meeting the criteria for anaerobic coverage.⁶

In contrast to the population of patients with AP described from the 1970s, we now diagnose AP more frequently in nursing home residents, the elderly with cognitive impairment, and those with tube feed dependence, dysphagia, or gastrointestinal motility disorders.¹ Concurrent with this change in the epidemiology of AP, we have witnessed a shift in recovered bacteria from anaerobes to aerobes in recent studies.^7,8 In an intensive care unit study from 1999, respiratory tract organisms of patients with suspected aspiration mirrored those of patients with CAP or HAP.⁹ In a systematic review of eight observational studies that included studies from 1993 to 2014 and involved elderly patients with uncomplicated AP, only two out of eight studies demonstrated the presence of anaerobes in respiratory cultures. Even in those two studies, anaerobic bacteria frequently coexisted with aerobes. The majority of organisms in all eight studies consisted of aerobic gram-positives, gram-negatives, or both.¹⁰

A study by El-Solh et al most frequently isolated pathogenic aerobic gram-negative bacteria (49% of cases), followed by anaerobic bacteria (16%), among institutionalized elderly patients with severe AP diagnosed by clinical features. In that same study, most anaerobes coexisted with aerobic gram-negative bacteria, and the clinical illness promptly resolved in the absence of specific anaerobic coverage.¹¹ AP can be successfully treated without anaerobic coverage due to a variety of factors: the insignificant role of anaerobes in the pathogenesis of uncomplicated AP, lower severity of illness in the absence of abscesses or pulmonary necrosis (uncomplicated), and altered local redox-potential from the elimination of aerobic pathogens, which effectively also treats anaerobes.¹ Moreover, anaerobes possess generally less virulence in comparison with aerobes. AP from these organisms typically requires risk for excessive oral growth (eg, periodontal disease) and macroaspiration of a large number of organisms.⁵

There are also potential harms associated with the unnecessary treatment of anaerobic bacteria. Since anaerobes account for the majority of the bacteria present in the bowel, targeting anaerobes can result in gut dysbiosis.¹ Moreover, a prospective study showed an increase in the incidence of vancomycin-resistant enterococci and antibiotic-resistant gram-negative bacteria associated with the empiric use of antibiotics with anaerobic activity.¹² Finally, a systematic review detailed the high incidence of Clostridioides difficile infections among patients receiving clindamycin and carbapenems.¹³

Despite the predominance of aerobic organisms in the respiratory tract specimens of patients diagnosed with AP in the current era, situations still exist that require treatment of anaerobes. These include necrotizing pneumonia, empyema, or lung abscess.² Additionally, patients with severe periodontal disease may harbor anaerobic bacteria such as Bacteroides species, Peptostreptococcus species, and Actinomyces israelii.⁵ When we suspect macroaspiration leading to AP, patients with severe periodontal disease may benefit from anaerobic coverage. Putrid sputum generation may indicate the presence of anaerobic organisms that produce the characteristic foul odor of short-chain volatile fatty acids observed in patients with lung abscess or empyema.² It often takes about 8 to 14 days after an aspiration event for lung cavitation or empyema to develop.¹⁴ Therefore, a longer duration of illness or putrid sputum production may signal a significant concurrent burden of anaerobes. The 2019 official guidelines of the American Thoracic Society and Infectious Disease Society of America recommend adding anaerobic coverage to CAP only when empyema or lung abscess is suspected (conditional recommendation, very low quality of evidence).¹⁵

When you suspect AP in a patient, categorize it as either community or hospital acquired based on risk factors similar to CAP or HAP. For patients with witnessed macroaspiration or in patients with substantial macroaspiration risk factors, perform a radiologic evaluation and a thorough oral examination to evaluate for poor dentition, gingival disease (marked redness, tendency to bleed, ulceration), and tongue coating. For patients presenting from the community with suspected AP without complications, treat with the standard therapy (without additional anaerobic coverage) for CAP. Provide empiric anaerobic coverage for complicated AP (eg, lung abscess, necrosis, or empyema) or for macroaspiration in the setting of severe periodontal disease, putrid sputum, or longer duration of illness. Similarly, treat hospital-acquired AP as HAP (Figure).

When prescribing anaerobic coverage of AP, use combination drugs that include a ß-lactamase inhibitor (eg, ampicillin-sulbactam), clindamycin (either alone or in combination with ß-lactams), or moxifloxacin.¹ Most anaerobes have ß-lactamase or cephalosporinase activity, which renders penicillin and cephalosporins ineffective. Despite its potential side effects, such as C difficile infection, treating with clindamycin has the benefit of a relatively low cost and its association with lower rates of methicillin-resistant Staphylococcus aureus emergence after treatment.¹⁶ Piperacillin-tazobactam and carbapenems also have excellent anaerobic coverage, but we should reserve them for more severe and complicated cases of AP given their extensive antibacterial activity and concern for the emergence of resistance.⁸ Although well known and used for decades for its activity against clinically important anaerobes, avoid metronidazole due to its reduced cure rate in lung abscess caused by microaerophilic streptococci of the oral cavity.¹⁷ Due to a lack of evidence, we do not recommend the use of metronidazole in lung infections.

• Empirically treat most suspected cases of AP with regimens similar to the standard antibiotics for CAP and HAP. In the absence of specific risk factors for anaerobic infections, do not routinely provide anaerobic coverage.
• Provide anaerobic coverage empirically for AP associated with macroaspiration in the setting of severe periodontal disease, putrid sputum, or longer duration of illness.
• Provide anaerobic coverage in AP with evidence of necrotizing pneumonia, empyema, or lung abscess.

Current evidence does not support routine anaerobic coverage of AP in the absence of identifiable risk factors for an anaerobic lung infection.

In consideration of the clinical case, importantly, she has no periodontal disease and no evidence for necrotizing pneumonia, empyema, or lung abscess radiographically. For these reasons, select an empiric antibiotic regime that targets CAP organisms predominantly and forgo additional anaerobic coverage.

Do you think this is a low-value practice? Is this truly a “Thing We Do for No Reason ^™ ”? Share what you do in your practice and join in the conversation online by retweeting it on Twitter (#TWDFNR) and liking it on Facebook. We invite you to propose ideas for other “Things We Do for No Reason ^™ ” topics by emailing [email protected].

The authors have no conflicts of interest relevant to this article.

Inspired by the ABIM Foundation’s Choosing Wisely^® campaign, the “Things We Do for No Reason^™” (TWDFNR) series reviews practices that have become common parts of hospital care but may provide little value to our patients. Practices reviewed in the TWDFNR series do not represent  clear-cut conclusions or clinical practice standards but are meant as a starting place for research and active discussions among hospitalists and patients. We invite you to be part of that discussion.

An 88-year-old woman with a history of dementia presents to the emergency room with new-onset dyspnea following 2 days of a self-limited gastrointestinal illness associated with nausea, vomiting, and diarrhea. After noting a new supplemental oxygen requirement of 4 L and a temperature of 38.6 °C, the hospitalist’s exam finds an edentulous patient with bibasilar lung crackles and a nontender abdomen. Taking into account her elevated white blood cell count and chest radiograph with right greater than left bibasilar opacities, the admitting hospitalist diagnoses aspiration pneumonia (AP) and specifically selects an antibiotic regimen with anaerobic coverage.

Aspiration, the inhalation of oropharyngeal or gastric materials into the lung, takes one of the following three forms: (1) “microaspiration,” wherein a small number of virulent organisms from oropharynx gains entry into the alveoli, (2) “macroaspiration,” wherein a large volume of typically less virulent organisms gains entry into the airways, or (3) a combination of the two. Hospitalists may struggle to distinguish unwitnessed macroaspiration causing AP from other typical causes of pneumonia, such as community-acquired pneumonia (CAP) or hospital-acquired pneumonia (HAP).¹ A hospitalist should suspect macroaspiration—the most common cause of AP—in patients with risk factors such as dysphagia, diminished cough reflex or impaired swallowing, and infiltrates in the dependent bronchopulmonary segments, or of course, in cases of witnessed aspiration.²

Moreover, hospitalists must differentiate AP, an infectious entity, from aspiration pneumonitis, a noninfectious entity caused by macroaspiration of mostly sterile gastric content. Aspiration pneumonitis presents with acute lung injury within hours of an aspiration event, whereas AP entails a gradual onset of symptoms and signs of pneumonia.² Although aspiration pneumonitis can present dramatically with hypoxemia and pulmonary edema and may evolve into AP, patients do not initially benefit from empiric antibiotics.¹

In the 1970s, several studies of patients who were presumed to have AP because of risk factors for macroaspiration, such as alcohol use disorder, illicit drug use, and seizure disorder, identified anaerobes as major etiologic pathogens. These studies reported the presence of putrid sputum and obtained samples through invasive methods (eg, transtracheal aspirates, thoracentesis, and blood cultures).^3,4 Many of the patients studied had radiographic findings of pleuropulmonary disease. For example, in the study by Bartlett et al, 70% of patients had radiographic evidence of abscess or pulmonary necrosis. These findings led to the assumption that anaerobes play a significant role in all cases of aspiration-related pulmonary syndromes. Because anaerobic bacteria live in the gingival sulcus, with an especially high burden in dental plaques, their role as a potential pathogen in AP may seem logical.⁵ Given the backdrop of those concerns, Kioka et al found that providers treated 90% of presumed AP patients in the intensive care unit with antibiotics that have anaerobic activity despite only 30% meeting the criteria for anaerobic coverage.⁶

In contrast to the population of patients with AP described from the 1970s, we now diagnose AP more frequently in nursing home residents, the elderly with cognitive impairment, and those with tube feed dependence, dysphagia, or gastrointestinal motility disorders.¹ Concurrent with this change in the epidemiology of AP, we have witnessed a shift in recovered bacteria from anaerobes to aerobes in recent studies.^7,8 In an intensive care unit study from 1999, respiratory tract organisms of patients with suspected aspiration mirrored those of patients with CAP or HAP.⁹ In a systematic review of eight observational studies that included studies from 1993 to 2014 and involved elderly patients with uncomplicated AP, only two out of eight studies demonstrated the presence of anaerobes in respiratory cultures. Even in those two studies, anaerobic bacteria frequently coexisted with aerobes. The majority of organisms in all eight studies consisted of aerobic gram-positives, gram-negatives, or both.¹⁰

A study by El-Solh et al most frequently isolated pathogenic aerobic gram-negative bacteria (49% of cases), followed by anaerobic bacteria (16%), among institutionalized elderly patients with severe AP diagnosed by clinical features. In that same study, most anaerobes coexisted with aerobic gram-negative bacteria, and the clinical illness promptly resolved in the absence of specific anaerobic coverage.¹¹ AP can be successfully treated without anaerobic coverage due to a variety of factors: the insignificant role of anaerobes in the pathogenesis of uncomplicated AP, lower severity of illness in the absence of abscesses or pulmonary necrosis (uncomplicated), and altered local redox-potential from the elimination of aerobic pathogens, which effectively also treats anaerobes.¹ Moreover, anaerobes possess generally less virulence in comparison with aerobes. AP from these organisms typically requires risk for excessive oral growth (eg, periodontal disease) and macroaspiration of a large number of organisms.⁵

There are also potential harms associated with the unnecessary treatment of anaerobic bacteria. Since anaerobes account for the majority of the bacteria present in the bowel, targeting anaerobes can result in gut dysbiosis.¹ Moreover, a prospective study showed an increase in the incidence of vancomycin-resistant enterococci and antibiotic-resistant gram-negative bacteria associated with the empiric use of antibiotics with anaerobic activity.¹² Finally, a systematic review detailed the high incidence of Clostridioides difficile infections among patients receiving clindamycin and carbapenems.¹³

Despite the predominance of aerobic organisms in the respiratory tract specimens of patients diagnosed with AP in the current era, situations still exist that require treatment of anaerobes. These include necrotizing pneumonia, empyema, or lung abscess.² Additionally, patients with severe periodontal disease may harbor anaerobic bacteria such as Bacteroides species, Peptostreptococcus species, and Actinomyces israelii.⁵ When we suspect macroaspiration leading to AP, patients with severe periodontal disease may benefit from anaerobic coverage. Putrid sputum generation may indicate the presence of anaerobic organisms that produce the characteristic foul odor of short-chain volatile fatty acids observed in patients with lung abscess or empyema.² It often takes about 8 to 14 days after an aspiration event for lung cavitation or empyema to develop.¹⁴ Therefore, a longer duration of illness or putrid sputum production may signal a significant concurrent burden of anaerobes. The 2019 official guidelines of the American Thoracic Society and Infectious Disease Society of America recommend adding anaerobic coverage to CAP only when empyema or lung abscess is suspected (conditional recommendation, very low quality of evidence).¹⁵

When you suspect AP in a patient, categorize it as either community or hospital acquired based on risk factors similar to CAP or HAP. For patients with witnessed macroaspiration or in patients with substantial macroaspiration risk factors, perform a radiologic evaluation and a thorough oral examination to evaluate for poor dentition, gingival disease (marked redness, tendency to bleed, ulceration), and tongue coating. For patients presenting from the community with suspected AP without complications, treat with the standard therapy (without additional anaerobic coverage) for CAP. Provide empiric anaerobic coverage for complicated AP (eg, lung abscess, necrosis, or empyema) or for macroaspiration in the setting of severe periodontal disease, putrid sputum, or longer duration of illness. Similarly, treat hospital-acquired AP as HAP (Figure).

When prescribing anaerobic coverage of AP, use combination drugs that include a ß-lactamase inhibitor (eg, ampicillin-sulbactam), clindamycin (either alone or in combination with ß-lactams), or moxifloxacin.¹ Most anaerobes have ß-lactamase or cephalosporinase activity, which renders penicillin and cephalosporins ineffective. Despite its potential side effects, such as C difficile infection, treating with clindamycin has the benefit of a relatively low cost and its association with lower rates of methicillin-resistant Staphylococcus aureus emergence after treatment.¹⁶ Piperacillin-tazobactam and carbapenems also have excellent anaerobic coverage, but we should reserve them for more severe and complicated cases of AP given their extensive antibacterial activity and concern for the emergence of resistance.⁸ Although well known and used for decades for its activity against clinically important anaerobes, avoid metronidazole due to its reduced cure rate in lung abscess caused by microaerophilic streptococci of the oral cavity.¹⁷ Due to a lack of evidence, we do not recommend the use of metronidazole in lung infections.

• Empirically treat most suspected cases of AP with regimens similar to the standard antibiotics for CAP and HAP. In the absence of specific risk factors for anaerobic infections, do not routinely provide anaerobic coverage.
• Provide anaerobic coverage empirically for AP associated with macroaspiration in the setting of severe periodontal disease, putrid sputum, or longer duration of illness.
• Provide anaerobic coverage in AP with evidence of necrotizing pneumonia, empyema, or lung abscess.

Current evidence does not support routine anaerobic coverage of AP in the absence of identifiable risk factors for an anaerobic lung infection.

In consideration of the clinical case, importantly, she has no periodontal disease and no evidence for necrotizing pneumonia, empyema, or lung abscess radiographically. For these reasons, select an empiric antibiotic regime that targets CAP organisms predominantly and forgo additional anaerobic coverage.

Do you think this is a low-value practice? Is this truly a “Thing We Do for No Reason ^™ ”? Share what you do in your practice and join in the conversation online by retweeting it on Twitter (#TWDFNR) and liking it on Facebook. We invite you to propose ideas for other “Things We Do for No Reason ^™ ” topics by emailing [email protected].

The authors have no conflicts of interest relevant to this article.

Inspired by the ABIM Foundation’s Choosing Wisely^® campaign, the “Things We Do for No Reason^™” (TWDFNR) series reviews practices that have become common parts of hospital care but may provide little value to our patients. Practices reviewed in the TWDFNR series do not represent  clear-cut conclusions or clinical practice standards but are meant as a starting place for research and active discussions among hospitalists and patients. We invite you to be part of that discussion.

An 88-year-old woman with a history of dementia presents to the emergency room with new-onset dyspnea following 2 days of a self-limited gastrointestinal illness associated with nausea, vomiting, and diarrhea. After noting a new supplemental oxygen requirement of 4 L and a temperature of 38.6 °C, the hospitalist’s exam finds an edentulous patient with bibasilar lung crackles and a nontender abdomen. Taking into account her elevated white blood cell count and chest radiograph with right greater than left bibasilar opacities, the admitting hospitalist diagnoses aspiration pneumonia (AP) and specifically selects an antibiotic regimen with anaerobic coverage.

Aspiration, the inhalation of oropharyngeal or gastric materials into the lung, takes one of the following three forms: (1) “microaspiration,” wherein a small number of virulent organisms from oropharynx gains entry into the alveoli, (2) “macroaspiration,” wherein a large volume of typically less virulent organisms gains entry into the airways, or (3) a combination of the two. Hospitalists may struggle to distinguish unwitnessed macroaspiration causing AP from other typical causes of pneumonia, such as community-acquired pneumonia (CAP) or hospital-acquired pneumonia (HAP).¹ A hospitalist should suspect macroaspiration—the most common cause of AP—in patients with risk factors such as dysphagia, diminished cough reflex or impaired swallowing, and infiltrates in the dependent bronchopulmonary segments, or of course, in cases of witnessed aspiration.²

Moreover, hospitalists must differentiate AP, an infectious entity, from aspiration pneumonitis, a noninfectious entity caused by macroaspiration of mostly sterile gastric content. Aspiration pneumonitis presents with acute lung injury within hours of an aspiration event, whereas AP entails a gradual onset of symptoms and signs of pneumonia.² Although aspiration pneumonitis can present dramatically with hypoxemia and pulmonary edema and may evolve into AP, patients do not initially benefit from empiric antibiotics.¹

In the 1970s, several studies of patients who were presumed to have AP because of risk factors for macroaspiration, such as alcohol use disorder, illicit drug use, and seizure disorder, identified anaerobes as major etiologic pathogens. These studies reported the presence of putrid sputum and obtained samples through invasive methods (eg, transtracheal aspirates, thoracentesis, and blood cultures).^3,4 Many of the patients studied had radiographic findings of pleuropulmonary disease. For example, in the study by Bartlett et al, 70% of patients had radiographic evidence of abscess or pulmonary necrosis. These findings led to the assumption that anaerobes play a significant role in all cases of aspiration-related pulmonary syndromes. Because anaerobic bacteria live in the gingival sulcus, with an especially high burden in dental plaques, their role as a potential pathogen in AP may seem logical.⁵ Given the backdrop of those concerns, Kioka et al found that providers treated 90% of presumed AP patients in the intensive care unit with antibiotics that have anaerobic activity despite only 30% meeting the criteria for anaerobic coverage.⁶

In contrast to the population of patients with AP described from the 1970s, we now diagnose AP more frequently in nursing home residents, the elderly with cognitive impairment, and those with tube feed dependence, dysphagia, or gastrointestinal motility disorders.¹ Concurrent with this change in the epidemiology of AP, we have witnessed a shift in recovered bacteria from anaerobes to aerobes in recent studies.^7,8 In an intensive care unit study from 1999, respiratory tract organisms of patients with suspected aspiration mirrored those of patients with CAP or HAP.⁹ In a systematic review of eight observational studies that included studies from 1993 to 2014 and involved elderly patients with uncomplicated AP, only two out of eight studies demonstrated the presence of anaerobes in respiratory cultures. Even in those two studies, anaerobic bacteria frequently coexisted with aerobes. The majority of organisms in all eight studies consisted of aerobic gram-positives, gram-negatives, or both.¹⁰

A study by El-Solh et al most frequently isolated pathogenic aerobic gram-negative bacteria (49% of cases), followed by anaerobic bacteria (16%), among institutionalized elderly patients with severe AP diagnosed by clinical features. In that same study, most anaerobes coexisted with aerobic gram-negative bacteria, and the clinical illness promptly resolved in the absence of specific anaerobic coverage.¹¹ AP can be successfully treated without anaerobic coverage due to a variety of factors: the insignificant role of anaerobes in the pathogenesis of uncomplicated AP, lower severity of illness in the absence of abscesses or pulmonary necrosis (uncomplicated), and altered local redox-potential from the elimination of aerobic pathogens, which effectively also treats anaerobes.¹ Moreover, anaerobes possess generally less virulence in comparison with aerobes. AP from these organisms typically requires risk for excessive oral growth (eg, periodontal disease) and macroaspiration of a large number of organisms.⁵

There are also potential harms associated with the unnecessary treatment of anaerobic bacteria. Since anaerobes account for the majority of the bacteria present in the bowel, targeting anaerobes can result in gut dysbiosis.¹ Moreover, a prospective study showed an increase in the incidence of vancomycin-resistant enterococci and antibiotic-resistant gram-negative bacteria associated with the empiric use of antibiotics with anaerobic activity.¹² Finally, a systematic review detailed the high incidence of Clostridioides difficile infections among patients receiving clindamycin and carbapenems.¹³

Despite the predominance of aerobic organisms in the respiratory tract specimens of patients diagnosed with AP in the current era, situations still exist that require treatment of anaerobes. These include necrotizing pneumonia, empyema, or lung abscess.² Additionally, patients with severe periodontal disease may harbor anaerobic bacteria such as Bacteroides species, Peptostreptococcus species, and Actinomyces israelii.⁵ When we suspect macroaspiration leading to AP, patients with severe periodontal disease may benefit from anaerobic coverage. Putrid sputum generation may indicate the presence of anaerobic organisms that produce the characteristic foul odor of short-chain volatile fatty acids observed in patients with lung abscess or empyema.² It often takes about 8 to 14 days after an aspiration event for lung cavitation or empyema to develop.¹⁴ Therefore, a longer duration of illness or putrid sputum production may signal a significant concurrent burden of anaerobes. The 2019 official guidelines of the American Thoracic Society and Infectious Disease Society of America recommend adding anaerobic coverage to CAP only when empyema or lung abscess is suspected (conditional recommendation, very low quality of evidence).¹⁵

When you suspect AP in a patient, categorize it as either community or hospital acquired based on risk factors similar to CAP or HAP. For patients with witnessed macroaspiration or in patients with substantial macroaspiration risk factors, perform a radiologic evaluation and a thorough oral examination to evaluate for poor dentition, gingival disease (marked redness, tendency to bleed, ulceration), and tongue coating. For patients presenting from the community with suspected AP without complications, treat with the standard therapy (without additional anaerobic coverage) for CAP. Provide empiric anaerobic coverage for complicated AP (eg, lung abscess, necrosis, or empyema) or for macroaspiration in the setting of severe periodontal disease, putrid sputum, or longer duration of illness. Similarly, treat hospital-acquired AP as HAP (Figure).

When prescribing anaerobic coverage of AP, use combination drugs that include a ß-lactamase inhibitor (eg, ampicillin-sulbactam), clindamycin (either alone or in combination with ß-lactams), or moxifloxacin.¹ Most anaerobes have ß-lactamase or cephalosporinase activity, which renders penicillin and cephalosporins ineffective. Despite its potential side effects, such as C difficile infection, treating with clindamycin has the benefit of a relatively low cost and its association with lower rates of methicillin-resistant Staphylococcus aureus emergence after treatment.¹⁶ Piperacillin-tazobactam and carbapenems also have excellent anaerobic coverage, but we should reserve them for more severe and complicated cases of AP given their extensive antibacterial activity and concern for the emergence of resistance.⁸ Although well known and used for decades for its activity against clinically important anaerobes, avoid metronidazole due to its reduced cure rate in lung abscess caused by microaerophilic streptococci of the oral cavity.¹⁷ Due to a lack of evidence, we do not recommend the use of metronidazole in lung infections.

• Empirically treat most suspected cases of AP with regimens similar to the standard antibiotics for CAP and HAP. In the absence of specific risk factors for anaerobic infections, do not routinely provide anaerobic coverage.
• Provide anaerobic coverage empirically for AP associated with macroaspiration in the setting of severe periodontal disease, putrid sputum, or longer duration of illness.
• Provide anaerobic coverage in AP with evidence of necrotizing pneumonia, empyema, or lung abscess.

Current evidence does not support routine anaerobic coverage of AP in the absence of identifiable risk factors for an anaerobic lung infection.

In consideration of the clinical case, importantly, she has no periodontal disease and no evidence for necrotizing pneumonia, empyema, or lung abscess radiographically. For these reasons, select an empiric antibiotic regime that targets CAP organisms predominantly and forgo additional anaerobic coverage.

Do you think this is a low-value practice? Is this truly a “Thing We Do for No Reason ^™ ”? Share what you do in your practice and join in the conversation online by retweeting it on Twitter (#TWDFNR) and liking it on Facebook. We invite you to propose ideas for other “Things We Do for No Reason ^™ ” topics by emailing [email protected].

The authors have no conflicts of interest relevant to this article.

A 64-year-old man presented with a 2-month history of a nonproductive cough, weight loss, and subjective fevers. He had no chest pain, hemoptysis, or shortness of breath. He also described worsening anorexia and a 15-pound weight loss over the previous 3 months. He had no arthralgias, myalgias, abdominal pain, nausea, emesis, or diarrhea.

Two weeks prior to his presentation, he was diagnosed with pneumonia and given a 5-day course of azithromycin. His symptoms did not improve, so he presented to the emergency room. 

He had not been seen regularly by a physician in decades and had no known medical conditions. He did not take any medications. He immigrated from China 3 years prior and lived with his wife in California. He had a 30 pack-year smoking history. He drank a shot glass of liquor daily and denied any drug use.

Weight loss might result from inflammatory disorders like cancer or noninflammatory causes such as decreased oral intake (eg, diminished appetite) or malabsorption (eg, celiac disease). However, his fevers suggest inflammation, which usually reflects an underlying infection, cancer, or autoimmune process. While chronic cough typically results from upper airway cough syndrome (allergic or nonallergic rhinitis), gastroesophageal reflux disease, or asthma, it can also point to pathology of the lung, which may be intrinsic (bronchiectasis) or extrinsic (mediastinal mass). The duration of 2 months makes a typical infectious process like pneumococcal pneumonia unlikely. Atypical infections such as tuberculosis, melioidosis, and talaromycosis are possible given his immigration from East Asia, and coccidioidomycosis given his residence in California. He might have undiagnosed medical conditions, such as diabetes, that could be relevant to his current presentation and classify him as immunocompromised. His smoking history prompts consideration of lung cancer.

His temperature was 36.5 ^oC, heart rate 70 beats per minute, blood pressure 118/66 mm Hg, respiratory rate 16 breaths per minute, oxygen saturation 98% on room air, and body mass index 23 kg/m². He was in no acute distress. The findings from the cardiac, lung, abdominal, and neurological exams were normal.

Skin examination found a fixed, symmetric, 5-cm, firm nodule at top of sternum (Figure 1A). In addition, he had two 1-cm, mobile, firm, subcutaneous nodules, one on his anterior left chest and another underneath his right axilla. He also had two 2-cm, erythematous, tender nodules on his left anterior forearm and a 1-cm nodule with a central black plug on the dorsal surface of his right hand (Figure 1B). He did not have any edema.

The white blood cell count was 10,500/mm³ (42% neutrophils, 37% lymphocytes, 16.4% monocytes, and 2.9% eosinophils), hemoglobin was 12.2 g/dL with a mean corpuscular volume of 91 fL, and the platelet count was 441,000/mm³. Basic metabolic panel, aminotransferase, bilirubin, and alkaline phosphatase were within reference ranges. Serum albumin was 3.1 g/dL. Serum total protein was elevated at 8.8 g/dL. Serum calcium was 9.0 mg/dL. Urinalysis results were normal.

The slightly low albumin, mildly elevated platelet count, monocytosis, and normocytic anemia suggest inflammation, although monocytosis might represent a hematologic malignancy like chronic myelomonocytic leukemia (CMML). His subjective fevers and weight loss further corroborate underlying inflammation. What is driving the inflammation? There are two localizing findings: cough and nodular skin lesions.

His lack of dyspnea and normal oxygen saturation, respiratory rate, and lung exam make an extrapulmonary cause of cough such as lymphadenopathy or mediastinal infection possible. The number of nodular skin lesions, wide-spread distribution, and appearance (eg, erythematous, tender) point to either a primary cutaneous disease with systemic manifestations (eg, cutaneous lymphoma) or a systemic disease with cutaneous features (eg, sarcoidosis).

Three categories—inflammatory, infectious, and neoplastic—account for most nodular skin lesions. Usually microscopic evaluation is necessary for definitive diagnosis, though epidemiology, associated symptoms, and characteristics of the nodules help prioritize the differential diagnosis. Tender nodules might reflect a panniculitis; erythema nodosum is the most common type, and while this classically develops on the anterior shins, it may also occur on the forearm. His immigration from China prompts consideration of tuberculosis and cutaneous leishmaniasis. Coccidioidomycosis can lead to inflammation and nodular skin lesions. Other infections such as nontuberculous mycobacteria, nocardiosis, and cryptococcosis may cause disseminated infection with pulmonary and skin manifestations. His smoking puts him at risk of lung cancer, which rarely results in metastatic subcutaneous infiltrates.

A chest radiograph demonstrated a prominent density in the right paratracheal region of the mediastinum with adjacent streaky opacities. A computed tomography scan of the chest with intravenous contrast demonstrated centrilobular emphysematous changes and revealed a 2.6 × 4.7-cm necrotic mass in the anterior chest wall with erosion into the manubrium, a 3.8 × 2.1-cm centrally necrotic soft-tissue mass in the right hilum, a 5-mm left upper-lobe noncalcified solid pulmonary nodule, and prominent subcarinal, paratracheal, hilar, and bilateral supraclavicular lymphadenopathy (Figure 2). 

Flow cytometry of the peripheral blood did not demonstrate a lymphoproliferative disorder. Blood smear demonstrated normal red blood cell, white blood cell, and platelet morphology. HIV antibody was negative. Hemoglobin A1c was 6.1%. Smear microscopy for acid-fast bacilli (AFB) was negative and sputum AFB samples were sent for culture. Bacterial, fungal, and AFB blood cultures were collected and pending. 

Causes of necrotizing pneumonia include liquid (eg, lymphoma) and solid (eg, squamous cell carcinoma) cancers, infections, and noninfectious inflammatory processes such as granulomatosis with polyangiitis (GPA). Given his subacute presentation and extrapulmonary cutaneous manifestations, consideration of mycobacteria, fungi (eg, Coccidioides, Aspergillus, and Cryptococcus), and filamentous bacteria (eg, Nocardia and Actinomyces) is prioritized among the myriad of infections that can cause a lung cavity. His smoking history and centrilobular emphysematous changes are highly suggestive of chronic obstructive pulmonary disease, which puts him at increased risk of bacterial colonization and recurrent pulmonary infections. Tuberculosis is still possible despite three negative AFB-sputa smears given the sensitivity of smear microscopy (with three specimens) is roughly 70% in an immunocompetent host.

The lymphadenopathy likely reflects spread from the necrotic lung mass. The frequency of non-Hodgkin lymphoma increases with age. The results of the peripheral flow cytometry do not exclude the possibility of an aggressive lymphoma with pulmonary and cutaneous manifestations.

The erosive property of the chest wall mass makes an autoimmune process like GPA unlikely. An aggressive and disseminated infection or cancer is most likely. A pathologic process that originated in the lung and then spread to the lymph nodes and skin is more likely than a disorder which started in the skin. It would be unlikely for a primary cutaneous disorder to cause such a well-defined necrotic lung mass. Lung cancer rarely metastasizes to the skin and, instead, preferentially involves the chest. Ultimately, ascertaining what the patient experienced first (ie, respiratory or cutaneous symptoms) will determine where the pathology originated.

Computed tomography scan of the abdomen and pelvis with intravenous contrast demonstrated multiple ill-­defined lytic lesions in the pelvis, including a 12-mm lesion of the left sacral ala and multiple subcentimeter lesions in the medial left iliac bone and superior right acetabulum. In addition, there were two 1-cm, rim-enhancing, hypodense nodules in the subcutaneous fat of the right flank at the level of L5 and the left lower quadrant, respectively. There was also a 2.2 × 1.9-cm faintly rim-enhancing hypodensity within the left iliopsoas muscle belly.

These imaging findings further corroborate a widely metastatic process probably originating in the lung and spreading to the lymph nodes, skin, muscles, and bones. The characterization of lesions as lytic as opposed to blastic is less helpful because many diseases can cause both. It does prompt consideration of multiple myeloma; however, multiple myeloma less commonly manifests with extramedullary plasmacytomas and is less likely given his normal renal function and calcium level. Bone lesions lessen the likelihood of GPA, and his necrotic lung mass makes sarcoidosis unlikely. Atypical infections and cancers are the prime suspect of his multisystemic disease.

There are no data yet to suggest a weakened immune system, which would increase his risk for atypical infections. His chronic lung disease, identified on imaging, is a risk factor for nocardiosis. This gram-positive, weakly acid-fast bacterium can involve any organ, although lung, brain, and skin are most commonly involved. Disseminated nocardiosis can result from a pulmonary or cutaneous site of origin. Mycobacteria; Actinomyces; dimorphic fungi like Histoplasma, Coccidioides, and Blastomyces; and molds such as Aspergillus can also cause disseminated disease with pulmonary, cutaneous, and musculoskeletal manifestations.

While metastases to muscle itself are rare, they can occur with primary lung cancers. Primary lung cancer with extrapulmonary features is feasible. Squamous cell lung cancer is the most likely to cavitate, although it rarely spreads to the skin. An aggressive lymphoma like diffuse large B-cell lymphoma or cutaneous T-cell lymphoma (higher occurrence in Asians) might also explain his constellation of findings. If culture data remain negative, then biopsy of the chest wall mass might be the safest and highest-yield target.

On hospital day 2, the patient developed new-onset severe neck pain. Magnetic resonance imaging of the cervical, thoracic, and lumbar spine revealed multilevel, bony, lytic lesions with notable cortical breakthrough of the C2 and C3 vertebrae into the prevertebral space, as well as epidural extension and paraspinal soft-tissue extension of the thoracic and lumbar vertebral lesions (Figure 3). 

On hospital day 3, the patient reported increased tenderness in his skin nodules with one on his left forearm spontaneously draining purulent fluid. Repeat complete blood count demonstrated a white blood cell count of 12,600/mm³ (45% neutrophils, 43% lymphocytes, 8.4% monocytes, and 4.3% eosinophils), hemoglobin of 16 g/dL, and platelet count of 355,000/mm³.

The erosion into the manubrium and cortical destruction of the cervical spine attests to the aggressiveness of the underlying disease process. Noncutaneous lymphoma and lung cancer are unlikely to have such prominent skin findings; the visceral pathology, necrotizing lung mass, and bone lesions make cutaneous lymphoma less likely. At this point, a disseminated infectious process is most likely. Leading considerations based on his emigration from China and residence in California are tuberculosis and coccidioidomycosis, respectively. Tuberculous spondylitis most commonly involves the lower thoracic and upper lumbar region, and less commonly the cervical spine. His three negative AFB sputa samples further reduce its posttest probability. Ultimately microbiologic data are needed to distinguish between a disseminated fungal process, like coccidioidomycosis, or tuberculosis.

Given the concern for malignancy, a fine needle aspiration of the left supraclavicular lymph node was pursued. This revealed fungal microorganisms morphologically compatible with Coccidioides spp. with a background of necrotizing granulomas and acute inflammation. Fungal blood cultures grew Coccidioides immitis. AFB blood cultures were discontinued due to overgrowth of mold. The Coccidioides immitis antibody immunodiffusion titer was positive at 1:256. 

During the remainder of the hospitalization, the patient was treated with oral fluconazole 800 mg daily. The patient underwent surgical debridement of the manubrium. In addition, given the concern for cervical spine instability, neurosurgery recommended follow-up with interval imaging. Since his discharge from the hospital, the patient continues to take oral fluconazole with resolution of his cutaneous lesions and respiratory symptoms. His titers have incrementally decreased from 1:256 to 1:16 after 8 months of treatment. 

This elderly gentleman from China presented with subacute symptoms and was found to have numerous cutaneous nodules, lymphadenopathy, and diffuse osseous lesions. This multisystem illness posed a diagnostic challenge, forcing our discussant to search for a disease process that could lead to such varied findings. Ultimately, epidemiologic and clinical clues suggested a diagnosis of disseminated coccidioidomycosis, which was later confirmed on lymph node biopsy.

Coccidioides species are important fungal pathogens in the Western Hemisphere. This organism exhibits dimorphism, existing as mycelia (with arthroconidia) in soil and spherules in tissues. Coccidioides spp are endemic to the Southwestern United States, particularly California’s central valley and parts of Arizona; it additionally remains an important pathogen in Mexico, Central America, and South America.¹ Newer epidemiologic studies have raised concerns that the incidence of coccidioidomycosis is increasing and that its geographic range may be more extensive than previously appreciated, with it now being found as far north as Washington state.² 

Coccidioidal infection can take several forms. One-half to two-thirds of infections may be asymptomatic.³ Clinically significant infections can include an acute self-limiting respiratory illness, pulmonary nodules and cavities, chronic fibrocavitary pneumonia, and infections with extrapulmonary dissemination. Early respiratory infection is often indistinguishable from typical community-acquired pneumonia (10%-15% of pneumonia in endemic areas) but can be associated with certain suggestive features, such as erythema nodosum, erythema multiforme, prominent arthralgias (ie, “desert rheumatism”), and a peripheral eosinophilia.^4,5 

Extrapulmonary dissemination is rare and most commonly associated with immunocompromising states.⁶ However, individuals of African or Filipino ancestry also appear to be at increased risk for disseminated disease, which led to a California court decision that excluded African American inmates from state prisons located in Coccidioides endemic areas.⁷ The most common sites of extrapulmonary dissemination include the skin and soft tissues, bones and joints, and the central nervous system (CNS).⁶ CNS disease has a predilection to manifest as a chronic basilar meningitis, most often complicated by hydrocephalus, vasculitic infarction, and spinal arachnoiditis.⁸

Cutaneous manifestations of coccidioidomycosis can occur as immunologic phenomenon associated with pulmonary disease or represent skin and soft tissue foci of disseminated infection.⁹ In primary pulmonary infection, skin findings can range from a nonspecific exanthem to erythema nodosum and erythema multiforme, which are thought to represent hypersensitivity responses. In contrast, Coccidioides spp can infect the skin either through direct inoculation (as in primary cutaneous coccidioidomycosis) or via hematogenous dissemination.^9,10 A variety of lesions have been described, with painless nodules being the most frequently encountered morphotype in one study.^11,12 On histopathologic examination, these lesions often have features of granulomatous dermatitis, eosinophilic infiltration, gummatous necrosis, microabscesses, or perivascular inflammation.¹³

Another common and highly morbid site of extrapulmonary dissemination is the musculoskeletal system. Bone and joint coccidioidomycosis most frequently affect the axial skeleton, although peripheral skeletal structures and joints can also be involved.^6,12 Vertebral coccidioidomycosis is associated with significant morbidity. A study describing the magnetic resonance imaging findings of patients with vertebral coccidioidomycosis found that Coccidioides spp appeared to have a predilection for the thoracic vertebrae (in up to 80% of the study’s cohort).¹⁴ Skip lesions with noncontiguously involved vertebrae occurred in roughly half of patients, highlighting the usefulness of imaging the total spine in suspected cases. 

The diagnosis of coccidioidomycosis is often established through serologic testing or by isolation of Coccidioides spp. on histopathology or culture. Obtaining sputum or tissue may be difficult, so clinicians often rely on noninvasive diagnostic tests such as coccidioidal antigen and serologies by enzyme immunoassays, immunodiffusion, and complement fixation. Enzyme immunoassays IgM and IgG results are positive early in the disease process and need to be confirmed with immunodiffusion or complement fixation testing. Complement fixation IgG is additionally useful to monitor disease activity over time and can help inform risk of disseminated disease.¹⁵ The gold standard of diagnosis of disseminated coccidioidomycosis infection remains histopathologic confirmation either by direct visualization of a spherule or growth in fungal cultures.¹⁶ Polymerase chain reaction testing of sputum samples is an emerging diagnostic technique that has been found to have similar sensitivity rates to fungal culture.¹⁷

Treatment decisions in coccidioidomycosis are complex and vary by site of infection, immune status of the host, and extent of disease.¹⁶ While uncomplicated primary pulmonary infections can often be managed with observation alone, prolonged medical therapy with azole antifungals is often recommended for complicated pulmonary infections, symptomatic cavitary disease, and virtually all forms of extrapulmonary disease. Intravenous liposomal amphotericin is often used as initial therapy in immunosuppressed individuals, pregnant women, and those with extensive disease. CNS disease represents a particularly challenging treatment scenario and requires lifelong azole therapy.^8,16 

The patient in this case initially presented with vague inflammatory symptoms, with each aliquot revealing further evidence of a metastatic disease process. Such multisystem presentations are diagnostically challenging and force clinicians to reach for some feature around which to build their differential diagnosis. It is with this in mind that we are often taught to “localize the lesion” in order to focus our search for a unifying diagnosis. Yet, in this case, the sheer number of disease foci ultimately helped the discussant to narrow the range of diagnostic possibilities because only a limited number of conditions could present with such widespread, multisystem manifestations. Therefore, this case serves as a reminder that, sometimes in clinical reasoning, “more is less.”

• Coccidioidomycosis is a fungal infection that can present with pulmonary or extrapulmonary disease. Risk of extrapulmonary dissemination is greatest among immunocompromised individuals and those of African or Filipino ancestry.^3,7
• The most common sites of extrapulmonary dissemination include the skin and soft tissues, bones and joints, and the CNS.⁶
• While serologic testing can be diagnostically useful, the gold standard for diagnosis of disseminated coccidioidomycosis infection remains histopathologic confirmation with direct visualization of a spherule or growth in fungal cultures.¹⁶

A 64-year-old man presented with a 2-month history of a nonproductive cough, weight loss, and subjective fevers. He had no chest pain, hemoptysis, or shortness of breath. He also described worsening anorexia and a 15-pound weight loss over the previous 3 months. He had no arthralgias, myalgias, abdominal pain, nausea, emesis, or diarrhea.

Two weeks prior to his presentation, he was diagnosed with pneumonia and given a 5-day course of azithromycin. His symptoms did not improve, so he presented to the emergency room. 

He had not been seen regularly by a physician in decades and had no known medical conditions. He did not take any medications. He immigrated from China 3 years prior and lived with his wife in California. He had a 30 pack-year smoking history. He drank a shot glass of liquor daily and denied any drug use.

Weight loss might result from inflammatory disorders like cancer or noninflammatory causes such as decreased oral intake (eg, diminished appetite) or malabsorption (eg, celiac disease). However, his fevers suggest inflammation, which usually reflects an underlying infection, cancer, or autoimmune process. While chronic cough typically results from upper airway cough syndrome (allergic or nonallergic rhinitis), gastroesophageal reflux disease, or asthma, it can also point to pathology of the lung, which may be intrinsic (bronchiectasis) or extrinsic (mediastinal mass). The duration of 2 months makes a typical infectious process like pneumococcal pneumonia unlikely. Atypical infections such as tuberculosis, melioidosis, and talaromycosis are possible given his immigration from East Asia, and coccidioidomycosis given his residence in California. He might have undiagnosed medical conditions, such as diabetes, that could be relevant to his current presentation and classify him as immunocompromised. His smoking history prompts consideration of lung cancer.

His temperature was 36.5 ^oC, heart rate 70 beats per minute, blood pressure 118/66 mm Hg, respiratory rate 16 breaths per minute, oxygen saturation 98% on room air, and body mass index 23 kg/m². He was in no acute distress. The findings from the cardiac, lung, abdominal, and neurological exams were normal.

Skin examination found a fixed, symmetric, 5-cm, firm nodule at top of sternum (Figure 1A). In addition, he had two 1-cm, mobile, firm, subcutaneous nodules, one on his anterior left chest and another underneath his right axilla. He also had two 2-cm, erythematous, tender nodules on his left anterior forearm and a 1-cm nodule with a central black plug on the dorsal surface of his right hand (Figure 1B). He did not have any edema.

The white blood cell count was 10,500/mm³ (42% neutrophils, 37% lymphocytes, 16.4% monocytes, and 2.9% eosinophils), hemoglobin was 12.2 g/dL with a mean corpuscular volume of 91 fL, and the platelet count was 441,000/mm³. Basic metabolic panel, aminotransferase, bilirubin, and alkaline phosphatase were within reference ranges. Serum albumin was 3.1 g/dL. Serum total protein was elevated at 8.8 g/dL. Serum calcium was 9.0 mg/dL. Urinalysis results were normal.

The slightly low albumin, mildly elevated platelet count, monocytosis, and normocytic anemia suggest inflammation, although monocytosis might represent a hematologic malignancy like chronic myelomonocytic leukemia (CMML). His subjective fevers and weight loss further corroborate underlying inflammation. What is driving the inflammation? There are two localizing findings: cough and nodular skin lesions.

His lack of dyspnea and normal oxygen saturation, respiratory rate, and lung exam make an extrapulmonary cause of cough such as lymphadenopathy or mediastinal infection possible. The number of nodular skin lesions, wide-spread distribution, and appearance (eg, erythematous, tender) point to either a primary cutaneous disease with systemic manifestations (eg, cutaneous lymphoma) or a systemic disease with cutaneous features (eg, sarcoidosis).

Three categories—inflammatory, infectious, and neoplastic—account for most nodular skin lesions. Usually microscopic evaluation is necessary for definitive diagnosis, though epidemiology, associated symptoms, and characteristics of the nodules help prioritize the differential diagnosis. Tender nodules might reflect a panniculitis; erythema nodosum is the most common type, and while this classically develops on the anterior shins, it may also occur on the forearm. His immigration from China prompts consideration of tuberculosis and cutaneous leishmaniasis. Coccidioidomycosis can lead to inflammation and nodular skin lesions. Other infections such as nontuberculous mycobacteria, nocardiosis, and cryptococcosis may cause disseminated infection with pulmonary and skin manifestations. His smoking puts him at risk of lung cancer, which rarely results in metastatic subcutaneous infiltrates.

A chest radiograph demonstrated a prominent density in the right paratracheal region of the mediastinum with adjacent streaky opacities. A computed tomography scan of the chest with intravenous contrast demonstrated centrilobular emphysematous changes and revealed a 2.6 × 4.7-cm necrotic mass in the anterior chest wall with erosion into the manubrium, a 3.8 × 2.1-cm centrally necrotic soft-tissue mass in the right hilum, a 5-mm left upper-lobe noncalcified solid pulmonary nodule, and prominent subcarinal, paratracheal, hilar, and bilateral supraclavicular lymphadenopathy (Figure 2). 

Flow cytometry of the peripheral blood did not demonstrate a lymphoproliferative disorder. Blood smear demonstrated normal red blood cell, white blood cell, and platelet morphology. HIV antibody was negative. Hemoglobin A1c was 6.1%. Smear microscopy for acid-fast bacilli (AFB) was negative and sputum AFB samples were sent for culture. Bacterial, fungal, and AFB blood cultures were collected and pending. 

Causes of necrotizing pneumonia include liquid (eg, lymphoma) and solid (eg, squamous cell carcinoma) cancers, infections, and noninfectious inflammatory processes such as granulomatosis with polyangiitis (GPA). Given his subacute presentation and extrapulmonary cutaneous manifestations, consideration of mycobacteria, fungi (eg, Coccidioides, Aspergillus, and Cryptococcus), and filamentous bacteria (eg, Nocardia and Actinomyces) is prioritized among the myriad of infections that can cause a lung cavity. His smoking history and centrilobular emphysematous changes are highly suggestive of chronic obstructive pulmonary disease, which puts him at increased risk of bacterial colonization and recurrent pulmonary infections. Tuberculosis is still possible despite three negative AFB-sputa smears given the sensitivity of smear microscopy (with three specimens) is roughly 70% in an immunocompetent host.

The lymphadenopathy likely reflects spread from the necrotic lung mass. The frequency of non-Hodgkin lymphoma increases with age. The results of the peripheral flow cytometry do not exclude the possibility of an aggressive lymphoma with pulmonary and cutaneous manifestations.

The erosive property of the chest wall mass makes an autoimmune process like GPA unlikely. An aggressive and disseminated infection or cancer is most likely. A pathologic process that originated in the lung and then spread to the lymph nodes and skin is more likely than a disorder which started in the skin. It would be unlikely for a primary cutaneous disorder to cause such a well-defined necrotic lung mass. Lung cancer rarely metastasizes to the skin and, instead, preferentially involves the chest. Ultimately, ascertaining what the patient experienced first (ie, respiratory or cutaneous symptoms) will determine where the pathology originated.

Computed tomography scan of the abdomen and pelvis with intravenous contrast demonstrated multiple ill-­defined lytic lesions in the pelvis, including a 12-mm lesion of the left sacral ala and multiple subcentimeter lesions in the medial left iliac bone and superior right acetabulum. In addition, there were two 1-cm, rim-enhancing, hypodense nodules in the subcutaneous fat of the right flank at the level of L5 and the left lower quadrant, respectively. There was also a 2.2 × 1.9-cm faintly rim-enhancing hypodensity within the left iliopsoas muscle belly.

These imaging findings further corroborate a widely metastatic process probably originating in the lung and spreading to the lymph nodes, skin, muscles, and bones. The characterization of lesions as lytic as opposed to blastic is less helpful because many diseases can cause both. It does prompt consideration of multiple myeloma; however, multiple myeloma less commonly manifests with extramedullary plasmacytomas and is less likely given his normal renal function and calcium level. Bone lesions lessen the likelihood of GPA, and his necrotic lung mass makes sarcoidosis unlikely. Atypical infections and cancers are the prime suspect of his multisystemic disease.

There are no data yet to suggest a weakened immune system, which would increase his risk for atypical infections. His chronic lung disease, identified on imaging, is a risk factor for nocardiosis. This gram-positive, weakly acid-fast bacterium can involve any organ, although lung, brain, and skin are most commonly involved. Disseminated nocardiosis can result from a pulmonary or cutaneous site of origin. Mycobacteria; Actinomyces; dimorphic fungi like Histoplasma, Coccidioides, and Blastomyces; and molds such as Aspergillus can also cause disseminated disease with pulmonary, cutaneous, and musculoskeletal manifestations.

While metastases to muscle itself are rare, they can occur with primary lung cancers. Primary lung cancer with extrapulmonary features is feasible. Squamous cell lung cancer is the most likely to cavitate, although it rarely spreads to the skin. An aggressive lymphoma like diffuse large B-cell lymphoma or cutaneous T-cell lymphoma (higher occurrence in Asians) might also explain his constellation of findings. If culture data remain negative, then biopsy of the chest wall mass might be the safest and highest-yield target.

On hospital day 2, the patient developed new-onset severe neck pain. Magnetic resonance imaging of the cervical, thoracic, and lumbar spine revealed multilevel, bony, lytic lesions with notable cortical breakthrough of the C2 and C3 vertebrae into the prevertebral space, as well as epidural extension and paraspinal soft-tissue extension of the thoracic and lumbar vertebral lesions (Figure 3). 

On hospital day 3, the patient reported increased tenderness in his skin nodules with one on his left forearm spontaneously draining purulent fluid. Repeat complete blood count demonstrated a white blood cell count of 12,600/mm³ (45% neutrophils, 43% lymphocytes, 8.4% monocytes, and 4.3% eosinophils), hemoglobin of 16 g/dL, and platelet count of 355,000/mm³.

The erosion into the manubrium and cortical destruction of the cervical spine attests to the aggressiveness of the underlying disease process. Noncutaneous lymphoma and lung cancer are unlikely to have such prominent skin findings; the visceral pathology, necrotizing lung mass, and bone lesions make cutaneous lymphoma less likely. At this point, a disseminated infectious process is most likely. Leading considerations based on his emigration from China and residence in California are tuberculosis and coccidioidomycosis, respectively. Tuberculous spondylitis most commonly involves the lower thoracic and upper lumbar region, and less commonly the cervical spine. His three negative AFB sputa samples further reduce its posttest probability. Ultimately microbiologic data are needed to distinguish between a disseminated fungal process, like coccidioidomycosis, or tuberculosis.

Given the concern for malignancy, a fine needle aspiration of the left supraclavicular lymph node was pursued. This revealed fungal microorganisms morphologically compatible with Coccidioides spp. with a background of necrotizing granulomas and acute inflammation. Fungal blood cultures grew Coccidioides immitis. AFB blood cultures were discontinued due to overgrowth of mold. The Coccidioides immitis antibody immunodiffusion titer was positive at 1:256. 

During the remainder of the hospitalization, the patient was treated with oral fluconazole 800 mg daily. The patient underwent surgical debridement of the manubrium. In addition, given the concern for cervical spine instability, neurosurgery recommended follow-up with interval imaging. Since his discharge from the hospital, the patient continues to take oral fluconazole with resolution of his cutaneous lesions and respiratory symptoms. His titers have incrementally decreased from 1:256 to 1:16 after 8 months of treatment. 

This elderly gentleman from China presented with subacute symptoms and was found to have numerous cutaneous nodules, lymphadenopathy, and diffuse osseous lesions. This multisystem illness posed a diagnostic challenge, forcing our discussant to search for a disease process that could lead to such varied findings. Ultimately, epidemiologic and clinical clues suggested a diagnosis of disseminated coccidioidomycosis, which was later confirmed on lymph node biopsy.

Coccidioides species are important fungal pathogens in the Western Hemisphere. This organism exhibits dimorphism, existing as mycelia (with arthroconidia) in soil and spherules in tissues. Coccidioides spp are endemic to the Southwestern United States, particularly California’s central valley and parts of Arizona; it additionally remains an important pathogen in Mexico, Central America, and South America.¹ Newer epidemiologic studies have raised concerns that the incidence of coccidioidomycosis is increasing and that its geographic range may be more extensive than previously appreciated, with it now being found as far north as Washington state.² 

Coccidioidal infection can take several forms. One-half to two-thirds of infections may be asymptomatic.³ Clinically significant infections can include an acute self-limiting respiratory illness, pulmonary nodules and cavities, chronic fibrocavitary pneumonia, and infections with extrapulmonary dissemination. Early respiratory infection is often indistinguishable from typical community-acquired pneumonia (10%-15% of pneumonia in endemic areas) but can be associated with certain suggestive features, such as erythema nodosum, erythema multiforme, prominent arthralgias (ie, “desert rheumatism”), and a peripheral eosinophilia.^4,5 

Extrapulmonary dissemination is rare and most commonly associated with immunocompromising states.⁶ However, individuals of African or Filipino ancestry also appear to be at increased risk for disseminated disease, which led to a California court decision that excluded African American inmates from state prisons located in Coccidioides endemic areas.⁷ The most common sites of extrapulmonary dissemination include the skin and soft tissues, bones and joints, and the central nervous system (CNS).⁶ CNS disease has a predilection to manifest as a chronic basilar meningitis, most often complicated by hydrocephalus, vasculitic infarction, and spinal arachnoiditis.⁸

Cutaneous manifestations of coccidioidomycosis can occur as immunologic phenomenon associated with pulmonary disease or represent skin and soft tissue foci of disseminated infection.⁹ In primary pulmonary infection, skin findings can range from a nonspecific exanthem to erythema nodosum and erythema multiforme, which are thought to represent hypersensitivity responses. In contrast, Coccidioides spp can infect the skin either through direct inoculation (as in primary cutaneous coccidioidomycosis) or via hematogenous dissemination.^9,10 A variety of lesions have been described, with painless nodules being the most frequently encountered morphotype in one study.^11,12 On histopathologic examination, these lesions often have features of granulomatous dermatitis, eosinophilic infiltration, gummatous necrosis, microabscesses, or perivascular inflammation.¹³

Another common and highly morbid site of extrapulmonary dissemination is the musculoskeletal system. Bone and joint coccidioidomycosis most frequently affect the axial skeleton, although peripheral skeletal structures and joints can also be involved.^6,12 Vertebral coccidioidomycosis is associated with significant morbidity. A study describing the magnetic resonance imaging findings of patients with vertebral coccidioidomycosis found that Coccidioides spp appeared to have a predilection for the thoracic vertebrae (in up to 80% of the study’s cohort).¹⁴ Skip lesions with noncontiguously involved vertebrae occurred in roughly half of patients, highlighting the usefulness of imaging the total spine in suspected cases. 

The diagnosis of coccidioidomycosis is often established through serologic testing or by isolation of Coccidioides spp. on histopathology or culture. Obtaining sputum or tissue may be difficult, so clinicians often rely on noninvasive diagnostic tests such as coccidioidal antigen and serologies by enzyme immunoassays, immunodiffusion, and complement fixation. Enzyme immunoassays IgM and IgG results are positive early in the disease process and need to be confirmed with immunodiffusion or complement fixation testing. Complement fixation IgG is additionally useful to monitor disease activity over time and can help inform risk of disseminated disease.¹⁵ The gold standard of diagnosis of disseminated coccidioidomycosis infection remains histopathologic confirmation either by direct visualization of a spherule or growth in fungal cultures.¹⁶ Polymerase chain reaction testing of sputum samples is an emerging diagnostic technique that has been found to have similar sensitivity rates to fungal culture.¹⁷

Treatment decisions in coccidioidomycosis are complex and vary by site of infection, immune status of the host, and extent of disease.¹⁶ While uncomplicated primary pulmonary infections can often be managed with observation alone, prolonged medical therapy with azole antifungals is often recommended for complicated pulmonary infections, symptomatic cavitary disease, and virtually all forms of extrapulmonary disease. Intravenous liposomal amphotericin is often used as initial therapy in immunosuppressed individuals, pregnant women, and those with extensive disease. CNS disease represents a particularly challenging treatment scenario and requires lifelong azole therapy.^8,16 

The patient in this case initially presented with vague inflammatory symptoms, with each aliquot revealing further evidence of a metastatic disease process. Such multisystem presentations are diagnostically challenging and force clinicians to reach for some feature around which to build their differential diagnosis. It is with this in mind that we are often taught to “localize the lesion” in order to focus our search for a unifying diagnosis. Yet, in this case, the sheer number of disease foci ultimately helped the discussant to narrow the range of diagnostic possibilities because only a limited number of conditions could present with such widespread, multisystem manifestations. Therefore, this case serves as a reminder that, sometimes in clinical reasoning, “more is less.”

• Coccidioidomycosis is a fungal infection that can present with pulmonary or extrapulmonary disease. Risk of extrapulmonary dissemination is greatest among immunocompromised individuals and those of African or Filipino ancestry.^3,7
• The most common sites of extrapulmonary dissemination include the skin and soft tissues, bones and joints, and the CNS.⁶
• While serologic testing can be diagnostically useful, the gold standard for diagnosis of disseminated coccidioidomycosis infection remains histopathologic confirmation with direct visualization of a spherule or growth in fungal cultures.¹⁶

A 64-year-old man presented with a 2-month history of a nonproductive cough, weight loss, and subjective fevers. He had no chest pain, hemoptysis, or shortness of breath. He also described worsening anorexia and a 15-pound weight loss over the previous 3 months. He had no arthralgias, myalgias, abdominal pain, nausea, emesis, or diarrhea.

Two weeks prior to his presentation, he was diagnosed with pneumonia and given a 5-day course of azithromycin. His symptoms did not improve, so he presented to the emergency room. 

He had not been seen regularly by a physician in decades and had no known medical conditions. He did not take any medications. He immigrated from China 3 years prior and lived with his wife in California. He had a 30 pack-year smoking history. He drank a shot glass of liquor daily and denied any drug use.

Weight loss might result from inflammatory disorders like cancer or noninflammatory causes such as decreased oral intake (eg, diminished appetite) or malabsorption (eg, celiac disease). However, his fevers suggest inflammation, which usually reflects an underlying infection, cancer, or autoimmune process. While chronic cough typically results from upper airway cough syndrome (allergic or nonallergic rhinitis), gastroesophageal reflux disease, or asthma, it can also point to pathology of the lung, which may be intrinsic (bronchiectasis) or extrinsic (mediastinal mass). The duration of 2 months makes a typical infectious process like pneumococcal pneumonia unlikely. Atypical infections such as tuberculosis, melioidosis, and talaromycosis are possible given his immigration from East Asia, and coccidioidomycosis given his residence in California. He might have undiagnosed medical conditions, such as diabetes, that could be relevant to his current presentation and classify him as immunocompromised. His smoking history prompts consideration of lung cancer.

His temperature was 36.5 ^oC, heart rate 70 beats per minute, blood pressure 118/66 mm Hg, respiratory rate 16 breaths per minute, oxygen saturation 98% on room air, and body mass index 23 kg/m². He was in no acute distress. The findings from the cardiac, lung, abdominal, and neurological exams were normal.

Skin examination found a fixed, symmetric, 5-cm, firm nodule at top of sternum (Figure 1A). In addition, he had two 1-cm, mobile, firm, subcutaneous nodules, one on his anterior left chest and another underneath his right axilla. He also had two 2-cm, erythematous, tender nodules on his left anterior forearm and a 1-cm nodule with a central black plug on the dorsal surface of his right hand (Figure 1B). He did not have any edema.

The white blood cell count was 10,500/mm³ (42% neutrophils, 37% lymphocytes, 16.4% monocytes, and 2.9% eosinophils), hemoglobin was 12.2 g/dL with a mean corpuscular volume of 91 fL, and the platelet count was 441,000/mm³. Basic metabolic panel, aminotransferase, bilirubin, and alkaline phosphatase were within reference ranges. Serum albumin was 3.1 g/dL. Serum total protein was elevated at 8.8 g/dL. Serum calcium was 9.0 mg/dL. Urinalysis results were normal.

The slightly low albumin, mildly elevated platelet count, monocytosis, and normocytic anemia suggest inflammation, although monocytosis might represent a hematologic malignancy like chronic myelomonocytic leukemia (CMML). His subjective fevers and weight loss further corroborate underlying inflammation. What is driving the inflammation? There are two localizing findings: cough and nodular skin lesions.

His lack of dyspnea and normal oxygen saturation, respiratory rate, and lung exam make an extrapulmonary cause of cough such as lymphadenopathy or mediastinal infection possible. The number of nodular skin lesions, wide-spread distribution, and appearance (eg, erythematous, tender) point to either a primary cutaneous disease with systemic manifestations (eg, cutaneous lymphoma) or a systemic disease with cutaneous features (eg, sarcoidosis).

Three categories—inflammatory, infectious, and neoplastic—account for most nodular skin lesions. Usually microscopic evaluation is necessary for definitive diagnosis, though epidemiology, associated symptoms, and characteristics of the nodules help prioritize the differential diagnosis. Tender nodules might reflect a panniculitis; erythema nodosum is the most common type, and while this classically develops on the anterior shins, it may also occur on the forearm. His immigration from China prompts consideration of tuberculosis and cutaneous leishmaniasis. Coccidioidomycosis can lead to inflammation and nodular skin lesions. Other infections such as nontuberculous mycobacteria, nocardiosis, and cryptococcosis may cause disseminated infection with pulmonary and skin manifestations. His smoking puts him at risk of lung cancer, which rarely results in metastatic subcutaneous infiltrates.

A chest radiograph demonstrated a prominent density in the right paratracheal region of the mediastinum with adjacent streaky opacities. A computed tomography scan of the chest with intravenous contrast demonstrated centrilobular emphysematous changes and revealed a 2.6 × 4.7-cm necrotic mass in the anterior chest wall with erosion into the manubrium, a 3.8 × 2.1-cm centrally necrotic soft-tissue mass in the right hilum, a 5-mm left upper-lobe noncalcified solid pulmonary nodule, and prominent subcarinal, paratracheal, hilar, and bilateral supraclavicular lymphadenopathy (Figure 2). 

Flow cytometry of the peripheral blood did not demonstrate a lymphoproliferative disorder. Blood smear demonstrated normal red blood cell, white blood cell, and platelet morphology. HIV antibody was negative. Hemoglobin A1c was 6.1%. Smear microscopy for acid-fast bacilli (AFB) was negative and sputum AFB samples were sent for culture. Bacterial, fungal, and AFB blood cultures were collected and pending. 

Causes of necrotizing pneumonia include liquid (eg, lymphoma) and solid (eg, squamous cell carcinoma) cancers, infections, and noninfectious inflammatory processes such as granulomatosis with polyangiitis (GPA). Given his subacute presentation and extrapulmonary cutaneous manifestations, consideration of mycobacteria, fungi (eg, Coccidioides, Aspergillus, and Cryptococcus), and filamentous bacteria (eg, Nocardia and Actinomyces) is prioritized among the myriad of infections that can cause a lung cavity. His smoking history and centrilobular emphysematous changes are highly suggestive of chronic obstructive pulmonary disease, which puts him at increased risk of bacterial colonization and recurrent pulmonary infections. Tuberculosis is still possible despite three negative AFB-sputa smears given the sensitivity of smear microscopy (with three specimens) is roughly 70% in an immunocompetent host.

The lymphadenopathy likely reflects spread from the necrotic lung mass. The frequency of non-Hodgkin lymphoma increases with age. The results of the peripheral flow cytometry do not exclude the possibility of an aggressive lymphoma with pulmonary and cutaneous manifestations.

The erosive property of the chest wall mass makes an autoimmune process like GPA unlikely. An aggressive and disseminated infection or cancer is most likely. A pathologic process that originated in the lung and then spread to the lymph nodes and skin is more likely than a disorder which started in the skin. It would be unlikely for a primary cutaneous disorder to cause such a well-defined necrotic lung mass. Lung cancer rarely metastasizes to the skin and, instead, preferentially involves the chest. Ultimately, ascertaining what the patient experienced first (ie, respiratory or cutaneous symptoms) will determine where the pathology originated.

Computed tomography scan of the abdomen and pelvis with intravenous contrast demonstrated multiple ill-­defined lytic lesions in the pelvis, including a 12-mm lesion of the left sacral ala and multiple subcentimeter lesions in the medial left iliac bone and superior right acetabulum. In addition, there were two 1-cm, rim-enhancing, hypodense nodules in the subcutaneous fat of the right flank at the level of L5 and the left lower quadrant, respectively. There was also a 2.2 × 1.9-cm faintly rim-enhancing hypodensity within the left iliopsoas muscle belly.

These imaging findings further corroborate a widely metastatic process probably originating in the lung and spreading to the lymph nodes, skin, muscles, and bones. The characterization of lesions as lytic as opposed to blastic is less helpful because many diseases can cause both. It does prompt consideration of multiple myeloma; however, multiple myeloma less commonly manifests with extramedullary plasmacytomas and is less likely given his normal renal function and calcium level. Bone lesions lessen the likelihood of GPA, and his necrotic lung mass makes sarcoidosis unlikely. Atypical infections and cancers are the prime suspect of his multisystemic disease.

There are no data yet to suggest a weakened immune system, which would increase his risk for atypical infections. His chronic lung disease, identified on imaging, is a risk factor for nocardiosis. This gram-positive, weakly acid-fast bacterium can involve any organ, although lung, brain, and skin are most commonly involved. Disseminated nocardiosis can result from a pulmonary or cutaneous site of origin. Mycobacteria; Actinomyces; dimorphic fungi like Histoplasma, Coccidioides, and Blastomyces; and molds such as Aspergillus can also cause disseminated disease with pulmonary, cutaneous, and musculoskeletal manifestations.

While metastases to muscle itself are rare, they can occur with primary lung cancers. Primary lung cancer with extrapulmonary features is feasible. Squamous cell lung cancer is the most likely to cavitate, although it rarely spreads to the skin. An aggressive lymphoma like diffuse large B-cell lymphoma or cutaneous T-cell lymphoma (higher occurrence in Asians) might also explain his constellation of findings. If culture data remain negative, then biopsy of the chest wall mass might be the safest and highest-yield target.

On hospital day 2, the patient developed new-onset severe neck pain. Magnetic resonance imaging of the cervical, thoracic, and lumbar spine revealed multilevel, bony, lytic lesions with notable cortical breakthrough of the C2 and C3 vertebrae into the prevertebral space, as well as epidural extension and paraspinal soft-tissue extension of the thoracic and lumbar vertebral lesions (Figure 3). 

On hospital day 3, the patient reported increased tenderness in his skin nodules with one on his left forearm spontaneously draining purulent fluid. Repeat complete blood count demonstrated a white blood cell count of 12,600/mm³ (45% neutrophils, 43% lymphocytes, 8.4% monocytes, and 4.3% eosinophils), hemoglobin of 16 g/dL, and platelet count of 355,000/mm³.

The erosion into the manubrium and cortical destruction of the cervical spine attests to the aggressiveness of the underlying disease process. Noncutaneous lymphoma and lung cancer are unlikely to have such prominent skin findings; the visceral pathology, necrotizing lung mass, and bone lesions make cutaneous lymphoma less likely. At this point, a disseminated infectious process is most likely. Leading considerations based on his emigration from China and residence in California are tuberculosis and coccidioidomycosis, respectively. Tuberculous spondylitis most commonly involves the lower thoracic and upper lumbar region, and less commonly the cervical spine. His three negative AFB sputa samples further reduce its posttest probability. Ultimately microbiologic data are needed to distinguish between a disseminated fungal process, like coccidioidomycosis, or tuberculosis.

Given the concern for malignancy, a fine needle aspiration of the left supraclavicular lymph node was pursued. This revealed fungal microorganisms morphologically compatible with Coccidioides spp. with a background of necrotizing granulomas and acute inflammation. Fungal blood cultures grew Coccidioides immitis. AFB blood cultures were discontinued due to overgrowth of mold. The Coccidioides immitis antibody immunodiffusion titer was positive at 1:256. 

During the remainder of the hospitalization, the patient was treated with oral fluconazole 800 mg daily. The patient underwent surgical debridement of the manubrium. In addition, given the concern for cervical spine instability, neurosurgery recommended follow-up with interval imaging. Since his discharge from the hospital, the patient continues to take oral fluconazole with resolution of his cutaneous lesions and respiratory symptoms. His titers have incrementally decreased from 1:256 to 1:16 after 8 months of treatment. 

This elderly gentleman from China presented with subacute symptoms and was found to have numerous cutaneous nodules, lymphadenopathy, and diffuse osseous lesions. This multisystem illness posed a diagnostic challenge, forcing our discussant to search for a disease process that could lead to such varied findings. Ultimately, epidemiologic and clinical clues suggested a diagnosis of disseminated coccidioidomycosis, which was later confirmed on lymph node biopsy.

Coccidioides species are important fungal pathogens in the Western Hemisphere. This organism exhibits dimorphism, existing as mycelia (with arthroconidia) in soil and spherules in tissues. Coccidioides spp are endemic to the Southwestern United States, particularly California’s central valley and parts of Arizona; it additionally remains an important pathogen in Mexico, Central America, and South America.¹ Newer epidemiologic studies have raised concerns that the incidence of coccidioidomycosis is increasing and that its geographic range may be more extensive than previously appreciated, with it now being found as far north as Washington state.² 

Coccidioidal infection can take several forms. One-half to two-thirds of infections may be asymptomatic.³ Clinically significant infections can include an acute self-limiting respiratory illness, pulmonary nodules and cavities, chronic fibrocavitary pneumonia, and infections with extrapulmonary dissemination. Early respiratory infection is often indistinguishable from typical community-acquired pneumonia (10%-15% of pneumonia in endemic areas) but can be associated with certain suggestive features, such as erythema nodosum, erythema multiforme, prominent arthralgias (ie, “desert rheumatism”), and a peripheral eosinophilia.^4,5 

Extrapulmonary dissemination is rare and most commonly associated with immunocompromising states.⁶ However, individuals of African or Filipino ancestry also appear to be at increased risk for disseminated disease, which led to a California court decision that excluded African American inmates from state prisons located in Coccidioides endemic areas.⁷ The most common sites of extrapulmonary dissemination include the skin and soft tissues, bones and joints, and the central nervous system (CNS).⁶ CNS disease has a predilection to manifest as a chronic basilar meningitis, most often complicated by hydrocephalus, vasculitic infarction, and spinal arachnoiditis.⁸

Cutaneous manifestations of coccidioidomycosis can occur as immunologic phenomenon associated with pulmonary disease or represent skin and soft tissue foci of disseminated infection.⁹ In primary pulmonary infection, skin findings can range from a nonspecific exanthem to erythema nodosum and erythema multiforme, which are thought to represent hypersensitivity responses. In contrast, Coccidioides spp can infect the skin either through direct inoculation (as in primary cutaneous coccidioidomycosis) or via hematogenous dissemination.^9,10 A variety of lesions have been described, with painless nodules being the most frequently encountered morphotype in one study.^11,12 On histopathologic examination, these lesions often have features of granulomatous dermatitis, eosinophilic infiltration, gummatous necrosis, microabscesses, or perivascular inflammation.¹³

Another common and highly morbid site of extrapulmonary dissemination is the musculoskeletal system. Bone and joint coccidioidomycosis most frequently affect the axial skeleton, although peripheral skeletal structures and joints can also be involved.^6,12 Vertebral coccidioidomycosis is associated with significant morbidity. A study describing the magnetic resonance imaging findings of patients with vertebral coccidioidomycosis found that Coccidioides spp appeared to have a predilection for the thoracic vertebrae (in up to 80% of the study’s cohort).¹⁴ Skip lesions with noncontiguously involved vertebrae occurred in roughly half of patients, highlighting the usefulness of imaging the total spine in suspected cases. 

The diagnosis of coccidioidomycosis is often established through serologic testing or by isolation of Coccidioides spp. on histopathology or culture. Obtaining sputum or tissue may be difficult, so clinicians often rely on noninvasive diagnostic tests such as coccidioidal antigen and serologies by enzyme immunoassays, immunodiffusion, and complement fixation. Enzyme immunoassays IgM and IgG results are positive early in the disease process and need to be confirmed with immunodiffusion or complement fixation testing. Complement fixation IgG is additionally useful to monitor disease activity over time and can help inform risk of disseminated disease.¹⁵ The gold standard of diagnosis of disseminated coccidioidomycosis infection remains histopathologic confirmation either by direct visualization of a spherule or growth in fungal cultures.¹⁶ Polymerase chain reaction testing of sputum samples is an emerging diagnostic technique that has been found to have similar sensitivity rates to fungal culture.¹⁷

Treatment decisions in coccidioidomycosis are complex and vary by site of infection, immune status of the host, and extent of disease.¹⁶ While uncomplicated primary pulmonary infections can often be managed with observation alone, prolonged medical therapy with azole antifungals is often recommended for complicated pulmonary infections, symptomatic cavitary disease, and virtually all forms of extrapulmonary disease. Intravenous liposomal amphotericin is often used as initial therapy in immunosuppressed individuals, pregnant women, and those with extensive disease. CNS disease represents a particularly challenging treatment scenario and requires lifelong azole therapy.^8,16 

The patient in this case initially presented with vague inflammatory symptoms, with each aliquot revealing further evidence of a metastatic disease process. Such multisystem presentations are diagnostically challenging and force clinicians to reach for some feature around which to build their differential diagnosis. It is with this in mind that we are often taught to “localize the lesion” in order to focus our search for a unifying diagnosis. Yet, in this case, the sheer number of disease foci ultimately helped the discussant to narrow the range of diagnostic possibilities because only a limited number of conditions could present with such widespread, multisystem manifestations. Therefore, this case serves as a reminder that, sometimes in clinical reasoning, “more is less.”

• Coccidioidomycosis is a fungal infection that can present with pulmonary or extrapulmonary disease. Risk of extrapulmonary dissemination is greatest among immunocompromised individuals and those of African or Filipino ancestry.^3,7
• The most common sites of extrapulmonary dissemination include the skin and soft tissues, bones and joints, and the CNS.⁶
• While serologic testing can be diagnostically useful, the gold standard for diagnosis of disseminated coccidioidomycosis infection remains histopathologic confirmation with direct visualization of a spherule or growth in fungal cultures.¹⁶

The spread of SARS-CoV-2, the pathogen behind the COVID-19 pandemic, has converged with an unrelenting addiction epidemic. These combined crises will have profound effects on people with substance use disorders (SUD) and people in recovery. Hospitals—which were already hit hard by the addiction epidemic—are the last line of defense in the COVID-19 pandemic. Hospitalists have an important role in balancing the effects of these intersecting, synergistic crises.

People with SUD are disproportionately affected by major medical illnesses, including infections such as hepatitis C, HIV, and cardiovascular, pulmonary, and liver diseases.¹ They also experience high rates of hospitalization due to drug-related infections, injury, and overdose.² People with SUD commonly have intersecting vulnerabilities that may affect their healthcare experience and health outcomes, including housing and food insecurity, mental illness, and experiences of racism, incarceration, and other trauma. They may also harbor mistrust of healthcare providers because of previous negative encounters and discrimination with health systems.³ These vulnerabilities increase risks for COVID-19 morbidity and mortality.^4,5 The COVID-19 pandemic may drive increases in use and harms from SUD among patients who already have an SUD, with widespread job loss, insurance loss,⁶ anxiety, and social isolation on the rise. We may also see increases in return to use among people in recovery or new substance use among those without a history of SUD.

The intersecting crises of SUD and COVID-19 are important for people with SUD and for public health. In this perspective, we describe how the COVID-19 pandemic has affected people with SUD and share practical resources for hospital providers to improve care for people with SUD during the pandemic and beyond.

Mistrust of Hospitals and Healthcare Providers

Fear of stigmatization is an ongoing problem for people with SUD, who often experience discrimination in hospitals and, as a result, may avoid hospital care.⁷ Much of this stigma is based on the false but persistent belief—widespread even among healthcare providers—that addiction is the result of bad choices and limited willpower; however, the science is clear that addiction is a disorder with neurobiological, genetic, and environmental underpinnings.³ These attitudes are likely to be amplified during COVID-19, as patients and providers experience higher levels of stress.

Increased Risks of Substance Use

Typically, people who use drugs are counseled to use with others nearby so that they might administer naloxone or call 911 in the event of an overdose.⁸ With physical distancing, people may be more likely to use alone. COVID-19 also introduces uncertainty into the drug supply chain through changes in drug production and trafficking.⁹ Further, access to alcohol may be limited as liquor stores close and public transportation becomes less available. As has been shown in other complex emergencies (such as social, political, economic, and environmental disasters), these barriers to obtaining substances may increase risks for withdrawal, for needing to exchange sex for money or drugs, for sharing syringes or drug preparation equipment,¹⁰ or for consuming other available sources of substances, like rubbing alcohol or hand sanitizer. COVID-19 may also increase risk for depression, anxiety, social isolation, and suicidality, all of which increase risk for return to use and overdose.

Changes to the Treatment Milieu

Many of the resources and services that people who use substances rely on to keep safe may be disrupted by COVID-19. Social distancing—the cornerstone of mitigating COVID-19 spread—may be challenging among people with SUD. Though federal regulations around methadone dispensing and buprenorphine prescribing have loosened in response to the pandemic,¹¹ individuals in treatment may still be required to provide urine drug screens or be physically present to receive methadone doses, sometimes daily and in crowded waiting rooms.

Recovery support groups such as Alcoholics Anonymous (AA) and Self-Management and Recovery Training (SMART) provide social connection and are the foundation of many people’s recovery. While many in-person meetings have rapidly transformed to online and telephone support, they remain inaccessible to the most marginalized members of communities: people without smart phones, computers, or internet. This digital shift may also disproportionately affect older adults, people with limited English proficiency, and people with low technological literacy. Limits for other resources, such as syringe service programs, community centers, food pantries, housing shelters, and other places that people depend on for clean water, food, showers, soap, and safer spaces to use, may limit services or close altogether; those that remain open may see an unprecedented rise in need for services as millions of Americans file for unemployment. For many, anxiety about the pandemic, unemployment, financial strain, increased isolation, family stressors, illness, and community losses can lead to enormous personal distress and trigger return to use; loss of a recovery network may further exacerbate this.

Intersectionality of SUD and Other Structural Inequities

Many of the inequities that increase people’s risk for undertreated SUD also increase risk for COVID-19 infection, including racism,¹² poverty, and homelessness.⁴ “Stay home and stay safe” is not an option for people who are unsheltered or whose homes are unsafe because of risks of physical, sexual, or emotional violence. Poverty commonly forces people to live in crowded communal apartments or shelters, rely on public transportation, wait in long lines at food pantries, and continue to work, even if unwell. Many shelters have had to reduce the number of people they serve to reduce crowding and support social distancing, which further compounds risks of unstable housing. Unfortunately, the same structural inequities that exacerbate SUD worsen the COVID-19 crisis.¹³

The intersecting vulnerabilities of SUD and COVID-19 heighten an already urgent need to address SUD among hospitalized patients.¹⁴ While COVID-19 may increase harms of substance use, it may also increase people’s readiness to engage in treatment given changes to the drug supply and patient’s concerns about health risks. As such, it is even more critical to make treatment readily accessible and support harm reduction. Hospitalists can take important, actionable steps for patients with SUD—many of which are good general practices¹⁴ (Appendix Table).

Hospitalists should do the following:

1. Identify and treat acute withdrawal.¹⁵

2. Manage acute pain, including providing high-dose opioids if needed.¹⁶ Both practices (1 and 2) are evidence-based, can promote patient’s trust in providers,¹⁷ and can help avoid patients leaving against medical advice (AMA). Leaving AMA can lead to poor individual health and further threaten public health if patients leave with undiagnosed or unmanaged COVID-19 infection.

3. Encourage their hospitals to provide patients with tablets or other means to communicate with family, friends, and recovery supports via videolink, and refer patients to virtual peer support and recovery meetings during hospitalization.¹⁸ These practices may further support patients in tolerating hospitalization and prevent AMA discharge.

4. Initiate medication for addiction during admission and refer to addictions treatment after discharge. COVID-19–related regulatory changes such as expanded telehealth buprenorphine options and fewer daily dosing requirements for methadone may make this easier. Further, hospitalists should offer medication for alcohol and tobacco use disorders,¹⁵ especially given heightened possibility of unhealthy alcohol use and the respiratory complications associated with both tobacco and COVID-19.

5. Assess mental health and suicide risks¹⁹ given their association with social isolation, job loss, and financial insecurity.

6. Discuss relapse prevention among people in recovery.

7. Assess overdose risk and promote harm reduction.¹⁹ Specifically, this may include counseling patients to avoid sharing smoking supplies to avoid COVID-19 transmission, identifying places to access clean syringes, prescribing naloxone,²⁰ and providing supports so that, if patients need to use alone, they can do so more safely.²¹

8. Consider high-risk transitions that may be exacerbated by COVID-19. COVID-19 may make safe discharge plans among people experiencing homelessness very challenging. Some communities are rapidly repurposing existing spaces or building new ones to care for people without a safe place to recover after acute hospitalization, yet many communities have no such resources. Hospital teams should consider the possibility that community services and SUD treatment resources may change rapidly during the pandemic. Hospitals can maintain updated resource lists and consider partnering with state and local health departments to improve safe care for people experiencing homelessness or lacking basic services.

COVID-19 is putting enormous strain on many US hospitals. Hospital-based addictions care is under resourced in the best of times,¹⁴ and while some hospitals have addiction consult services, many do not. To what degree hospitalists and hospital teams can address anything beyond COVID-19 emergencies will vary based on settings and resources. Furthermore, we recognize that who performs various activities will depend on individual hospital’s resources and practices. Addiction consult services, if available, can play a critical role, as can hospital social workers and care managers, nurses, residents, students, and other members of the healthcare team.

Finally, though COVID-19 adds tremendous stress to hospitals, permanent improvements in SUD treatment systems such as telephone visits for buprenorphine or eased methadone restrictions may emerge that could reduce barriers to hospital-based addictions care.¹¹ Leveraging these changes now may help hospital providers to better support patients long-term.

Hospitalization can be a challenging time for patients with SUD and for the hospital teams who care for them. These tensions are exacerbated by the COVID-19 pandemic, yet hospitalists play a critical role in addressing the converging crises of SUD and COVID-19. Providing comprehensive, compassionate, evidence-based care for hospitalized patients with SUD is important for both individual and community health during COVID-19.

The authors would like to thank Alisa Patten for help preparing this manuscript.

The authors have no conflicts of interest to disclose.

Dr King received grant support from the National Institutes of Health (UG1DA015815) and the National Institute on Drug Abuse (R01DA037441). Dr Snyder received a Public Health Institute grant payable to her institution.

The spread of SARS-CoV-2, the pathogen behind the COVID-19 pandemic, has converged with an unrelenting addiction epidemic. These combined crises will have profound effects on people with substance use disorders (SUD) and people in recovery. Hospitals—which were already hit hard by the addiction epidemic—are the last line of defense in the COVID-19 pandemic. Hospitalists have an important role in balancing the effects of these intersecting, synergistic crises.

People with SUD are disproportionately affected by major medical illnesses, including infections such as hepatitis C, HIV, and cardiovascular, pulmonary, and liver diseases.¹ They also experience high rates of hospitalization due to drug-related infections, injury, and overdose.² People with SUD commonly have intersecting vulnerabilities that may affect their healthcare experience and health outcomes, including housing and food insecurity, mental illness, and experiences of racism, incarceration, and other trauma. They may also harbor mistrust of healthcare providers because of previous negative encounters and discrimination with health systems.³ These vulnerabilities increase risks for COVID-19 morbidity and mortality.^4,5 The COVID-19 pandemic may drive increases in use and harms from SUD among patients who already have an SUD, with widespread job loss, insurance loss,⁶ anxiety, and social isolation on the rise. We may also see increases in return to use among people in recovery or new substance use among those without a history of SUD.

The intersecting crises of SUD and COVID-19 are important for people with SUD and for public health. In this perspective, we describe how the COVID-19 pandemic has affected people with SUD and share practical resources for hospital providers to improve care for people with SUD during the pandemic and beyond.

Mistrust of Hospitals and Healthcare Providers

Fear of stigmatization is an ongoing problem for people with SUD, who often experience discrimination in hospitals and, as a result, may avoid hospital care.⁷ Much of this stigma is based on the false but persistent belief—widespread even among healthcare providers—that addiction is the result of bad choices and limited willpower; however, the science is clear that addiction is a disorder with neurobiological, genetic, and environmental underpinnings.³ These attitudes are likely to be amplified during COVID-19, as patients and providers experience higher levels of stress.

Increased Risks of Substance Use

Typically, people who use drugs are counseled to use with others nearby so that they might administer naloxone or call 911 in the event of an overdose.⁸ With physical distancing, people may be more likely to use alone. COVID-19 also introduces uncertainty into the drug supply chain through changes in drug production and trafficking.⁹ Further, access to alcohol may be limited as liquor stores close and public transportation becomes less available. As has been shown in other complex emergencies (such as social, political, economic, and environmental disasters), these barriers to obtaining substances may increase risks for withdrawal, for needing to exchange sex for money or drugs, for sharing syringes or drug preparation equipment,¹⁰ or for consuming other available sources of substances, like rubbing alcohol or hand sanitizer. COVID-19 may also increase risk for depression, anxiety, social isolation, and suicidality, all of which increase risk for return to use and overdose.

Changes to the Treatment Milieu

Many of the resources and services that people who use substances rely on to keep safe may be disrupted by COVID-19. Social distancing—the cornerstone of mitigating COVID-19 spread—may be challenging among people with SUD. Though federal regulations around methadone dispensing and buprenorphine prescribing have loosened in response to the pandemic,¹¹ individuals in treatment may still be required to provide urine drug screens or be physically present to receive methadone doses, sometimes daily and in crowded waiting rooms.

Recovery support groups such as Alcoholics Anonymous (AA) and Self-Management and Recovery Training (SMART) provide social connection and are the foundation of many people’s recovery. While many in-person meetings have rapidly transformed to online and telephone support, they remain inaccessible to the most marginalized members of communities: people without smart phones, computers, or internet. This digital shift may also disproportionately affect older adults, people with limited English proficiency, and people with low technological literacy. Limits for other resources, such as syringe service programs, community centers, food pantries, housing shelters, and other places that people depend on for clean water, food, showers, soap, and safer spaces to use, may limit services or close altogether; those that remain open may see an unprecedented rise in need for services as millions of Americans file for unemployment. For many, anxiety about the pandemic, unemployment, financial strain, increased isolation, family stressors, illness, and community losses can lead to enormous personal distress and trigger return to use; loss of a recovery network may further exacerbate this.

Intersectionality of SUD and Other Structural Inequities

Many of the inequities that increase people’s risk for undertreated SUD also increase risk for COVID-19 infection, including racism,¹² poverty, and homelessness.⁴ “Stay home and stay safe” is not an option for people who are unsheltered or whose homes are unsafe because of risks of physical, sexual, or emotional violence. Poverty commonly forces people to live in crowded communal apartments or shelters, rely on public transportation, wait in long lines at food pantries, and continue to work, even if unwell. Many shelters have had to reduce the number of people they serve to reduce crowding and support social distancing, which further compounds risks of unstable housing. Unfortunately, the same structural inequities that exacerbate SUD worsen the COVID-19 crisis.¹³

The intersecting vulnerabilities of SUD and COVID-19 heighten an already urgent need to address SUD among hospitalized patients.¹⁴ While COVID-19 may increase harms of substance use, it may also increase people’s readiness to engage in treatment given changes to the drug supply and patient’s concerns about health risks. As such, it is even more critical to make treatment readily accessible and support harm reduction. Hospitalists can take important, actionable steps for patients with SUD—many of which are good general practices¹⁴ (Appendix Table).

Hospitalists should do the following:

1. Identify and treat acute withdrawal.¹⁵

2. Manage acute pain, including providing high-dose opioids if needed.¹⁶ Both practices (1 and 2) are evidence-based, can promote patient’s trust in providers,¹⁷ and can help avoid patients leaving against medical advice (AMA). Leaving AMA can lead to poor individual health and further threaten public health if patients leave with undiagnosed or unmanaged COVID-19 infection.

3. Encourage their hospitals to provide patients with tablets or other means to communicate with family, friends, and recovery supports via videolink, and refer patients to virtual peer support and recovery meetings during hospitalization.¹⁸ These practices may further support patients in tolerating hospitalization and prevent AMA discharge.

4. Initiate medication for addiction during admission and refer to addictions treatment after discharge. COVID-19–related regulatory changes such as expanded telehealth buprenorphine options and fewer daily dosing requirements for methadone may make this easier. Further, hospitalists should offer medication for alcohol and tobacco use disorders,¹⁵ especially given heightened possibility of unhealthy alcohol use and the respiratory complications associated with both tobacco and COVID-19.

5. Assess mental health and suicide risks¹⁹ given their association with social isolation, job loss, and financial insecurity.

6. Discuss relapse prevention among people in recovery.

7. Assess overdose risk and promote harm reduction.¹⁹ Specifically, this may include counseling patients to avoid sharing smoking supplies to avoid COVID-19 transmission, identifying places to access clean syringes, prescribing naloxone,²⁰ and providing supports so that, if patients need to use alone, they can do so more safely.²¹

8. Consider high-risk transitions that may be exacerbated by COVID-19. COVID-19 may make safe discharge plans among people experiencing homelessness very challenging. Some communities are rapidly repurposing existing spaces or building new ones to care for people without a safe place to recover after acute hospitalization, yet many communities have no such resources. Hospital teams should consider the possibility that community services and SUD treatment resources may change rapidly during the pandemic. Hospitals can maintain updated resource lists and consider partnering with state and local health departments to improve safe care for people experiencing homelessness or lacking basic services.

COVID-19 is putting enormous strain on many US hospitals. Hospital-based addictions care is under resourced in the best of times,¹⁴ and while some hospitals have addiction consult services, many do not. To what degree hospitalists and hospital teams can address anything beyond COVID-19 emergencies will vary based on settings and resources. Furthermore, we recognize that who performs various activities will depend on individual hospital’s resources and practices. Addiction consult services, if available, can play a critical role, as can hospital social workers and care managers, nurses, residents, students, and other members of the healthcare team.

Finally, though COVID-19 adds tremendous stress to hospitals, permanent improvements in SUD treatment systems such as telephone visits for buprenorphine or eased methadone restrictions may emerge that could reduce barriers to hospital-based addictions care.¹¹ Leveraging these changes now may help hospital providers to better support patients long-term.

Hospitalization can be a challenging time for patients with SUD and for the hospital teams who care for them. These tensions are exacerbated by the COVID-19 pandemic, yet hospitalists play a critical role in addressing the converging crises of SUD and COVID-19. Providing comprehensive, compassionate, evidence-based care for hospitalized patients with SUD is important for both individual and community health during COVID-19.

The authors would like to thank Alisa Patten for help preparing this manuscript.

The authors have no conflicts of interest to disclose.

Dr King received grant support from the National Institutes of Health (UG1DA015815) and the National Institute on Drug Abuse (R01DA037441). Dr Snyder received a Public Health Institute grant payable to her institution.

The spread of SARS-CoV-2, the pathogen behind the COVID-19 pandemic, has converged with an unrelenting addiction epidemic. These combined crises will have profound effects on people with substance use disorders (SUD) and people in recovery. Hospitals—which were already hit hard by the addiction epidemic—are the last line of defense in the COVID-19 pandemic. Hospitalists have an important role in balancing the effects of these intersecting, synergistic crises.

People with SUD are disproportionately affected by major medical illnesses, including infections such as hepatitis C, HIV, and cardiovascular, pulmonary, and liver diseases.¹ They also experience high rates of hospitalization due to drug-related infections, injury, and overdose.² People with SUD commonly have intersecting vulnerabilities that may affect their healthcare experience and health outcomes, including housing and food insecurity, mental illness, and experiences of racism, incarceration, and other trauma. They may also harbor mistrust of healthcare providers because of previous negative encounters and discrimination with health systems.³ These vulnerabilities increase risks for COVID-19 morbidity and mortality.^4,5 The COVID-19 pandemic may drive increases in use and harms from SUD among patients who already have an SUD, with widespread job loss, insurance loss,⁶ anxiety, and social isolation on the rise. We may also see increases in return to use among people in recovery or new substance use among those without a history of SUD.

The intersecting crises of SUD and COVID-19 are important for people with SUD and for public health. In this perspective, we describe how the COVID-19 pandemic has affected people with SUD and share practical resources for hospital providers to improve care for people with SUD during the pandemic and beyond.

Mistrust of Hospitals and Healthcare Providers

Fear of stigmatization is an ongoing problem for people with SUD, who often experience discrimination in hospitals and, as a result, may avoid hospital care.⁷ Much of this stigma is based on the false but persistent belief—widespread even among healthcare providers—that addiction is the result of bad choices and limited willpower; however, the science is clear that addiction is a disorder with neurobiological, genetic, and environmental underpinnings.³ These attitudes are likely to be amplified during COVID-19, as patients and providers experience higher levels of stress.

Increased Risks of Substance Use

Typically, people who use drugs are counseled to use with others nearby so that they might administer naloxone or call 911 in the event of an overdose.⁸ With physical distancing, people may be more likely to use alone. COVID-19 also introduces uncertainty into the drug supply chain through changes in drug production and trafficking.⁹ Further, access to alcohol may be limited as liquor stores close and public transportation becomes less available. As has been shown in other complex emergencies (such as social, political, economic, and environmental disasters), these barriers to obtaining substances may increase risks for withdrawal, for needing to exchange sex for money or drugs, for sharing syringes or drug preparation equipment,¹⁰ or for consuming other available sources of substances, like rubbing alcohol or hand sanitizer. COVID-19 may also increase risk for depression, anxiety, social isolation, and suicidality, all of which increase risk for return to use and overdose.

Changes to the Treatment Milieu

Many of the resources and services that people who use substances rely on to keep safe may be disrupted by COVID-19. Social distancing—the cornerstone of mitigating COVID-19 spread—may be challenging among people with SUD. Though federal regulations around methadone dispensing and buprenorphine prescribing have loosened in response to the pandemic,¹¹ individuals in treatment may still be required to provide urine drug screens or be physically present to receive methadone doses, sometimes daily and in crowded waiting rooms.

Recovery support groups such as Alcoholics Anonymous (AA) and Self-Management and Recovery Training (SMART) provide social connection and are the foundation of many people’s recovery. While many in-person meetings have rapidly transformed to online and telephone support, they remain inaccessible to the most marginalized members of communities: people without smart phones, computers, or internet. This digital shift may also disproportionately affect older adults, people with limited English proficiency, and people with low technological literacy. Limits for other resources, such as syringe service programs, community centers, food pantries, housing shelters, and other places that people depend on for clean water, food, showers, soap, and safer spaces to use, may limit services or close altogether; those that remain open may see an unprecedented rise in need for services as millions of Americans file for unemployment. For many, anxiety about the pandemic, unemployment, financial strain, increased isolation, family stressors, illness, and community losses can lead to enormous personal distress and trigger return to use; loss of a recovery network may further exacerbate this.

Intersectionality of SUD and Other Structural Inequities

Many of the inequities that increase people’s risk for undertreated SUD also increase risk for COVID-19 infection, including racism,¹² poverty, and homelessness.⁴ “Stay home and stay safe” is not an option for people who are unsheltered or whose homes are unsafe because of risks of physical, sexual, or emotional violence. Poverty commonly forces people to live in crowded communal apartments or shelters, rely on public transportation, wait in long lines at food pantries, and continue to work, even if unwell. Many shelters have had to reduce the number of people they serve to reduce crowding and support social distancing, which further compounds risks of unstable housing. Unfortunately, the same structural inequities that exacerbate SUD worsen the COVID-19 crisis.¹³

The intersecting vulnerabilities of SUD and COVID-19 heighten an already urgent need to address SUD among hospitalized patients.¹⁴ While COVID-19 may increase harms of substance use, it may also increase people’s readiness to engage in treatment given changes to the drug supply and patient’s concerns about health risks. As such, it is even more critical to make treatment readily accessible and support harm reduction. Hospitalists can take important, actionable steps for patients with SUD—many of which are good general practices¹⁴ (Appendix Table).

Hospitalists should do the following:

1. Identify and treat acute withdrawal.¹⁵

2. Manage acute pain, including providing high-dose opioids if needed.¹⁶ Both practices (1 and 2) are evidence-based, can promote patient’s trust in providers,¹⁷ and can help avoid patients leaving against medical advice (AMA). Leaving AMA can lead to poor individual health and further threaten public health if patients leave with undiagnosed or unmanaged COVID-19 infection.

3. Encourage their hospitals to provide patients with tablets or other means to communicate with family, friends, and recovery supports via videolink, and refer patients to virtual peer support and recovery meetings during hospitalization.¹⁸ These practices may further support patients in tolerating hospitalization and prevent AMA discharge.

4. Initiate medication for addiction during admission and refer to addictions treatment after discharge. COVID-19–related regulatory changes such as expanded telehealth buprenorphine options and fewer daily dosing requirements for methadone may make this easier. Further, hospitalists should offer medication for alcohol and tobacco use disorders,¹⁵ especially given heightened possibility of unhealthy alcohol use and the respiratory complications associated with both tobacco and COVID-19.

5. Assess mental health and suicide risks¹⁹ given their association with social isolation, job loss, and financial insecurity.

6. Discuss relapse prevention among people in recovery.

7. Assess overdose risk and promote harm reduction.¹⁹ Specifically, this may include counseling patients to avoid sharing smoking supplies to avoid COVID-19 transmission, identifying places to access clean syringes, prescribing naloxone,²⁰ and providing supports so that, if patients need to use alone, they can do so more safely.²¹

8. Consider high-risk transitions that may be exacerbated by COVID-19. COVID-19 may make safe discharge plans among people experiencing homelessness very challenging. Some communities are rapidly repurposing existing spaces or building new ones to care for people without a safe place to recover after acute hospitalization, yet many communities have no such resources. Hospital teams should consider the possibility that community services and SUD treatment resources may change rapidly during the pandemic. Hospitals can maintain updated resource lists and consider partnering with state and local health departments to improve safe care for people experiencing homelessness or lacking basic services.

COVID-19 is putting enormous strain on many US hospitals. Hospital-based addictions care is under resourced in the best of times,¹⁴ and while some hospitals have addiction consult services, many do not. To what degree hospitalists and hospital teams can address anything beyond COVID-19 emergencies will vary based on settings and resources. Furthermore, we recognize that who performs various activities will depend on individual hospital’s resources and practices. Addiction consult services, if available, can play a critical role, as can hospital social workers and care managers, nurses, residents, students, and other members of the healthcare team.

Finally, though COVID-19 adds tremendous stress to hospitals, permanent improvements in SUD treatment systems such as telephone visits for buprenorphine or eased methadone restrictions may emerge that could reduce barriers to hospital-based addictions care.¹¹ Leveraging these changes now may help hospital providers to better support patients long-term.

Hospitalization can be a challenging time for patients with SUD and for the hospital teams who care for them. These tensions are exacerbated by the COVID-19 pandemic, yet hospitalists play a critical role in addressing the converging crises of SUD and COVID-19. Providing comprehensive, compassionate, evidence-based care for hospitalized patients with SUD is important for both individual and community health during COVID-19.

The authors would like to thank Alisa Patten for help preparing this manuscript.

The authors have no conflicts of interest to disclose.

Dr King received grant support from the National Institutes of Health (UG1DA015815) and the National Institute on Drug Abuse (R01DA037441). Dr Snyder received a Public Health Institute grant payable to her institution.

Public health emergencies may require shifting from conventional to contingency and ultimately to crisis standards of care, which prompts consideration of needs and resources across hospital systems.^1,2 Within conventional care contexts, institutions have their usual resources including supplies, staff, and space and are able to provide a usual standard of care to patients. As institutions anticipate shortages in an emergency, they may enter a contingency state. In this state, the institution begins to plan for shortages, often by finding alternative uses of supplies, staff, and space that are functionally equivalent but still aiming to conserve resources such as rescheduling elective procedures and using alternative but functionally equivalent personal protective equipment. Still, during this state, institutions are able to provide the usual standard of care.

Under crisis standards of care, resources have reached a level of scarcity or circumstances are such that they do not permit normal operations. In this state, institutions may not be able to meet the usual standard of care. Instead, institutions are expected to provide care that is sufficient given available resources and circumstances. How to utilize scarce resources, however, invokes consideration of the ethical duties of institutions. Despite the likelihood of entering crisis standards of care (CSCs) in the current COVID-19 pandemic, limited ethical guidance exists regarding how institutions should relate to each other in a crisis. Relevant moral duties during conventional, contingency, and CSCs include duties of rescue, fidelity, solidarity, and justice. As CSCs develop, these duties require limiting elective procedures and instituting triage in certain circumstances, but how this relates to coordination among hospitals is unclear.

We argue that the primary role of pediatric institutions during the COVID-19 pandemic under CSCs is increasing system capacity by regionalization of pediatric care. Under regionalization of care, children’s hospitals that serve as local/regional referral centers would preferentially take all pediatric patients in the region, including those who might normally be admitted to a primarily adult hospital, thereby increasing availability of beds and resources at primarily adult facilities. This maximizes the expertise and resources of pediatric institutions and avoids unnecessary harm to all patients by mitigating shortages before any hospital faces conditions in which they need to invoke triage procedures. General hospitals should transfer pediatric patients to pediatric institutions and should consider transfer of patients and/or resources between regional institutions, which helps avoid triage conditions until all accessible resources are in use.

Institutions are prominent moral actors with duties to patients extending beyond those of providers.³

The duty to treat includes two subsidiary duties. First, the duty of rescue has a special role in emergencies, requiring providers to intervene with those helpless without assistance.^4-6 For children’s hospitals, this means providing care for children in the region who cannot receive needed care elsewhere. Second, the duty of fidelity requires promoting patients’ good, including giving precedence to patients with established treatment relationships.⁷

Institutions also have a duty of solidarity.⁸ Institutions must recognize they are bound together to care for the broader community and should work in tandem.⁹ Solidarity encompasses the duty of stewardship—responsibly using resources to mitigate shortages; this duty sometimes requires subsuming patient, provider, or institutional needs for overall community benefit.

Finally, institutions have duties of justice,² to provide fair and equitable care with transparency and trustworthiness. Justice requires that institutions ensure shifting to CSCs does not disfavor already disadvantaged groups.¹⁰

Public health emergencies strain health care resources in ways that hinder providing usual standards of care. Public health ethics guide healthcare systems during contingency or CSCs in ethically grounded approaches to mitigate shortages and allocate resources.^1,2 We consider how duties evolve from conventional care to CSCs, with a focus on actions to meet institutional duties under changing circumstances.

Conventional Care

Ordinarily, institutions provide usual standards of care, which follow typical operations. Interactions between institutions and providers rely on basic ethical principles, including primacy of patient welfare, autonomy, and social justice. A degree of redundancy allows institutions to meet duties of rescue, fidelity, solidarity, and justice even with increased demand. The duty to treat is primary but requires balancing duties to rescue with fiduciary duties. Thus, if the institution were near capacity and a decision is needed about which patient to accept in transfer, avoiding irreversible harm to a previously unknown patient who could not receive adequate care in the community should take precedence over accepting an established patient who could receive adequate care elsewhere. If neither patient could receive adequate care elsewhere, the patient known to the children’s hospital should be accepted, under the duty of fidelity. Fidelity also requires that patients currently admitted continue to receive treatment. Justice requires fair and equitable treatment of patients, without consideration of morally irrelevant features (eg, race or immigration status).

Contingency Care

Contingency care begins when a public health emergency introduces strains on hospital resources.^1,2,11 As long as typical or alternative resources last, adaptations in care have minimal effects on quality, and the duties of rescue, fidelity, and justice mirror conventional care; however, operations begin to shift to recognize greater duties of solidarity. In the COVID-19 pandemic, given their missions to provide specialized care for children, pediatric hospitals can meet their duty to treat by accepting patients who might otherwise receive care elsewhere. Children’s hospitals should consider accepting any child for which they have capacity to help decompress other systems (eg, liberating beds for more adults at other institutions). Children’s hospitals should also continue to preferentially admit children requiring tertiary care (eg, neonates requiring subspecialty surgery), which respects the duty of rescue.

The duty of solidarity supports strategic sharing and stewarding of resources, including personal protective equipment, ventilators, and staff. Strategies might include postponing elective procedures, repurposing facilities, or limiting staff entering isolation rooms; such alterations to standard care require careful discussions with providers to anticipate negative consequences, ensure safe practices, and plan for reassessment.

The duty of rescue requires maintaining ability to care for patients who cannot receive adequate care elsewhere. Institutions can meet this duty by reserving a small number of intensive care and general beds to care for patients needing emergent specialty care.

Crisis Standards of Care

Under CSCs, resources are insufficient to maintain usual standards of care and mitigation attempts no longer suffice. Scarcity demands greater duties of solidarity, reducing attention to some individuals to promote the community good. To meet duties of solidarity, institutions should prepare for triage after exhausting efforts to preserve system resources.

During a pandemic such as COVID-19 that primarily affects adults, pediatric resources should be consolidated by transferring children to regional pediatric facilities. Without transfer, children who present to primarily adult facilities, where resources are more strained given the higher burden of disease in adults, may otherwise be subject to triaging of scarce resources at the adult facility. But, no child should have care determined by any hospital’s triage system if any pediatric bed is available within a region, and if pediatric resources are regionalized, children will be less likely to face triage at primarily adult facilities unless the entire system has reached capacity. In addition to regionalization, children’s hospitals may also face requests to accept adult patients or share equipment and/or staff with adult facilities; when these actions do not compromise the capacity of the pediatric institution to provide care to children, institutions should consider them.¹² However, pediatric institutions can best meet the duty of solidarity by expanding regional capacity through freeing up resources in general hospitals, including beds, ventilators, and staffing usable for adults, preventing all hospitals from needing to triage. If triage is necessary because the entire system has reached capacity, triage should also take place at children’s hospitals, in respect of solidarity, to optimize this community resource.

Under CSCs, significant practice variation in triage policies may occur. Regional institutions may individually employ triage policies during crisis standards of care and deny critical care resources to some individuals who might receive them in noncrisis times, when there isn’t such scarcity. Minimizing denials across a region requires collaboration between centers to ensure solidarity. Processes should be fair and equitable. Justice entails ensuring consistency in allocation criteria, with differences prioritizing those least well off. Triage teams in a region should use consistent, aligned processes so that similarly situated patients have equitable access to resources and care across centers. However, triaging pediatric and adult patients together could disadvantage children (eg, priority given to health workers); moreover, illness severity measures for infants/children differ from those applicable to adults, which makes equivalent scoring for allocation challenging.¹³ Some resources are specific to pediatric or adult care. Therefore, it may be necessary to separate pediatric and adult allocation processes.

Triage criteria must not discriminate based on morally irrelevant criteria, such as sex, race/ethnicity, or disability.¹ Institutions using “objective” scoring systems for morbidity and mortality should acknowledge that these systems could disadvantage marginalized populations with higher rates of chronic conditions resulting from systemic inequities.

A commitment to justice mandates that no patient should be triaged if the required resources (eg, ventilators) are available at a regional hospital and transfer is feasible. Transfer should occur across all regional hospitals, not just partners within hospital networks. Facilitating transfers requires institutions to engage in close communication. If no centralized external system exists, a group of individuals with knowledge of inpatient resources—but without direct care duties—should provide coordination.

Because CSCs are so different from conventional standards, institutions should collect data on regionalization and triage protocols. Recognition of inequitable outcomes may necessitate changing scoring criteria or reveal disproportionate burdens on vulnerable populations.

To maintain public trust and promote justice, institutions must be transparent regarding triage policies and procedures for CSCs. These should be available for public review, revised with public input, and readily available once finalized.

Despite the ethical justification for regional coordination of care and resources, there are multiple barriers to implementation. Providers and families may hesitate to disturb continuity of care at medical homes. Organizations may have financial disincentives to transfer long-term patients to new institutions. Openness with patients and families regarding the temporary nature of transfers and plans to return to their usual care may help. Granting temporary privileges at recipient institutions for providers to continue seeing their patients may lessen discontinuity. Solidarity in public health emergencies requires all institutions to compromise their own interests to some degree.

Similarly, barriers in achieving consistency across institutional triage policies may arise. Allocation strategies embody multiple values, for example, regarding quality of life or contributions of essential workers. Resolution of these value differences may prove difficult.

In the current COVID-19 pandemic, an ethical approach to CSCs necessitates coordination to align available resources at the regional, rather than institutional, level to avoid triage at individual institutions. Pediatric regionalization of care is the first step in freeing up system capacity for adults. Solidarity rises in importance, but must be balanced by duties of rescue, fidelity, and justice so that pediatric institutions continue to care for children with urgent needs requiring pediatric expertise.

Dr Paquette reported funding under the Pediatric Critical Care and Trauma Scientist Development Program, NICHD K12HDO47349 and NICHD Loan Repayment Program L40 HD089260. Dr Derrington is a director at large for the American Society of Bioethics and Medical Humanities and had travel expenses reimbursed for the annual conference in 2019. Dr Michelson has received funding from the National Palliative Care Research Center and is a consultant on a National Institutes of Health study that are unrelated to this work. Dr Michelson is also involved in unrelated work supported by the National Alliance for Grieving Children. All other authors declared they have nothing to disclose.

Public health emergencies may require shifting from conventional to contingency and ultimately to crisis standards of care, which prompts consideration of needs and resources across hospital systems.^1,2 Within conventional care contexts, institutions have their usual resources including supplies, staff, and space and are able to provide a usual standard of care to patients. As institutions anticipate shortages in an emergency, they may enter a contingency state. In this state, the institution begins to plan for shortages, often by finding alternative uses of supplies, staff, and space that are functionally equivalent but still aiming to conserve resources such as rescheduling elective procedures and using alternative but functionally equivalent personal protective equipment. Still, during this state, institutions are able to provide the usual standard of care.

Under crisis standards of care, resources have reached a level of scarcity or circumstances are such that they do not permit normal operations. In this state, institutions may not be able to meet the usual standard of care. Instead, institutions are expected to provide care that is sufficient given available resources and circumstances. How to utilize scarce resources, however, invokes consideration of the ethical duties of institutions. Despite the likelihood of entering crisis standards of care (CSCs) in the current COVID-19 pandemic, limited ethical guidance exists regarding how institutions should relate to each other in a crisis. Relevant moral duties during conventional, contingency, and CSCs include duties of rescue, fidelity, solidarity, and justice. As CSCs develop, these duties require limiting elective procedures and instituting triage in certain circumstances, but how this relates to coordination among hospitals is unclear.

We argue that the primary role of pediatric institutions during the COVID-19 pandemic under CSCs is increasing system capacity by regionalization of pediatric care. Under regionalization of care, children’s hospitals that serve as local/regional referral centers would preferentially take all pediatric patients in the region, including those who might normally be admitted to a primarily adult hospital, thereby increasing availability of beds and resources at primarily adult facilities. This maximizes the expertise and resources of pediatric institutions and avoids unnecessary harm to all patients by mitigating shortages before any hospital faces conditions in which they need to invoke triage procedures. General hospitals should transfer pediatric patients to pediatric institutions and should consider transfer of patients and/or resources between regional institutions, which helps avoid triage conditions until all accessible resources are in use.

Institutions are prominent moral actors with duties to patients extending beyond those of providers.³

The duty to treat includes two subsidiary duties. First, the duty of rescue has a special role in emergencies, requiring providers to intervene with those helpless without assistance.^4-6 For children’s hospitals, this means providing care for children in the region who cannot receive needed care elsewhere. Second, the duty of fidelity requires promoting patients’ good, including giving precedence to patients with established treatment relationships.⁷

Institutions also have a duty of solidarity.⁸ Institutions must recognize they are bound together to care for the broader community and should work in tandem.⁹ Solidarity encompasses the duty of stewardship—responsibly using resources to mitigate shortages; this duty sometimes requires subsuming patient, provider, or institutional needs for overall community benefit.

Finally, institutions have duties of justice,² to provide fair and equitable care with transparency and trustworthiness. Justice requires that institutions ensure shifting to CSCs does not disfavor already disadvantaged groups.¹⁰

Public health emergencies strain health care resources in ways that hinder providing usual standards of care. Public health ethics guide healthcare systems during contingency or CSCs in ethically grounded approaches to mitigate shortages and allocate resources.^1,2 We consider how duties evolve from conventional care to CSCs, with a focus on actions to meet institutional duties under changing circumstances.

Conventional Care

Ordinarily, institutions provide usual standards of care, which follow typical operations. Interactions between institutions and providers rely on basic ethical principles, including primacy of patient welfare, autonomy, and social justice. A degree of redundancy allows institutions to meet duties of rescue, fidelity, solidarity, and justice even with increased demand. The duty to treat is primary but requires balancing duties to rescue with fiduciary duties. Thus, if the institution were near capacity and a decision is needed about which patient to accept in transfer, avoiding irreversible harm to a previously unknown patient who could not receive adequate care in the community should take precedence over accepting an established patient who could receive adequate care elsewhere. If neither patient could receive adequate care elsewhere, the patient known to the children’s hospital should be accepted, under the duty of fidelity. Fidelity also requires that patients currently admitted continue to receive treatment. Justice requires fair and equitable treatment of patients, without consideration of morally irrelevant features (eg, race or immigration status).

Contingency Care

Contingency care begins when a public health emergency introduces strains on hospital resources.^1,2,11 As long as typical or alternative resources last, adaptations in care have minimal effects on quality, and the duties of rescue, fidelity, and justice mirror conventional care; however, operations begin to shift to recognize greater duties of solidarity. In the COVID-19 pandemic, given their missions to provide specialized care for children, pediatric hospitals can meet their duty to treat by accepting patients who might otherwise receive care elsewhere. Children’s hospitals should consider accepting any child for which they have capacity to help decompress other systems (eg, liberating beds for more adults at other institutions). Children’s hospitals should also continue to preferentially admit children requiring tertiary care (eg, neonates requiring subspecialty surgery), which respects the duty of rescue.

The duty of solidarity supports strategic sharing and stewarding of resources, including personal protective equipment, ventilators, and staff. Strategies might include postponing elective procedures, repurposing facilities, or limiting staff entering isolation rooms; such alterations to standard care require careful discussions with providers to anticipate negative consequences, ensure safe practices, and plan for reassessment.

The duty of rescue requires maintaining ability to care for patients who cannot receive adequate care elsewhere. Institutions can meet this duty by reserving a small number of intensive care and general beds to care for patients needing emergent specialty care.

Crisis Standards of Care

Under CSCs, resources are insufficient to maintain usual standards of care and mitigation attempts no longer suffice. Scarcity demands greater duties of solidarity, reducing attention to some individuals to promote the community good. To meet duties of solidarity, institutions should prepare for triage after exhausting efforts to preserve system resources.

During a pandemic such as COVID-19 that primarily affects adults, pediatric resources should be consolidated by transferring children to regional pediatric facilities. Without transfer, children who present to primarily adult facilities, where resources are more strained given the higher burden of disease in adults, may otherwise be subject to triaging of scarce resources at the adult facility. But, no child should have care determined by any hospital’s triage system if any pediatric bed is available within a region, and if pediatric resources are regionalized, children will be less likely to face triage at primarily adult facilities unless the entire system has reached capacity. In addition to regionalization, children’s hospitals may also face requests to accept adult patients or share equipment and/or staff with adult facilities; when these actions do not compromise the capacity of the pediatric institution to provide care to children, institutions should consider them.¹² However, pediatric institutions can best meet the duty of solidarity by expanding regional capacity through freeing up resources in general hospitals, including beds, ventilators, and staffing usable for adults, preventing all hospitals from needing to triage. If triage is necessary because the entire system has reached capacity, triage should also take place at children’s hospitals, in respect of solidarity, to optimize this community resource.

Under CSCs, significant practice variation in triage policies may occur. Regional institutions may individually employ triage policies during crisis standards of care and deny critical care resources to some individuals who might receive them in noncrisis times, when there isn’t such scarcity. Minimizing denials across a region requires collaboration between centers to ensure solidarity. Processes should be fair and equitable. Justice entails ensuring consistency in allocation criteria, with differences prioritizing those least well off. Triage teams in a region should use consistent, aligned processes so that similarly situated patients have equitable access to resources and care across centers. However, triaging pediatric and adult patients together could disadvantage children (eg, priority given to health workers); moreover, illness severity measures for infants/children differ from those applicable to adults, which makes equivalent scoring for allocation challenging.¹³ Some resources are specific to pediatric or adult care. Therefore, it may be necessary to separate pediatric and adult allocation processes.

Triage criteria must not discriminate based on morally irrelevant criteria, such as sex, race/ethnicity, or disability.¹ Institutions using “objective” scoring systems for morbidity and mortality should acknowledge that these systems could disadvantage marginalized populations with higher rates of chronic conditions resulting from systemic inequities.

A commitment to justice mandates that no patient should be triaged if the required resources (eg, ventilators) are available at a regional hospital and transfer is feasible. Transfer should occur across all regional hospitals, not just partners within hospital networks. Facilitating transfers requires institutions to engage in close communication. If no centralized external system exists, a group of individuals with knowledge of inpatient resources—but without direct care duties—should provide coordination.

Because CSCs are so different from conventional standards, institutions should collect data on regionalization and triage protocols. Recognition of inequitable outcomes may necessitate changing scoring criteria or reveal disproportionate burdens on vulnerable populations.

To maintain public trust and promote justice, institutions must be transparent regarding triage policies and procedures for CSCs. These should be available for public review, revised with public input, and readily available once finalized.

Despite the ethical justification for regional coordination of care and resources, there are multiple barriers to implementation. Providers and families may hesitate to disturb continuity of care at medical homes. Organizations may have financial disincentives to transfer long-term patients to new institutions. Openness with patients and families regarding the temporary nature of transfers and plans to return to their usual care may help. Granting temporary privileges at recipient institutions for providers to continue seeing their patients may lessen discontinuity. Solidarity in public health emergencies requires all institutions to compromise their own interests to some degree.

Similarly, barriers in achieving consistency across institutional triage policies may arise. Allocation strategies embody multiple values, for example, regarding quality of life or contributions of essential workers. Resolution of these value differences may prove difficult.

In the current COVID-19 pandemic, an ethical approach to CSCs necessitates coordination to align available resources at the regional, rather than institutional, level to avoid triage at individual institutions. Pediatric regionalization of care is the first step in freeing up system capacity for adults. Solidarity rises in importance, but must be balanced by duties of rescue, fidelity, and justice so that pediatric institutions continue to care for children with urgent needs requiring pediatric expertise.

Dr Paquette reported funding under the Pediatric Critical Care and Trauma Scientist Development Program, NICHD K12HDO47349 and NICHD Loan Repayment Program L40 HD089260. Dr Derrington is a director at large for the American Society of Bioethics and Medical Humanities and had travel expenses reimbursed for the annual conference in 2019. Dr Michelson has received funding from the National Palliative Care Research Center and is a consultant on a National Institutes of Health study that are unrelated to this work. Dr Michelson is also involved in unrelated work supported by the National Alliance for Grieving Children. All other authors declared they have nothing to disclose.

Public health emergencies may require shifting from conventional to contingency and ultimately to crisis standards of care, which prompts consideration of needs and resources across hospital systems.^1,2 Within conventional care contexts, institutions have their usual resources including supplies, staff, and space and are able to provide a usual standard of care to patients. As institutions anticipate shortages in an emergency, they may enter a contingency state. In this state, the institution begins to plan for shortages, often by finding alternative uses of supplies, staff, and space that are functionally equivalent but still aiming to conserve resources such as rescheduling elective procedures and using alternative but functionally equivalent personal protective equipment. Still, during this state, institutions are able to provide the usual standard of care.

Under crisis standards of care, resources have reached a level of scarcity or circumstances are such that they do not permit normal operations. In this state, institutions may not be able to meet the usual standard of care. Instead, institutions are expected to provide care that is sufficient given available resources and circumstances. How to utilize scarce resources, however, invokes consideration of the ethical duties of institutions. Despite the likelihood of entering crisis standards of care (CSCs) in the current COVID-19 pandemic, limited ethical guidance exists regarding how institutions should relate to each other in a crisis. Relevant moral duties during conventional, contingency, and CSCs include duties of rescue, fidelity, solidarity, and justice. As CSCs develop, these duties require limiting elective procedures and instituting triage in certain circumstances, but how this relates to coordination among hospitals is unclear.

We argue that the primary role of pediatric institutions during the COVID-19 pandemic under CSCs is increasing system capacity by regionalization of pediatric care. Under regionalization of care, children’s hospitals that serve as local/regional referral centers would preferentially take all pediatric patients in the region, including those who might normally be admitted to a primarily adult hospital, thereby increasing availability of beds and resources at primarily adult facilities. This maximizes the expertise and resources of pediatric institutions and avoids unnecessary harm to all patients by mitigating shortages before any hospital faces conditions in which they need to invoke triage procedures. General hospitals should transfer pediatric patients to pediatric institutions and should consider transfer of patients and/or resources between regional institutions, which helps avoid triage conditions until all accessible resources are in use.

Institutions are prominent moral actors with duties to patients extending beyond those of providers.³

The duty to treat includes two subsidiary duties. First, the duty of rescue has a special role in emergencies, requiring providers to intervene with those helpless without assistance.^4-6 For children’s hospitals, this means providing care for children in the region who cannot receive needed care elsewhere. Second, the duty of fidelity requires promoting patients’ good, including giving precedence to patients with established treatment relationships.⁷

Institutions also have a duty of solidarity.⁸ Institutions must recognize they are bound together to care for the broader community and should work in tandem.⁹ Solidarity encompasses the duty of stewardship—responsibly using resources to mitigate shortages; this duty sometimes requires subsuming patient, provider, or institutional needs for overall community benefit.

Finally, institutions have duties of justice,² to provide fair and equitable care with transparency and trustworthiness. Justice requires that institutions ensure shifting to CSCs does not disfavor already disadvantaged groups.¹⁰

Public health emergencies strain health care resources in ways that hinder providing usual standards of care. Public health ethics guide healthcare systems during contingency or CSCs in ethically grounded approaches to mitigate shortages and allocate resources.^1,2 We consider how duties evolve from conventional care to CSCs, with a focus on actions to meet institutional duties under changing circumstances.

Conventional Care

Ordinarily, institutions provide usual standards of care, which follow typical operations. Interactions between institutions and providers rely on basic ethical principles, including primacy of patient welfare, autonomy, and social justice. A degree of redundancy allows institutions to meet duties of rescue, fidelity, solidarity, and justice even with increased demand. The duty to treat is primary but requires balancing duties to rescue with fiduciary duties. Thus, if the institution were near capacity and a decision is needed about which patient to accept in transfer, avoiding irreversible harm to a previously unknown patient who could not receive adequate care in the community should take precedence over accepting an established patient who could receive adequate care elsewhere. If neither patient could receive adequate care elsewhere, the patient known to the children’s hospital should be accepted, under the duty of fidelity. Fidelity also requires that patients currently admitted continue to receive treatment. Justice requires fair and equitable treatment of patients, without consideration of morally irrelevant features (eg, race or immigration status).

Contingency Care

Contingency care begins when a public health emergency introduces strains on hospital resources.^1,2,11 As long as typical or alternative resources last, adaptations in care have minimal effects on quality, and the duties of rescue, fidelity, and justice mirror conventional care; however, operations begin to shift to recognize greater duties of solidarity. In the COVID-19 pandemic, given their missions to provide specialized care for children, pediatric hospitals can meet their duty to treat by accepting patients who might otherwise receive care elsewhere. Children’s hospitals should consider accepting any child for which they have capacity to help decompress other systems (eg, liberating beds for more adults at other institutions). Children’s hospitals should also continue to preferentially admit children requiring tertiary care (eg, neonates requiring subspecialty surgery), which respects the duty of rescue.

The duty of solidarity supports strategic sharing and stewarding of resources, including personal protective equipment, ventilators, and staff. Strategies might include postponing elective procedures, repurposing facilities, or limiting staff entering isolation rooms; such alterations to standard care require careful discussions with providers to anticipate negative consequences, ensure safe practices, and plan for reassessment.

The duty of rescue requires maintaining ability to care for patients who cannot receive adequate care elsewhere. Institutions can meet this duty by reserving a small number of intensive care and general beds to care for patients needing emergent specialty care.

Crisis Standards of Care

Under CSCs, resources are insufficient to maintain usual standards of care and mitigation attempts no longer suffice. Scarcity demands greater duties of solidarity, reducing attention to some individuals to promote the community good. To meet duties of solidarity, institutions should prepare for triage after exhausting efforts to preserve system resources.

During a pandemic such as COVID-19 that primarily affects adults, pediatric resources should be consolidated by transferring children to regional pediatric facilities. Without transfer, children who present to primarily adult facilities, where resources are more strained given the higher burden of disease in adults, may otherwise be subject to triaging of scarce resources at the adult facility. But, no child should have care determined by any hospital’s triage system if any pediatric bed is available within a region, and if pediatric resources are regionalized, children will be less likely to face triage at primarily adult facilities unless the entire system has reached capacity. In addition to regionalization, children’s hospitals may also face requests to accept adult patients or share equipment and/or staff with adult facilities; when these actions do not compromise the capacity of the pediatric institution to provide care to children, institutions should consider them.¹² However, pediatric institutions can best meet the duty of solidarity by expanding regional capacity through freeing up resources in general hospitals, including beds, ventilators, and staffing usable for adults, preventing all hospitals from needing to triage. If triage is necessary because the entire system has reached capacity, triage should also take place at children’s hospitals, in respect of solidarity, to optimize this community resource.

Under CSCs, significant practice variation in triage policies may occur. Regional institutions may individually employ triage policies during crisis standards of care and deny critical care resources to some individuals who might receive them in noncrisis times, when there isn’t such scarcity. Minimizing denials across a region requires collaboration between centers to ensure solidarity. Processes should be fair and equitable. Justice entails ensuring consistency in allocation criteria, with differences prioritizing those least well off. Triage teams in a region should use consistent, aligned processes so that similarly situated patients have equitable access to resources and care across centers. However, triaging pediatric and adult patients together could disadvantage children (eg, priority given to health workers); moreover, illness severity measures for infants/children differ from those applicable to adults, which makes equivalent scoring for allocation challenging.¹³ Some resources are specific to pediatric or adult care. Therefore, it may be necessary to separate pediatric and adult allocation processes.

Triage criteria must not discriminate based on morally irrelevant criteria, such as sex, race/ethnicity, or disability.¹ Institutions using “objective” scoring systems for morbidity and mortality should acknowledge that these systems could disadvantage marginalized populations with higher rates of chronic conditions resulting from systemic inequities.

A commitment to justice mandates that no patient should be triaged if the required resources (eg, ventilators) are available at a regional hospital and transfer is feasible. Transfer should occur across all regional hospitals, not just partners within hospital networks. Facilitating transfers requires institutions to engage in close communication. If no centralized external system exists, a group of individuals with knowledge of inpatient resources—but without direct care duties—should provide coordination.

Because CSCs are so different from conventional standards, institutions should collect data on regionalization and triage protocols. Recognition of inequitable outcomes may necessitate changing scoring criteria or reveal disproportionate burdens on vulnerable populations.

To maintain public trust and promote justice, institutions must be transparent regarding triage policies and procedures for CSCs. These should be available for public review, revised with public input, and readily available once finalized.

Despite the ethical justification for regional coordination of care and resources, there are multiple barriers to implementation. Providers and families may hesitate to disturb continuity of care at medical homes. Organizations may have financial disincentives to transfer long-term patients to new institutions. Openness with patients and families regarding the temporary nature of transfers and plans to return to their usual care may help. Granting temporary privileges at recipient institutions for providers to continue seeing their patients may lessen discontinuity. Solidarity in public health emergencies requires all institutions to compromise their own interests to some degree.

Similarly, barriers in achieving consistency across institutional triage policies may arise. Allocation strategies embody multiple values, for example, regarding quality of life or contributions of essential workers. Resolution of these value differences may prove difficult.

In the current COVID-19 pandemic, an ethical approach to CSCs necessitates coordination to align available resources at the regional, rather than institutional, level to avoid triage at individual institutions. Pediatric regionalization of care is the first step in freeing up system capacity for adults. Solidarity rises in importance, but must be balanced by duties of rescue, fidelity, and justice so that pediatric institutions continue to care for children with urgent needs requiring pediatric expertise.

Dr Paquette reported funding under the Pediatric Critical Care and Trauma Scientist Development Program, NICHD K12HDO47349 and NICHD Loan Repayment Program L40 HD089260. Dr Derrington is a director at large for the American Society of Bioethics and Medical Humanities and had travel expenses reimbursed for the annual conference in 2019. Dr Michelson has received funding from the National Palliative Care Research Center and is a consultant on a National Institutes of Health study that are unrelated to this work. Dr Michelson is also involved in unrelated work supported by the National Alliance for Grieving Children. All other authors declared they have nothing to disclose.