Many US health care systems experienced a surge of critically ill corona virus disease 2019 (COVID-19) patients while lacking adequate resources to provide optimal care. Nurses, doctors, and other providers in the United States were confronted with having to implement crisis standards of care for the first time. The refrain “these are unprecedented times” was repeated to colleagues and patients. The demands and shortages of supplies are unique in recent history. As a result, many frontline responders have wrestled with moral distress, the feelings of distress experienced when forced to act—because of institutional or resource constraints—in a manner contrary to their beliefs.¹ However, for those medical professionals whose work includes being deployed on global disaster response teams or providing healthcare in chronically low-resourced settings, navigating limitations of medicines, equipment, and personnel is a daily reality. We offer a framework for recognizing one’s own moral distress and that of one’s colleagues based on our experiences in global disaster response that may be helpful for clinicians during the COVID-19 pandemic.

The intense and debilitating feelings of unexpected loss and helplessness faced by clinicians who are making challenging choices about medical interventions can be better understood by applying a theoretical framework that has the following three main stages in the evolution and response to moral distress: indignation, resignation, and acclimation. This framework can provide guidance to individuals experiencing distress during the COVID-19 pandemic and may also be beneficial in contextualizing interactions when working in teams or with referring providers.

Indignation

When working in a disaster setting, an initial period of indignation is common. The clinician is shocked and horrified by the conditions encountered, the severity of suffering, and a lack of resources with which they are unaccustomed. As we bear witness to the many healthcare providers who have fallen ill and died, we fear for our own safety in choosing to care for patients sick with COVID: “I’m risking my life caring for patients on the front lines, and it’s unacceptable that I’m not even being provided with adequate PPE!” Patients and families are suffering in ways we had previously thought our health system was capable of addressing: “How can I be a compassionate clinician when my patients are forced to die alone?!” It feels surreal and unacceptable that so many patients can die so quickly despite our heroic interventions and that we have very little control over their fate. We are unaccustomed to caring for so many dying patients at once. For example, during the peak of the pandemic in New York City, patients were dying at four times the city’s normal death rate.² Indignation may be compounded in settings where providers are not even equipped to deal with the aftermath of deaths, such as piling bodies into makeshift morgues²: “I feel powerless to prevent my patients’ deaths and horrified that many are dying alone and scared, and now I can’t even guarantee that their bodies will be cared for after death!” Additionally, during this pandemic, many of us are now facing issues of resource allocation that we had never imagined dealing with. “I took an oath to care for and protect my patients. How could I possibly tell a patient we have no more ventilators to put them on? Who makes the decision of which patients deserve to live or die?” With the realization that COVID-19 has been disproportionately affecting racial and ethnic minorities, concerns for systemic discrimination within our healthcare system may rightly lead to a deep indignation.³

Resignation

After the initial indignation stage, resignation often follows. “I guess I can’t fix healthcare in this new setting, and I was foolish for even trying.” Clinicians go through the motions and continue to care for patients but feel disillusioned. Part of the ongoing stress involves the concern that they aren’t making a difference. Lack of viral testing may breed further resignation: Clinicians are on the front lines caring for patients that they are not even sure are positive for COVID-19, they have no way of accessing antibody testing for themselves to be able to gauge their own personal risks, and when there is not enough testing being done on a larger scale, there may be a sense that, by continuing to work on the front lines, they are sticking their finger in the dike, without actually having data to inform when it is safe to reopen states and ease restrictions. The suffering of patients and families may feel overwhelming and insurmountable. “I know I have to comply with my hospital’s visitor restriction policies, but it’s hard to see my patients suffering alone and know there’s nothing I can do to help them.”

Acclimation

Acclimation follows the indignation and resignation stages. Even amid disasters, a productive rhythm develops as teams coalesce and are galvanized by a shared sense of purpose. Clinicians make meaning out of their role in the crisis and in the care of the patients they can help, despite often deep and significant obstacles. “There’s a lot of suffering and a lot that I may not be able to fix, but some that I can.” Clinicians that have been deployed to unfamiliar roles may start to habituate and even enjoy having responsibilities and challenges that are different from those they typically face. Innovation during a pandemic may feel empowering. “I’m committed to making sure my dying patients and their families can say goodbye however possible. Although it’s not ideal, I’ve been using technology for virtual communication and advocating for families to visit in person when possible.”

One’s path of moral distress through a disaster may not be linear; one does not necessarily progress through the stages of indignation, resignation, and acclimation in a certain order or at a certain pace. Additionally, the stages can recur throughout the disaster. Being able to recognize these stages may prove useful for the duration of this pandemic while waves of providers are redeployed in new settings and experience fresh indignation, whereas others who have been in the trenches for some time may be more likely experiencing resignation or, hopefully, acclimation. The trajectory and duration of this pandemic in the United States remains unclear. While hot spots such as Seattle, New York, and Boston may be moving past their peak phase and acclimating to a “new normal,” there remain concerns that surges may recur in the fall and winter, which will undoubtedly lead battle-weary clinicians to experience the stages of moral distress anew and potentially compounding their distress.

An added complexity in this pandemic is that we, as clinicians, are both the victims and the healers. From the literature on disaster mental health, we know that emotional suffering is universal in affected populations.^4,5 Unlike many disaster scenarios in which teams leave the safety and security of well-established and well-resourced practices to deploy and care for disaster victims in new, austere environments, we are also part of that affected population in this pandemic. Each day or night, we return to homes that, too, are infiltrated by this pandemic. Our ability to move through the indignation, resignation, and acclimation stages may be hindered and blocked by our home responsibilities, stressors, and supports. Having to reconcile working in COVID-affected hospitals (particularly if caring for critically ill colleagues) only to return home to young or immunocompromised family members at night may place us in a state of indignation with its continued risk of burnout for the duration of this pandemic. Naming and acknowledging these painful challenges may allow self-compassion, self-forgiveness, and acceptance.

Though the primary focus of this article is to provide a framework to assist with the recognition of moral distress, it is important to address next steps once one recognizes someone is experiencing moral distress in this pandemic. Even outside of a disaster scenario, many clinicians feel obligated to put our patients’ needs before our own, and this sentiment is only heightened in a disaster scenario. It may feel unthinkable to call out sick or request a leave or reassignment during the pandemic. However, we are reminded that “the duty to serve is not endless.”⁶ Recognizing one’s own limits and reaching out to supervisors and mental health support before reaching one’s own limit is essential when experiencing moral distress.^7,8

Cultivating resilience is also recognized as a tool for managing moral distress.^6,9 For harried frontline clinicians, this may be as simple as taking a few minutes each night to journal three good things that occurred during the day.¹⁰ Mindfulness-­based stress reduction has also been found to decrease perceptions of moral distress,⁹ and many mindfulness programs (such as Headspace®, a mindfulness and meditation app¹¹) currently offer free membership to frontline providers during the pandemic. Mindfulness may be a particularly useful tool to leverage when one is stuck in the resignation phase and experiencing moral residue, described as a buildup of unresolved conflicts within the clinician that may crescendo with unresolved or inadequately resolved moral distress.^6,12 Lastly, the American Association of Critical Care Nurses Ethics Workgroup developed the 4 A’s to Rise Above Moral Distress, which provides a framework of 4 concrete steps: ask appropriate questions, affirm your distress and your commitment to take care of yourself, assess or identify sources of your distress, and act or take action.¹³

Providers may experience moral distress in times of disaster. In applying this framework, we can gain self-insight and compassion, understand the types of moral distress our colleagues may be experiencing, and explore concrete tools for managing moral distress. Just as we confront the suffering of our COVID-positive patients, so too may we benefit from sitting with and naming our own suffering and moral distress.

The authors have nothing to disclose.

Many US health care systems experienced a surge of critically ill corona virus disease 2019 (COVID-19) patients while lacking adequate resources to provide optimal care. Nurses, doctors, and other providers in the United States were confronted with having to implement crisis standards of care for the first time. The refrain “these are unprecedented times” was repeated to colleagues and patients. The demands and shortages of supplies are unique in recent history. As a result, many frontline responders have wrestled with moral distress, the feelings of distress experienced when forced to act—because of institutional or resource constraints—in a manner contrary to their beliefs.¹ However, for those medical professionals whose work includes being deployed on global disaster response teams or providing healthcare in chronically low-resourced settings, navigating limitations of medicines, equipment, and personnel is a daily reality. We offer a framework for recognizing one’s own moral distress and that of one’s colleagues based on our experiences in global disaster response that may be helpful for clinicians during the COVID-19 pandemic.

The intense and debilitating feelings of unexpected loss and helplessness faced by clinicians who are making challenging choices about medical interventions can be better understood by applying a theoretical framework that has the following three main stages in the evolution and response to moral distress: indignation, resignation, and acclimation. This framework can provide guidance to individuals experiencing distress during the COVID-19 pandemic and may also be beneficial in contextualizing interactions when working in teams or with referring providers.

Indignation

When working in a disaster setting, an initial period of indignation is common. The clinician is shocked and horrified by the conditions encountered, the severity of suffering, and a lack of resources with which they are unaccustomed. As we bear witness to the many healthcare providers who have fallen ill and died, we fear for our own safety in choosing to care for patients sick with COVID: “I’m risking my life caring for patients on the front lines, and it’s unacceptable that I’m not even being provided with adequate PPE!” Patients and families are suffering in ways we had previously thought our health system was capable of addressing: “How can I be a compassionate clinician when my patients are forced to die alone?!” It feels surreal and unacceptable that so many patients can die so quickly despite our heroic interventions and that we have very little control over their fate. We are unaccustomed to caring for so many dying patients at once. For example, during the peak of the pandemic in New York City, patients were dying at four times the city’s normal death rate.² Indignation may be compounded in settings where providers are not even equipped to deal with the aftermath of deaths, such as piling bodies into makeshift morgues²: “I feel powerless to prevent my patients’ deaths and horrified that many are dying alone and scared, and now I can’t even guarantee that their bodies will be cared for after death!” Additionally, during this pandemic, many of us are now facing issues of resource allocation that we had never imagined dealing with. “I took an oath to care for and protect my patients. How could I possibly tell a patient we have no more ventilators to put them on? Who makes the decision of which patients deserve to live or die?” With the realization that COVID-19 has been disproportionately affecting racial and ethnic minorities, concerns for systemic discrimination within our healthcare system may rightly lead to a deep indignation.³

Resignation

After the initial indignation stage, resignation often follows. “I guess I can’t fix healthcare in this new setting, and I was foolish for even trying.” Clinicians go through the motions and continue to care for patients but feel disillusioned. Part of the ongoing stress involves the concern that they aren’t making a difference. Lack of viral testing may breed further resignation: Clinicians are on the front lines caring for patients that they are not even sure are positive for COVID-19, they have no way of accessing antibody testing for themselves to be able to gauge their own personal risks, and when there is not enough testing being done on a larger scale, there may be a sense that, by continuing to work on the front lines, they are sticking their finger in the dike, without actually having data to inform when it is safe to reopen states and ease restrictions. The suffering of patients and families may feel overwhelming and insurmountable. “I know I have to comply with my hospital’s visitor restriction policies, but it’s hard to see my patients suffering alone and know there’s nothing I can do to help them.”

Acclimation

Acclimation follows the indignation and resignation stages. Even amid disasters, a productive rhythm develops as teams coalesce and are galvanized by a shared sense of purpose. Clinicians make meaning out of their role in the crisis and in the care of the patients they can help, despite often deep and significant obstacles. “There’s a lot of suffering and a lot that I may not be able to fix, but some that I can.” Clinicians that have been deployed to unfamiliar roles may start to habituate and even enjoy having responsibilities and challenges that are different from those they typically face. Innovation during a pandemic may feel empowering. “I’m committed to making sure my dying patients and their families can say goodbye however possible. Although it’s not ideal, I’ve been using technology for virtual communication and advocating for families to visit in person when possible.”

One’s path of moral distress through a disaster may not be linear; one does not necessarily progress through the stages of indignation, resignation, and acclimation in a certain order or at a certain pace. Additionally, the stages can recur throughout the disaster. Being able to recognize these stages may prove useful for the duration of this pandemic while waves of providers are redeployed in new settings and experience fresh indignation, whereas others who have been in the trenches for some time may be more likely experiencing resignation or, hopefully, acclimation. The trajectory and duration of this pandemic in the United States remains unclear. While hot spots such as Seattle, New York, and Boston may be moving past their peak phase and acclimating to a “new normal,” there remain concerns that surges may recur in the fall and winter, which will undoubtedly lead battle-weary clinicians to experience the stages of moral distress anew and potentially compounding their distress.

An added complexity in this pandemic is that we, as clinicians, are both the victims and the healers. From the literature on disaster mental health, we know that emotional suffering is universal in affected populations.^4,5 Unlike many disaster scenarios in which teams leave the safety and security of well-established and well-resourced practices to deploy and care for disaster victims in new, austere environments, we are also part of that affected population in this pandemic. Each day or night, we return to homes that, too, are infiltrated by this pandemic. Our ability to move through the indignation, resignation, and acclimation stages may be hindered and blocked by our home responsibilities, stressors, and supports. Having to reconcile working in COVID-affected hospitals (particularly if caring for critically ill colleagues) only to return home to young or immunocompromised family members at night may place us in a state of indignation with its continued risk of burnout for the duration of this pandemic. Naming and acknowledging these painful challenges may allow self-compassion, self-forgiveness, and acceptance.

Though the primary focus of this article is to provide a framework to assist with the recognition of moral distress, it is important to address next steps once one recognizes someone is experiencing moral distress in this pandemic. Even outside of a disaster scenario, many clinicians feel obligated to put our patients’ needs before our own, and this sentiment is only heightened in a disaster scenario. It may feel unthinkable to call out sick or request a leave or reassignment during the pandemic. However, we are reminded that “the duty to serve is not endless.”⁶ Recognizing one’s own limits and reaching out to supervisors and mental health support before reaching one’s own limit is essential when experiencing moral distress.^7,8

Cultivating resilience is also recognized as a tool for managing moral distress.^6,9 For harried frontline clinicians, this may be as simple as taking a few minutes each night to journal three good things that occurred during the day.¹⁰ Mindfulness-­based stress reduction has also been found to decrease perceptions of moral distress,⁹ and many mindfulness programs (such as Headspace®, a mindfulness and meditation app¹¹) currently offer free membership to frontline providers during the pandemic. Mindfulness may be a particularly useful tool to leverage when one is stuck in the resignation phase and experiencing moral residue, described as a buildup of unresolved conflicts within the clinician that may crescendo with unresolved or inadequately resolved moral distress.^6,12 Lastly, the American Association of Critical Care Nurses Ethics Workgroup developed the 4 A’s to Rise Above Moral Distress, which provides a framework of 4 concrete steps: ask appropriate questions, affirm your distress and your commitment to take care of yourself, assess or identify sources of your distress, and act or take action.¹³

Providers may experience moral distress in times of disaster. In applying this framework, we can gain self-insight and compassion, understand the types of moral distress our colleagues may be experiencing, and explore concrete tools for managing moral distress. Just as we confront the suffering of our COVID-positive patients, so too may we benefit from sitting with and naming our own suffering and moral distress.

The authors have nothing to disclose.

Many US health care systems experienced a surge of critically ill corona virus disease 2019 (COVID-19) patients while lacking adequate resources to provide optimal care. Nurses, doctors, and other providers in the United States were confronted with having to implement crisis standards of care for the first time. The refrain “these are unprecedented times” was repeated to colleagues and patients. The demands and shortages of supplies are unique in recent history. As a result, many frontline responders have wrestled with moral distress, the feelings of distress experienced when forced to act—because of institutional or resource constraints—in a manner contrary to their beliefs.¹ However, for those medical professionals whose work includes being deployed on global disaster response teams or providing healthcare in chronically low-resourced settings, navigating limitations of medicines, equipment, and personnel is a daily reality. We offer a framework for recognizing one’s own moral distress and that of one’s colleagues based on our experiences in global disaster response that may be helpful for clinicians during the COVID-19 pandemic.

The intense and debilitating feelings of unexpected loss and helplessness faced by clinicians who are making challenging choices about medical interventions can be better understood by applying a theoretical framework that has the following three main stages in the evolution and response to moral distress: indignation, resignation, and acclimation. This framework can provide guidance to individuals experiencing distress during the COVID-19 pandemic and may also be beneficial in contextualizing interactions when working in teams or with referring providers.

Indignation

When working in a disaster setting, an initial period of indignation is common. The clinician is shocked and horrified by the conditions encountered, the severity of suffering, and a lack of resources with which they are unaccustomed. As we bear witness to the many healthcare providers who have fallen ill and died, we fear for our own safety in choosing to care for patients sick with COVID: “I’m risking my life caring for patients on the front lines, and it’s unacceptable that I’m not even being provided with adequate PPE!” Patients and families are suffering in ways we had previously thought our health system was capable of addressing: “How can I be a compassionate clinician when my patients are forced to die alone?!” It feels surreal and unacceptable that so many patients can die so quickly despite our heroic interventions and that we have very little control over their fate. We are unaccustomed to caring for so many dying patients at once. For example, during the peak of the pandemic in New York City, patients were dying at four times the city’s normal death rate.² Indignation may be compounded in settings where providers are not even equipped to deal with the aftermath of deaths, such as piling bodies into makeshift morgues²: “I feel powerless to prevent my patients’ deaths and horrified that many are dying alone and scared, and now I can’t even guarantee that their bodies will be cared for after death!” Additionally, during this pandemic, many of us are now facing issues of resource allocation that we had never imagined dealing with. “I took an oath to care for and protect my patients. How could I possibly tell a patient we have no more ventilators to put them on? Who makes the decision of which patients deserve to live or die?” With the realization that COVID-19 has been disproportionately affecting racial and ethnic minorities, concerns for systemic discrimination within our healthcare system may rightly lead to a deep indignation.³

Resignation

After the initial indignation stage, resignation often follows. “I guess I can’t fix healthcare in this new setting, and I was foolish for even trying.” Clinicians go through the motions and continue to care for patients but feel disillusioned. Part of the ongoing stress involves the concern that they aren’t making a difference. Lack of viral testing may breed further resignation: Clinicians are on the front lines caring for patients that they are not even sure are positive for COVID-19, they have no way of accessing antibody testing for themselves to be able to gauge their own personal risks, and when there is not enough testing being done on a larger scale, there may be a sense that, by continuing to work on the front lines, they are sticking their finger in the dike, without actually having data to inform when it is safe to reopen states and ease restrictions. The suffering of patients and families may feel overwhelming and insurmountable. “I know I have to comply with my hospital’s visitor restriction policies, but it’s hard to see my patients suffering alone and know there’s nothing I can do to help them.”

Acclimation

Acclimation follows the indignation and resignation stages. Even amid disasters, a productive rhythm develops as teams coalesce and are galvanized by a shared sense of purpose. Clinicians make meaning out of their role in the crisis and in the care of the patients they can help, despite often deep and significant obstacles. “There’s a lot of suffering and a lot that I may not be able to fix, but some that I can.” Clinicians that have been deployed to unfamiliar roles may start to habituate and even enjoy having responsibilities and challenges that are different from those they typically face. Innovation during a pandemic may feel empowering. “I’m committed to making sure my dying patients and their families can say goodbye however possible. Although it’s not ideal, I’ve been using technology for virtual communication and advocating for families to visit in person when possible.”

One’s path of moral distress through a disaster may not be linear; one does not necessarily progress through the stages of indignation, resignation, and acclimation in a certain order or at a certain pace. Additionally, the stages can recur throughout the disaster. Being able to recognize these stages may prove useful for the duration of this pandemic while waves of providers are redeployed in new settings and experience fresh indignation, whereas others who have been in the trenches for some time may be more likely experiencing resignation or, hopefully, acclimation. The trajectory and duration of this pandemic in the United States remains unclear. While hot spots such as Seattle, New York, and Boston may be moving past their peak phase and acclimating to a “new normal,” there remain concerns that surges may recur in the fall and winter, which will undoubtedly lead battle-weary clinicians to experience the stages of moral distress anew and potentially compounding their distress.

An added complexity in this pandemic is that we, as clinicians, are both the victims and the healers. From the literature on disaster mental health, we know that emotional suffering is universal in affected populations.^4,5 Unlike many disaster scenarios in which teams leave the safety and security of well-established and well-resourced practices to deploy and care for disaster victims in new, austere environments, we are also part of that affected population in this pandemic. Each day or night, we return to homes that, too, are infiltrated by this pandemic. Our ability to move through the indignation, resignation, and acclimation stages may be hindered and blocked by our home responsibilities, stressors, and supports. Having to reconcile working in COVID-affected hospitals (particularly if caring for critically ill colleagues) only to return home to young or immunocompromised family members at night may place us in a state of indignation with its continued risk of burnout for the duration of this pandemic. Naming and acknowledging these painful challenges may allow self-compassion, self-forgiveness, and acceptance.

Though the primary focus of this article is to provide a framework to assist with the recognition of moral distress, it is important to address next steps once one recognizes someone is experiencing moral distress in this pandemic. Even outside of a disaster scenario, many clinicians feel obligated to put our patients’ needs before our own, and this sentiment is only heightened in a disaster scenario. It may feel unthinkable to call out sick or request a leave or reassignment during the pandemic. However, we are reminded that “the duty to serve is not endless.”⁶ Recognizing one’s own limits and reaching out to supervisors and mental health support before reaching one’s own limit is essential when experiencing moral distress.^7,8

Cultivating resilience is also recognized as a tool for managing moral distress.^6,9 For harried frontline clinicians, this may be as simple as taking a few minutes each night to journal three good things that occurred during the day.¹⁰ Mindfulness-­based stress reduction has also been found to decrease perceptions of moral distress,⁹ and many mindfulness programs (such as Headspace®, a mindfulness and meditation app¹¹) currently offer free membership to frontline providers during the pandemic. Mindfulness may be a particularly useful tool to leverage when one is stuck in the resignation phase and experiencing moral residue, described as a buildup of unresolved conflicts within the clinician that may crescendo with unresolved or inadequately resolved moral distress.^6,12 Lastly, the American Association of Critical Care Nurses Ethics Workgroup developed the 4 A’s to Rise Above Moral Distress, which provides a framework of 4 concrete steps: ask appropriate questions, affirm your distress and your commitment to take care of yourself, assess or identify sources of your distress, and act or take action.¹³

Providers may experience moral distress in times of disaster. In applying this framework, we can gain self-insight and compassion, understand the types of moral distress our colleagues may be experiencing, and explore concrete tools for managing moral distress. Just as we confront the suffering of our COVID-positive patients, so too may we benefit from sitting with and naming our own suffering and moral distress.

The authors have nothing to disclose.

Basic science and clinical research are the hallmarks of progress in biomedicine. Scientists rely on timely access to research findings to accelerate and strengthen their work, and clinicians depend on the latest data to ensure that the highest level of care reaches each patient’s bedside. Historically, academic journals have served as the gatekeepers of this knowledge, using expert peer review to cull the bad science from the good and ensure a meticulous standard of reporting before sharing information with the public. While robust and effective, the peer review process can, at times, be slow and cumbersome. During widespread emergencies, such as the current COVID-19 pandemic, delays in publication may handicap our ability to meet the urgent demands of the global scientific and medical communities. Indeed, academic journals initially struggled to manage the deluge of COVID-19–­related submissions, with potential reviewers similarly occupied on the clinical front lines and unable to promptly evaluate pending submissions. This impasse necessarily hindered the dissemination of relevant clinical data, which left physicians operatingwith limited evidence in some settings and, in turn, may have led to potentially avoidable harm.¹ Although many journals have since expedited their review processes in light of current pressing circumstances, these measures are not necessarily sustainable or scalable in the face of an increasingly expansive biomedical enterprise that will continue to face challenges of increasing urgency.² Moreover, it remains unclear to what extent quality has been sacrificed in exchange for this temporary expedience.

Scientific progress demands access to the rapid dissemination of robust data, and preprint servers are uniquely positioned to meet this need. Preprints are manuscripts released to the public before formal peer review and publication in an “official” indexed journal. Long used in mathematics and the physical sciences, preprint servers for the biomedical community such as medRxiv and bioRxiv have previously had limited traction because many have cited the risks of circulating information that may later be disputed or, worse, invalidated.^3-6 The risk-benefit calculus, however, must be carefully considered. Preprints provide a fast and wide-reaching means for sharing new discoveries. Submissions often undergo a brief screening process to ensure appropriateness, but otherwise largely forego scientific review before being posted online where the data become freely and widely available to the public.

The enthusiasm for preprints in the current era has demonstrated both the promise and peril of a free and wide distribution strategy.⁵ Early in the COVID-19 pandemic, Western hospitals were flooded with critically ill patients and relied on reports from providers in China, where the disease had struck first, to define the basic pathophysiology. Guan et al shared the clinical symptoms, laboratory abnormalities, and radiologic findings of 1,099 patients with COVID-19 through preprint servers in early February 2020, well before many American clinicians had gained direct experience with SARS-CoV-2.⁷ Their findings were published in the New England Journal of Medicine 1 month later,⁸ but the initial preprint provided an early window into the largest threats that COVID-19 would pose for patients and the health system and corroborated that the increasing number of patients with acute respiratory distress syndrome was on pace to dwarf the number of available ventilators around the world. Physicians responded in kind and used preprints as a mechanism to share their early experience with awake prone positioning and shared ventilation, which were critical components of the global strategy to contend with the limited ventilator supply during the height of the pandemic.^9-12

Despite these undisputed triumphs, hazards abound. Rapidly disseminating new findings via preprint servers neither implies shoddy science nor absolves investigators of the need for critical review, yet it provides opportunities for both. As an example, Gautret et al first shared their open-label study examining the efficacy of hydroxychloroquine and azithromycin for COVID-19 by using preprint publication.¹³ The study did not meet a priori sample size requirements, it incorporated a trial arm that was not prespecified, and it was promptly contradicted by a second trial, which raised concern about the validity of the findings.¹⁴ While the study was ultimately published in a journal, preprint allowed these often-misquoted data to circulate far longer than would have been possible were expert peer review to have requested strengthening of the findings.¹⁵ Under ideal circumstances, peer review serves to capture and address these types of methodologic errors in order to avoid the publication of misleading or incomplete results. By foregoing the peer review process when posting a preprint manuscript, investigators have an equal opportunity to share good and bad science with a community that may lack the expertise to distinguish between the two. Indeed, the results posted by Gautret et al were immediately amplified by media and policy makers alike, who touted hydroxychloroquine as a “game-changing” panacea despite the preliminary nature of the findings.¹⁶ Irrational exuberance then prompted drug hoarding and supply issues before more robust studies alerted providers to the potential adverse effects of this regimen and the limited evidence of any efficacy.^17,18

Ultimately, both preprints and perfunctory peer review afford minimal safeguards to prevent the adoption of incomplete or misinterpreted results. While envisioned as a tool for scientific collaboration, preprints do have a broader readership that may be unaware of fundamental differences between a preprint manuscript and one reviewed by a rigorous academic journal. Considering the reliability of findings from these different domains as equivalent could ultimately cause public harm.

To be sure, there are ways to enhance the current system and limit opportunities for misguided enthusiasm. Firstly, preprint servers can be difficult to navigate. Limited indexing in disparate silos that are distinct from the rest of the literature (ie, the U.S. National Library of Medicine’s PubMed) make relevant articles challenging to identify and, in some instances, relegate the curation of new papers to social media platforms. Resources to aggregate and query the growing database of submissions would improve our ability to identify appropriate articles and use this preliminary evidence base.

Secondly, once an article has been unearthed, few tools exist to help nonexpert readers evaluate the quality of the research. Many consumers, inclusive of other scientists, may not share the investigators’ expertise. Preprint platforms might aid readers by compiling metrics to indicate study quality. For example, a voting and commenting function to permit a form of crowd-sourced peer review, while imperfect, would allow subject matter experts to communicate the value of a submission and point out errors. Weighting of votes by the h-index or institution of each “reviewer” might further enhance the value of this crowd-sourced evaluation. Additionally, the site could indicate when there is broad agreement on a particular critique by alerting readers to an established limitation of the study in question. Ultimately, numerous such mechanisms might be considered, but all share the overarching goal of guiding readers to exercise appropriate caution in interpreting a study in order to avoid unfettered acceptance of flawed research.

Thirdly, preprint servers can minimize the circulation of outdated research by highlighting manuscripts whose findings have subsequently been disproven. There are certainly complexities in distinguishing between a scientific difference of opinion and an invalidated research finding, but rather than avoid these challenging topics, systems must acknowledge this critical nuance and address it transparently. Indeed, the more prominent preprint servers have already begun to limit the dissemination of clearly misleading research in acknowledgment of this responsibility.^1,19 The biomedical community must continue to engage in open dialogue to determine where the filter is set between blocking harmful pseudoscience and honest efforts to evaluate research validity.

Lastly, while prominent preprint platforms continue to limit the dissemination of opinion pieces, clinical recommendations, and review articles, these submissions are among the most urgently useful content during a pandemic, as evidenced by the ongoing stream of published consensus statements and clinical guidelines. Moreover, these pieces are often invited unilaterally by journal editors and are less likely to undergo peer review before formal publication. Clinicians hunger for practical insights during this pandemic, and allowing guidelines and reviews to be posted rapidly—and to be flagged accordingly as “nonoriginal” research—could spark timely dialogue that might ultimately accelerate science.

Preprint servers do not obviate the need for critical scientific appraisal of their content; however, their risks are not an excuse to limit their adoption as an effective and practical data sharing platform. By embracing the rapid and transparent dissemination of data afforded by preprints, and thoughtfully navigating the caveats of applying new research (non–peer-­reviewed manuscripts or otherwise), we will have added a powerful instrument to the biomedical armamentarium with lasting implications beyond the current crisis.

Dr Guterman reported receipt of grants from the National Institute of Neurological Disorders and Stroke (1K23NS116128-01), the National Institute on Aging (5R01AG056715), the American Academy of Neurology, as well as consulting fees from Marinus, Inc, that are outside the submitted work. Dr Braunstein reported no potential conflicts of interest. 

Basic science and clinical research are the hallmarks of progress in biomedicine. Scientists rely on timely access to research findings to accelerate and strengthen their work, and clinicians depend on the latest data to ensure that the highest level of care reaches each patient’s bedside. Historically, academic journals have served as the gatekeepers of this knowledge, using expert peer review to cull the bad science from the good and ensure a meticulous standard of reporting before sharing information with the public. While robust and effective, the peer review process can, at times, be slow and cumbersome. During widespread emergencies, such as the current COVID-19 pandemic, delays in publication may handicap our ability to meet the urgent demands of the global scientific and medical communities. Indeed, academic journals initially struggled to manage the deluge of COVID-19–­related submissions, with potential reviewers similarly occupied on the clinical front lines and unable to promptly evaluate pending submissions. This impasse necessarily hindered the dissemination of relevant clinical data, which left physicians operatingwith limited evidence in some settings and, in turn, may have led to potentially avoidable harm.¹ Although many journals have since expedited their review processes in light of current pressing circumstances, these measures are not necessarily sustainable or scalable in the face of an increasingly expansive biomedical enterprise that will continue to face challenges of increasing urgency.² Moreover, it remains unclear to what extent quality has been sacrificed in exchange for this temporary expedience.

Scientific progress demands access to the rapid dissemination of robust data, and preprint servers are uniquely positioned to meet this need. Preprints are manuscripts released to the public before formal peer review and publication in an “official” indexed journal. Long used in mathematics and the physical sciences, preprint servers for the biomedical community such as medRxiv and bioRxiv have previously had limited traction because many have cited the risks of circulating information that may later be disputed or, worse, invalidated.^3-6 The risk-benefit calculus, however, must be carefully considered. Preprints provide a fast and wide-reaching means for sharing new discoveries. Submissions often undergo a brief screening process to ensure appropriateness, but otherwise largely forego scientific review before being posted online where the data become freely and widely available to the public.

The enthusiasm for preprints in the current era has demonstrated both the promise and peril of a free and wide distribution strategy.⁵ Early in the COVID-19 pandemic, Western hospitals were flooded with critically ill patients and relied on reports from providers in China, where the disease had struck first, to define the basic pathophysiology. Guan et al shared the clinical symptoms, laboratory abnormalities, and radiologic findings of 1,099 patients with COVID-19 through preprint servers in early February 2020, well before many American clinicians had gained direct experience with SARS-CoV-2.⁷ Their findings were published in the New England Journal of Medicine 1 month later,⁸ but the initial preprint provided an early window into the largest threats that COVID-19 would pose for patients and the health system and corroborated that the increasing number of patients with acute respiratory distress syndrome was on pace to dwarf the number of available ventilators around the world. Physicians responded in kind and used preprints as a mechanism to share their early experience with awake prone positioning and shared ventilation, which were critical components of the global strategy to contend with the limited ventilator supply during the height of the pandemic.^9-12

Despite these undisputed triumphs, hazards abound. Rapidly disseminating new findings via preprint servers neither implies shoddy science nor absolves investigators of the need for critical review, yet it provides opportunities for both. As an example, Gautret et al first shared their open-label study examining the efficacy of hydroxychloroquine and azithromycin for COVID-19 by using preprint publication.¹³ The study did not meet a priori sample size requirements, it incorporated a trial arm that was not prespecified, and it was promptly contradicted by a second trial, which raised concern about the validity of the findings.¹⁴ While the study was ultimately published in a journal, preprint allowed these often-misquoted data to circulate far longer than would have been possible were expert peer review to have requested strengthening of the findings.¹⁵ Under ideal circumstances, peer review serves to capture and address these types of methodologic errors in order to avoid the publication of misleading or incomplete results. By foregoing the peer review process when posting a preprint manuscript, investigators have an equal opportunity to share good and bad science with a community that may lack the expertise to distinguish between the two. Indeed, the results posted by Gautret et al were immediately amplified by media and policy makers alike, who touted hydroxychloroquine as a “game-changing” panacea despite the preliminary nature of the findings.¹⁶ Irrational exuberance then prompted drug hoarding and supply issues before more robust studies alerted providers to the potential adverse effects of this regimen and the limited evidence of any efficacy.^17,18

Ultimately, both preprints and perfunctory peer review afford minimal safeguards to prevent the adoption of incomplete or misinterpreted results. While envisioned as a tool for scientific collaboration, preprints do have a broader readership that may be unaware of fundamental differences between a preprint manuscript and one reviewed by a rigorous academic journal. Considering the reliability of findings from these different domains as equivalent could ultimately cause public harm.

To be sure, there are ways to enhance the current system and limit opportunities for misguided enthusiasm. Firstly, preprint servers can be difficult to navigate. Limited indexing in disparate silos that are distinct from the rest of the literature (ie, the U.S. National Library of Medicine’s PubMed) make relevant articles challenging to identify and, in some instances, relegate the curation of new papers to social media platforms. Resources to aggregate and query the growing database of submissions would improve our ability to identify appropriate articles and use this preliminary evidence base.

Secondly, once an article has been unearthed, few tools exist to help nonexpert readers evaluate the quality of the research. Many consumers, inclusive of other scientists, may not share the investigators’ expertise. Preprint platforms might aid readers by compiling metrics to indicate study quality. For example, a voting and commenting function to permit a form of crowd-sourced peer review, while imperfect, would allow subject matter experts to communicate the value of a submission and point out errors. Weighting of votes by the h-index or institution of each “reviewer” might further enhance the value of this crowd-sourced evaluation. Additionally, the site could indicate when there is broad agreement on a particular critique by alerting readers to an established limitation of the study in question. Ultimately, numerous such mechanisms might be considered, but all share the overarching goal of guiding readers to exercise appropriate caution in interpreting a study in order to avoid unfettered acceptance of flawed research.

Thirdly, preprint servers can minimize the circulation of outdated research by highlighting manuscripts whose findings have subsequently been disproven. There are certainly complexities in distinguishing between a scientific difference of opinion and an invalidated research finding, but rather than avoid these challenging topics, systems must acknowledge this critical nuance and address it transparently. Indeed, the more prominent preprint servers have already begun to limit the dissemination of clearly misleading research in acknowledgment of this responsibility.^1,19 The biomedical community must continue to engage in open dialogue to determine where the filter is set between blocking harmful pseudoscience and honest efforts to evaluate research validity.

Lastly, while prominent preprint platforms continue to limit the dissemination of opinion pieces, clinical recommendations, and review articles, these submissions are among the most urgently useful content during a pandemic, as evidenced by the ongoing stream of published consensus statements and clinical guidelines. Moreover, these pieces are often invited unilaterally by journal editors and are less likely to undergo peer review before formal publication. Clinicians hunger for practical insights during this pandemic, and allowing guidelines and reviews to be posted rapidly—and to be flagged accordingly as “nonoriginal” research—could spark timely dialogue that might ultimately accelerate science.

Preprint servers do not obviate the need for critical scientific appraisal of their content; however, their risks are not an excuse to limit their adoption as an effective and practical data sharing platform. By embracing the rapid and transparent dissemination of data afforded by preprints, and thoughtfully navigating the caveats of applying new research (non–peer-­reviewed manuscripts or otherwise), we will have added a powerful instrument to the biomedical armamentarium with lasting implications beyond the current crisis.

Dr Guterman reported receipt of grants from the National Institute of Neurological Disorders and Stroke (1K23NS116128-01), the National Institute on Aging (5R01AG056715), the American Academy of Neurology, as well as consulting fees from Marinus, Inc, that are outside the submitted work. Dr Braunstein reported no potential conflicts of interest. 

Basic science and clinical research are the hallmarks of progress in biomedicine. Scientists rely on timely access to research findings to accelerate and strengthen their work, and clinicians depend on the latest data to ensure that the highest level of care reaches each patient’s bedside. Historically, academic journals have served as the gatekeepers of this knowledge, using expert peer review to cull the bad science from the good and ensure a meticulous standard of reporting before sharing information with the public. While robust and effective, the peer review process can, at times, be slow and cumbersome. During widespread emergencies, such as the current COVID-19 pandemic, delays in publication may handicap our ability to meet the urgent demands of the global scientific and medical communities. Indeed, academic journals initially struggled to manage the deluge of COVID-19–­related submissions, with potential reviewers similarly occupied on the clinical front lines and unable to promptly evaluate pending submissions. This impasse necessarily hindered the dissemination of relevant clinical data, which left physicians operatingwith limited evidence in some settings and, in turn, may have led to potentially avoidable harm.¹ Although many journals have since expedited their review processes in light of current pressing circumstances, these measures are not necessarily sustainable or scalable in the face of an increasingly expansive biomedical enterprise that will continue to face challenges of increasing urgency.² Moreover, it remains unclear to what extent quality has been sacrificed in exchange for this temporary expedience.

Scientific progress demands access to the rapid dissemination of robust data, and preprint servers are uniquely positioned to meet this need. Preprints are manuscripts released to the public before formal peer review and publication in an “official” indexed journal. Long used in mathematics and the physical sciences, preprint servers for the biomedical community such as medRxiv and bioRxiv have previously had limited traction because many have cited the risks of circulating information that may later be disputed or, worse, invalidated.^3-6 The risk-benefit calculus, however, must be carefully considered. Preprints provide a fast and wide-reaching means for sharing new discoveries. Submissions often undergo a brief screening process to ensure appropriateness, but otherwise largely forego scientific review before being posted online where the data become freely and widely available to the public.

The enthusiasm for preprints in the current era has demonstrated both the promise and peril of a free and wide distribution strategy.⁵ Early in the COVID-19 pandemic, Western hospitals were flooded with critically ill patients and relied on reports from providers in China, where the disease had struck first, to define the basic pathophysiology. Guan et al shared the clinical symptoms, laboratory abnormalities, and radiologic findings of 1,099 patients with COVID-19 through preprint servers in early February 2020, well before many American clinicians had gained direct experience with SARS-CoV-2.⁷ Their findings were published in the New England Journal of Medicine 1 month later,⁸ but the initial preprint provided an early window into the largest threats that COVID-19 would pose for patients and the health system and corroborated that the increasing number of patients with acute respiratory distress syndrome was on pace to dwarf the number of available ventilators around the world. Physicians responded in kind and used preprints as a mechanism to share their early experience with awake prone positioning and shared ventilation, which were critical components of the global strategy to contend with the limited ventilator supply during the height of the pandemic.^9-12

Despite these undisputed triumphs, hazards abound. Rapidly disseminating new findings via preprint servers neither implies shoddy science nor absolves investigators of the need for critical review, yet it provides opportunities for both. As an example, Gautret et al first shared their open-label study examining the efficacy of hydroxychloroquine and azithromycin for COVID-19 by using preprint publication.¹³ The study did not meet a priori sample size requirements, it incorporated a trial arm that was not prespecified, and it was promptly contradicted by a second trial, which raised concern about the validity of the findings.¹⁴ While the study was ultimately published in a journal, preprint allowed these often-misquoted data to circulate far longer than would have been possible were expert peer review to have requested strengthening of the findings.¹⁵ Under ideal circumstances, peer review serves to capture and address these types of methodologic errors in order to avoid the publication of misleading or incomplete results. By foregoing the peer review process when posting a preprint manuscript, investigators have an equal opportunity to share good and bad science with a community that may lack the expertise to distinguish between the two. Indeed, the results posted by Gautret et al were immediately amplified by media and policy makers alike, who touted hydroxychloroquine as a “game-changing” panacea despite the preliminary nature of the findings.¹⁶ Irrational exuberance then prompted drug hoarding and supply issues before more robust studies alerted providers to the potential adverse effects of this regimen and the limited evidence of any efficacy.^17,18

Ultimately, both preprints and perfunctory peer review afford minimal safeguards to prevent the adoption of incomplete or misinterpreted results. While envisioned as a tool for scientific collaboration, preprints do have a broader readership that may be unaware of fundamental differences between a preprint manuscript and one reviewed by a rigorous academic journal. Considering the reliability of findings from these different domains as equivalent could ultimately cause public harm.

To be sure, there are ways to enhance the current system and limit opportunities for misguided enthusiasm. Firstly, preprint servers can be difficult to navigate. Limited indexing in disparate silos that are distinct from the rest of the literature (ie, the U.S. National Library of Medicine’s PubMed) make relevant articles challenging to identify and, in some instances, relegate the curation of new papers to social media platforms. Resources to aggregate and query the growing database of submissions would improve our ability to identify appropriate articles and use this preliminary evidence base.

Secondly, once an article has been unearthed, few tools exist to help nonexpert readers evaluate the quality of the research. Many consumers, inclusive of other scientists, may not share the investigators’ expertise. Preprint platforms might aid readers by compiling metrics to indicate study quality. For example, a voting and commenting function to permit a form of crowd-sourced peer review, while imperfect, would allow subject matter experts to communicate the value of a submission and point out errors. Weighting of votes by the h-index or institution of each “reviewer” might further enhance the value of this crowd-sourced evaluation. Additionally, the site could indicate when there is broad agreement on a particular critique by alerting readers to an established limitation of the study in question. Ultimately, numerous such mechanisms might be considered, but all share the overarching goal of guiding readers to exercise appropriate caution in interpreting a study in order to avoid unfettered acceptance of flawed research.

Thirdly, preprint servers can minimize the circulation of outdated research by highlighting manuscripts whose findings have subsequently been disproven. There are certainly complexities in distinguishing between a scientific difference of opinion and an invalidated research finding, but rather than avoid these challenging topics, systems must acknowledge this critical nuance and address it transparently. Indeed, the more prominent preprint servers have already begun to limit the dissemination of clearly misleading research in acknowledgment of this responsibility.^1,19 The biomedical community must continue to engage in open dialogue to determine where the filter is set between blocking harmful pseudoscience and honest efforts to evaluate research validity.

Lastly, while prominent preprint platforms continue to limit the dissemination of opinion pieces, clinical recommendations, and review articles, these submissions are among the most urgently useful content during a pandemic, as evidenced by the ongoing stream of published consensus statements and clinical guidelines. Moreover, these pieces are often invited unilaterally by journal editors and are less likely to undergo peer review before formal publication. Clinicians hunger for practical insights during this pandemic, and allowing guidelines and reviews to be posted rapidly—and to be flagged accordingly as “nonoriginal” research—could spark timely dialogue that might ultimately accelerate science.

Preprint servers do not obviate the need for critical scientific appraisal of their content; however, their risks are not an excuse to limit their adoption as an effective and practical data sharing platform. By embracing the rapid and transparent dissemination of data afforded by preprints, and thoughtfully navigating the caveats of applying new research (non–peer-­reviewed manuscripts or otherwise), we will have added a powerful instrument to the biomedical armamentarium with lasting implications beyond the current crisis.

Dr Guterman reported receipt of grants from the National Institute of Neurological Disorders and Stroke (1K23NS116128-01), the National Institute on Aging (5R01AG056715), the American Academy of Neurology, as well as consulting fees from Marinus, Inc, that are outside the submitted work. Dr Braunstein reported no potential conflicts of interest. 

Hospitals play important roles in the healthcare ecosystem. Currently, they account for approximately one-third of more than $3 trillion dollars spent on healthcare annually.¹ To contain costs, improve patient experience, and advance population health, there has been progress in standardizing quality metrics and increasing transparency around key performance metrics.

Launched in 2016, the Overall Hospital Quality Star Rating was developed by the Centers for Medicare & Medicaid Services (CMS) as a means of assessing quality and outcome measures. More importantly, star ratings are aimed to enhance the usability and accessibility of information about quality. The rating system evaluates seven quality categories: mortality, safety, readmission, patient experience, effectiveness, timeliness, and efficient use of medical imaging. Hospitals that have at least three measures within at least three measure categories, including one outcome group (mortality, safety, or readmission) are eligible for an overall rating based on a five-star system.²

While the intent of quality ratings is to summarize high-dimensional information to facilitate patients in choosing hospitals with better quality, it is unclear whether patients have equal geographic proximity to hospitals with high ratings. Although researchers have examined overall quality ratings by hospital type (community, specialty, teaching, bed size),³ there is an opportunity to expand the body of knowledge at the intersection of overall star rating and race/ethnicity, education attainment, income level, and geographic region.

This study complements prior investigations on the topic. For example, Osbourne et al found that comorbidities and socioeconomic barriers were leading factors in observed mortality disparities between Black and White patients.⁴ Since mortality ratings are factored into overall star ratings, hospitals that serve low-income communities of color with high-acuity volumes may be at risk for lower star quality ratings. Trivedi et al found that, compared with White patients, Black and Hispanic patients were more likely to use low-volume hospitals for cardiac procedures. In addition, Black patients experienced worse outcomes.⁵ Insurance barriers, limited access to specialty care providers, and residential segregation may explain the chasm. These factors, often beyond hospitals’ control, may impact readmissions, which are also factored into overall quality ratings. Additionally, Hu and Nerenz found that, on average, the most “stressed” cities have lower quality ratings than less “stressed” cities.⁶ Stress markers include poverty, unemployment, divorce rate, and adult health conditions. Other findings suggest readmission rates are correlated with patient provider ratios, community characteristics, and poor social and economic conditions that influence decision-making.^7-9 Some investigators have explored quality ratings in other sectors of healthcare. For example, residents in socioeconomically disadvantaged counties are less likely to access nursing homes with higher star ratings.⁹

In light of new and emerging value-based payment models, coupled with efforts to risk-adjust for socioeconomic conditions that may compromise desired outcomes, this study sought to expand the scope of knowledge by offering insight on the association between hospital quality ratings and socioeconomic factors and geographic indicators. Particularly, we focus on the minority population percentage, county-level household income, education, dual eligibility, rural/urban designation, and geographic region.

Data and Study Sample

Our analysis relies on data extracted from multiple sources. We obtained hospital overall quality ratings from the Hospital Compare website (www.medicare.gov/hospitalcompare) released in July 2018. We also included key hospital characteristics extracted by American Hospital Directory and Medicare cost reports. Socioeconomic and demographic variables were obtained from the Area Health Resources Files (AHRF) maintained by Health Resources & Services Administration. Hospital referral region data was downloaded from Dartmouth Atlas Project. We included only acute hospitals that were certified by CMS. Hospitals with missing overall star rating values were excluded. Our study included 3,075 acute care hospitals in 1,047 counties and 306 hospital referral regions.

Dependent Variable: Hospital Quality Ratings

Our main outcome variables are hospital quality ratings reported by CMS. The overall star ratings use 64 of more than 100 quality measures and ranges from one to five stars, with five stars representing the highest quality. Our study uses the hospital quality star rating released in July 2018. The measurement period starts in January 2014 and extends to September 2017. Because of space limitation, we only present the results on the overall rating. The full results of all seven quality domains are provided in appendices.

Key Independent Variables

Key variables of interest are the socioeconomic factors of the communities served by the hospital. Specifically, our analysis focuses on minority population percentage, household income, education attainment, Medicare/Medicaid dual eligibility, urban/rural designation, and geographic region. For these key variables except urban/rural designation and geographic region, we created categorical variables indicating whether the values are below the national median (low group), in the 3rd quartile (intermediate group), and in the 4th quartile (high group). Group cutoffs are based on socioeconomic and demographic variables reported by AHRF for all counties nationwide. Because we use the county averages as the cutoff values and each county has a different number of hospitals, the number of hospitals distributes unevenly in each quartile. Additionally, we grouped the 1st and 2nd quartiles as the low group because there are fewer hospitals in these two quartiles. Education attainment is measured by the percentage of population above 25 years old with a college degree. “Hospital access” is defined as a measure for the availability of services from competing hospitals, and we counted the number of hospitals available in a hospital referral region. For the 306 hospital referral regions, the number of hospitals ranges from 1 to 71 with an average of 12.

Statistical Model

To study the relationship between quality rating and socioeconomic factors, we used both logistic and multinomial logistic regression models. The regression model can be described as follows:

Q _i = Minority _i β ₁ + Income _i β ₂ + Population Age _i β ₃ + Education _i β ₄ + Access _i β ₅ + Dual_Eligible _i β ₆ + Rural _i β ₇ + Region _i β ₈ + Hosp _i γ + ϵ _i

In the logistic model, Q_i represents the dependent variable indicating whether a hospital has an overall quality star rating of either one star or five stars; we also ran a multinomial logistic regression model in which the hospital overall quality star rating ranges from one star to five stars with one-star increments. These ordinal regression models include key socioeconomic factors, such as percentage of population that is a minority, the average household income, the education attainment level, access to hospitals, the percentage of population that is Medicare/Medicaid dual-eligible, and the rurality of a hospital. We also include a set of dummy variables to control for region differences. [Hosp]_i is a vector of hospital characteristics, including ownership status, teaching status, and hospital size.

To examine extreme hospital quality (ie, one or five stars) overall ratings in relation to socioeconomic factors of serving communities, we first used the logistic regression model to predict probabilities of hospitals with either one-star or five-star ratings. We then compared the marginal probabilities of key socioeconomic factors. Finally, we treated the overall quality rating collectively, ranging from one to five stars, as an ordinal variable and applied multinomial logistic regression to produce odds ratios of relationship of key variables with higher quality rating hospitals. For all these models, standard errors are clustered at the hospital referral region level. Models are estimated by generalized estimating equations. Statistical analyses were conducted in SAS 9.2.

We first present the summary statistics of key variables in Table 1. The estimated marginal probabilities and odds ratios from the multivariate regressions are reported in Table 2.

Distribution of Quality Ratings

The distribution of hospital quality rating is shown in the Figure. About 8% of the hospitals received a one-star rating, whereas 9.95% of the hospitals had a five-star rating. Most of the hospitals received two, three, and four stars with frequencies of 21.63%, 30.80%, and 29.63%, respectively. The distribution of quality ratings with respect to socioeconomic and geographic factors are presented in Table 1. Most hospitals in our sample were located in counties where the minority population percentage was above the national median (8.21%). The hospitals in counties with highest minority presence had a lower overall rating (2.86). There is a clear gradient between the median household income and hospital overall rating. About 43% of hospitals were in counties in which the median household income was in the 4th quartile, whereas only 31% of hospitals are in counties with a median household income below the national median. Hospitals in counties with high income also have higher overall rating (3.24). In terms of urban/rural hospitals, there are more urban hospitals (70%) but with a lower overall rating of 3.04, compared with rural hospitals (30%, 3.31). We also found that the counties with higher education attainment and lower dual-eligible population tend to have higher hospital ratings. Geographically, hospitals in the Midwest and West have higher average overall quality ratings than do those in the Northeast and South.

Minority Population Percentage and Hospital Rating

As shown in Table 2, results from the logistic regression show that, compared with those in counties with low minority population percentage, hospitals in counties with high minority population percentage have higher marginal probabilities to have one-star ratings, and the result is statistically significant at the 1% level. At the same time, hospitals in counties with intermediate minority percentage have lower marginal probabilities of having a five-star rating. On the other hand, the odds ratio from the multinomial logistic regressions show that minority population percentage is negatively correlated with hospital rating, statistically significant at the 1% level.

Median Household Income and Hospital Rating

We found a statistically significant relationship between household income and hospital quality rating. Hospitals in lower income groups are more likely to have one-star ratings. The odds ratio analysis provides consistent evidence that higher household income is correlated with star ratings.

Education Attainment, Dual Eligibility, and Hospital Rating

In addition, we found a consistent and statistically significant relationship between education attainment and hospital ratings. Compared with counties with high education attainment (reference group), hospitals in counties with intermediate education attainment are more likely to have one-star ratings. Similarly, hospitals in counties with less and intermediate education attainment are less likely to be five-star rated. Consistently, odds ratios of hospitals in intermediate and lower education attainment counties with better quality are significantly lower, at the 1% level.

In terms of dual eligibility, hospitals in counties with higher percentage of dual-eligible residents are statistically significantly less likely to receive five-star ratings. Consistent evidence was found in odds ratios. However, dual eligibility is not statistically significantly correlated with the probabilities of receiving one-star ratings.

Rurality, Geographic Region, and Hospital Rating

Compared with urban hospitals, rural hospitals are less likely to receive five-star ratings. However, there is no difference in the probabilities of receiving one-star ratings and no statistically significant difference in overall ratings. Geographically, hospitals in the Northeast are more likely to have one-star ratings and less likely to be five-star rated. The odds ratio also suggests that Northeastern hospitals on average have lower quality rating compared with Midwestern hospitals. Hospitals in South and West are also less likely to have five-star ratings.

Consistent with findings in nursing homes,¹⁰ hospitals that serve lower income communities have comparatively lower quality ratings than did those that serve more affluent communities. Several factors may contribute to these outcomes. Higher volumes of uninsured patients and patients with public insurance impact how much revenue the hospital collects for services, hindering the capacity to reinvest in processes to advance quality. Moreover, these hospitals are likely to serve patients with higher acuity and complex psychosocial barriers that affect their experience, perceptions, and outcomes. Structural conditions of economically distressed communities also play a role. Limited access to a robust network of community-based resources for healthy living post surgery may contribute to higher rates of readmission, which may compromise overall quality ratings.

Furthermore, after adjustment for community characteristics, hospitals that serve higher volumes of racial minorities have higher probability of receiving one-star ratings and lower average quality rating. While more research is needed to examine specific measures in the quality rating formula that may disproportionately affect racial and ethnic minorities, Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) surveys may offer some insight. Some researchers have found that White respondents and those with higher levels of education are more likely to cite favorable HCAHPS responses than are minorities or persons with lower levels of education.¹¹ This has negative implications on the HCAPHS scores of hospitals that serve higher volumes of minority patients with low education attainment. Real or perceived discrimination, unconscious bias, miscommunication, and language discordance may explain the disparity between the survey results of White respondents and minorities.^12-16

While interpreting the results of this study, it is important to note that the research design examines the relationship between quality ratings, race, and community characteristics. Our analysis does not specifically examine clinical quality of care. It should not be assumed that hospitals with low ratings provide substandard clinical care.

While the intent of Hospital Quality Ratings is well received, there are varying perspectives on the calculation methodology—particularly the need for social risk adjustment.^17-19 There is also concern about community perception which affects consumer choice, decision making, and referral patterns. Hospitals with lower ratings are likely to have negative repercussions that perpetuate inequities. For example, in light of new and emerging pay-for-performance models, the publicity of star ratings has the potential to influence behaviors that exacerbate disparities.²⁰ Physicians and medical groups may explicitly or implicitly avoid patients with characteristics that may lower their quality scores. Patients with resources to fully cover their healthcare expenses may choose hospitals with higher quality ratings, leaving hospitals with lower quality ratings to serve the under- or uninsured. Over time, these patterns may jeopardize quality, safety, and the fiscal viability of hospitals that serve communities with lower socioeconomic status.

Among the geographic regions analyzed, quality ratings were higher in the Midwest. This finding aligns with a report from the Agency for Healthcare Research and Quality, which recognized five states from the Midwest for having the highest quality ratings (Iowa, Minnesota, Nebraska, North Dakota, and Wisconsin).²¹ Hospitals in the South and Northeast generally had lower quality ratings. As discovered by other investigators, nonteaching, smaller, rural hospitals had more favorable outcomes when compared with teaching, larger, urban hospitals, which are more likely to care for more complex, critically ill patients.²² These regional differences, coupled with hospital types, have implications for federal appropriations and funding priorities earmarked for quality initiatives.

As national efforts continue to promote health equity and enhance the value of healthcare, it is important to recognize the association between race, socioeconomic factors, and hospital star quality ratings. Allocated resources should ensure that hospitals serving racial minorities, low-income communities, and those in urban settings have the capacity to deliver comprehensive care based on the unique needs of the community. Hospitals that serve low-income communities may benefit from payment models and incentives that adjust for these differences—which could allow them to invest in quality improvement processes and social support services.

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

The authors did not receive external funding for this study.

Hospitals play important roles in the healthcare ecosystem. Currently, they account for approximately one-third of more than $3 trillion dollars spent on healthcare annually.¹ To contain costs, improve patient experience, and advance population health, there has been progress in standardizing quality metrics and increasing transparency around key performance metrics.

Launched in 2016, the Overall Hospital Quality Star Rating was developed by the Centers for Medicare & Medicaid Services (CMS) as a means of assessing quality and outcome measures. More importantly, star ratings are aimed to enhance the usability and accessibility of information about quality. The rating system evaluates seven quality categories: mortality, safety, readmission, patient experience, effectiveness, timeliness, and efficient use of medical imaging. Hospitals that have at least three measures within at least three measure categories, including one outcome group (mortality, safety, or readmission) are eligible for an overall rating based on a five-star system.²

While the intent of quality ratings is to summarize high-dimensional information to facilitate patients in choosing hospitals with better quality, it is unclear whether patients have equal geographic proximity to hospitals with high ratings. Although researchers have examined overall quality ratings by hospital type (community, specialty, teaching, bed size),³ there is an opportunity to expand the body of knowledge at the intersection of overall star rating and race/ethnicity, education attainment, income level, and geographic region.

This study complements prior investigations on the topic. For example, Osbourne et al found that comorbidities and socioeconomic barriers were leading factors in observed mortality disparities between Black and White patients.⁴ Since mortality ratings are factored into overall star ratings, hospitals that serve low-income communities of color with high-acuity volumes may be at risk for lower star quality ratings. Trivedi et al found that, compared with White patients, Black and Hispanic patients were more likely to use low-volume hospitals for cardiac procedures. In addition, Black patients experienced worse outcomes.⁵ Insurance barriers, limited access to specialty care providers, and residential segregation may explain the chasm. These factors, often beyond hospitals’ control, may impact readmissions, which are also factored into overall quality ratings. Additionally, Hu and Nerenz found that, on average, the most “stressed” cities have lower quality ratings than less “stressed” cities.⁶ Stress markers include poverty, unemployment, divorce rate, and adult health conditions. Other findings suggest readmission rates are correlated with patient provider ratios, community characteristics, and poor social and economic conditions that influence decision-making.^7-9 Some investigators have explored quality ratings in other sectors of healthcare. For example, residents in socioeconomically disadvantaged counties are less likely to access nursing homes with higher star ratings.⁹

In light of new and emerging value-based payment models, coupled with efforts to risk-adjust for socioeconomic conditions that may compromise desired outcomes, this study sought to expand the scope of knowledge by offering insight on the association between hospital quality ratings and socioeconomic factors and geographic indicators. Particularly, we focus on the minority population percentage, county-level household income, education, dual eligibility, rural/urban designation, and geographic region.

Data and Study Sample

Our analysis relies on data extracted from multiple sources. We obtained hospital overall quality ratings from the Hospital Compare website (www.medicare.gov/hospitalcompare) released in July 2018. We also included key hospital characteristics extracted by American Hospital Directory and Medicare cost reports. Socioeconomic and demographic variables were obtained from the Area Health Resources Files (AHRF) maintained by Health Resources & Services Administration. Hospital referral region data was downloaded from Dartmouth Atlas Project. We included only acute hospitals that were certified by CMS. Hospitals with missing overall star rating values were excluded. Our study included 3,075 acute care hospitals in 1,047 counties and 306 hospital referral regions.

Dependent Variable: Hospital Quality Ratings

Our main outcome variables are hospital quality ratings reported by CMS. The overall star ratings use 64 of more than 100 quality measures and ranges from one to five stars, with five stars representing the highest quality. Our study uses the hospital quality star rating released in July 2018. The measurement period starts in January 2014 and extends to September 2017. Because of space limitation, we only present the results on the overall rating. The full results of all seven quality domains are provided in appendices.

Key Independent Variables

Key variables of interest are the socioeconomic factors of the communities served by the hospital. Specifically, our analysis focuses on minority population percentage, household income, education attainment, Medicare/Medicaid dual eligibility, urban/rural designation, and geographic region. For these key variables except urban/rural designation and geographic region, we created categorical variables indicating whether the values are below the national median (low group), in the 3rd quartile (intermediate group), and in the 4th quartile (high group). Group cutoffs are based on socioeconomic and demographic variables reported by AHRF for all counties nationwide. Because we use the county averages as the cutoff values and each county has a different number of hospitals, the number of hospitals distributes unevenly in each quartile. Additionally, we grouped the 1st and 2nd quartiles as the low group because there are fewer hospitals in these two quartiles. Education attainment is measured by the percentage of population above 25 years old with a college degree. “Hospital access” is defined as a measure for the availability of services from competing hospitals, and we counted the number of hospitals available in a hospital referral region. For the 306 hospital referral regions, the number of hospitals ranges from 1 to 71 with an average of 12.

Statistical Model

To study the relationship between quality rating and socioeconomic factors, we used both logistic and multinomial logistic regression models. The regression model can be described as follows:

Q _i = Minority _i β ₁ + Income _i β ₂ + Population Age _i β ₃ + Education _i β ₄ + Access _i β ₅ + Dual_Eligible _i β ₆ + Rural _i β ₇ + Region _i β ₈ + Hosp _i γ + ϵ _i

In the logistic model, Q_i represents the dependent variable indicating whether a hospital has an overall quality star rating of either one star or five stars; we also ran a multinomial logistic regression model in which the hospital overall quality star rating ranges from one star to five stars with one-star increments. These ordinal regression models include key socioeconomic factors, such as percentage of population that is a minority, the average household income, the education attainment level, access to hospitals, the percentage of population that is Medicare/Medicaid dual-eligible, and the rurality of a hospital. We also include a set of dummy variables to control for region differences. [Hosp]_i is a vector of hospital characteristics, including ownership status, teaching status, and hospital size.

To examine extreme hospital quality (ie, one or five stars) overall ratings in relation to socioeconomic factors of serving communities, we first used the logistic regression model to predict probabilities of hospitals with either one-star or five-star ratings. We then compared the marginal probabilities of key socioeconomic factors. Finally, we treated the overall quality rating collectively, ranging from one to five stars, as an ordinal variable and applied multinomial logistic regression to produce odds ratios of relationship of key variables with higher quality rating hospitals. For all these models, standard errors are clustered at the hospital referral region level. Models are estimated by generalized estimating equations. Statistical analyses were conducted in SAS 9.2.

We first present the summary statistics of key variables in Table 1. The estimated marginal probabilities and odds ratios from the multivariate regressions are reported in Table 2.

Distribution of Quality Ratings

The distribution of hospital quality rating is shown in the Figure. About 8% of the hospitals received a one-star rating, whereas 9.95% of the hospitals had a five-star rating. Most of the hospitals received two, three, and four stars with frequencies of 21.63%, 30.80%, and 29.63%, respectively. The distribution of quality ratings with respect to socioeconomic and geographic factors are presented in Table 1. Most hospitals in our sample were located in counties where the minority population percentage was above the national median (8.21%). The hospitals in counties with highest minority presence had a lower overall rating (2.86). There is a clear gradient between the median household income and hospital overall rating. About 43% of hospitals were in counties in which the median household income was in the 4th quartile, whereas only 31% of hospitals are in counties with a median household income below the national median. Hospitals in counties with high income also have higher overall rating (3.24). In terms of urban/rural hospitals, there are more urban hospitals (70%) but with a lower overall rating of 3.04, compared with rural hospitals (30%, 3.31). We also found that the counties with higher education attainment and lower dual-eligible population tend to have higher hospital ratings. Geographically, hospitals in the Midwest and West have higher average overall quality ratings than do those in the Northeast and South.

Minority Population Percentage and Hospital Rating

As shown in Table 2, results from the logistic regression show that, compared with those in counties with low minority population percentage, hospitals in counties with high minority population percentage have higher marginal probabilities to have one-star ratings, and the result is statistically significant at the 1% level. At the same time, hospitals in counties with intermediate minority percentage have lower marginal probabilities of having a five-star rating. On the other hand, the odds ratio from the multinomial logistic regressions show that minority population percentage is negatively correlated with hospital rating, statistically significant at the 1% level.

Median Household Income and Hospital Rating

We found a statistically significant relationship between household income and hospital quality rating. Hospitals in lower income groups are more likely to have one-star ratings. The odds ratio analysis provides consistent evidence that higher household income is correlated with star ratings.

Education Attainment, Dual Eligibility, and Hospital Rating

In addition, we found a consistent and statistically significant relationship between education attainment and hospital ratings. Compared with counties with high education attainment (reference group), hospitals in counties with intermediate education attainment are more likely to have one-star ratings. Similarly, hospitals in counties with less and intermediate education attainment are less likely to be five-star rated. Consistently, odds ratios of hospitals in intermediate and lower education attainment counties with better quality are significantly lower, at the 1% level.

In terms of dual eligibility, hospitals in counties with higher percentage of dual-eligible residents are statistically significantly less likely to receive five-star ratings. Consistent evidence was found in odds ratios. However, dual eligibility is not statistically significantly correlated with the probabilities of receiving one-star ratings.

Rurality, Geographic Region, and Hospital Rating

Compared with urban hospitals, rural hospitals are less likely to receive five-star ratings. However, there is no difference in the probabilities of receiving one-star ratings and no statistically significant difference in overall ratings. Geographically, hospitals in the Northeast are more likely to have one-star ratings and less likely to be five-star rated. The odds ratio also suggests that Northeastern hospitals on average have lower quality rating compared with Midwestern hospitals. Hospitals in South and West are also less likely to have five-star ratings.

Consistent with findings in nursing homes,¹⁰ hospitals that serve lower income communities have comparatively lower quality ratings than did those that serve more affluent communities. Several factors may contribute to these outcomes. Higher volumes of uninsured patients and patients with public insurance impact how much revenue the hospital collects for services, hindering the capacity to reinvest in processes to advance quality. Moreover, these hospitals are likely to serve patients with higher acuity and complex psychosocial barriers that affect their experience, perceptions, and outcomes. Structural conditions of economically distressed communities also play a role. Limited access to a robust network of community-based resources for healthy living post surgery may contribute to higher rates of readmission, which may compromise overall quality ratings.

Furthermore, after adjustment for community characteristics, hospitals that serve higher volumes of racial minorities have higher probability of receiving one-star ratings and lower average quality rating. While more research is needed to examine specific measures in the quality rating formula that may disproportionately affect racial and ethnic minorities, Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) surveys may offer some insight. Some researchers have found that White respondents and those with higher levels of education are more likely to cite favorable HCAHPS responses than are minorities or persons with lower levels of education.¹¹ This has negative implications on the HCAPHS scores of hospitals that serve higher volumes of minority patients with low education attainment. Real or perceived discrimination, unconscious bias, miscommunication, and language discordance may explain the disparity between the survey results of White respondents and minorities.^12-16

While interpreting the results of this study, it is important to note that the research design examines the relationship between quality ratings, race, and community characteristics. Our analysis does not specifically examine clinical quality of care. It should not be assumed that hospitals with low ratings provide substandard clinical care.

While the intent of Hospital Quality Ratings is well received, there are varying perspectives on the calculation methodology—particularly the need for social risk adjustment.^17-19 There is also concern about community perception which affects consumer choice, decision making, and referral patterns. Hospitals with lower ratings are likely to have negative repercussions that perpetuate inequities. For example, in light of new and emerging pay-for-performance models, the publicity of star ratings has the potential to influence behaviors that exacerbate disparities.²⁰ Physicians and medical groups may explicitly or implicitly avoid patients with characteristics that may lower their quality scores. Patients with resources to fully cover their healthcare expenses may choose hospitals with higher quality ratings, leaving hospitals with lower quality ratings to serve the under- or uninsured. Over time, these patterns may jeopardize quality, safety, and the fiscal viability of hospitals that serve communities with lower socioeconomic status.

Among the geographic regions analyzed, quality ratings were higher in the Midwest. This finding aligns with a report from the Agency for Healthcare Research and Quality, which recognized five states from the Midwest for having the highest quality ratings (Iowa, Minnesota, Nebraska, North Dakota, and Wisconsin).²¹ Hospitals in the South and Northeast generally had lower quality ratings. As discovered by other investigators, nonteaching, smaller, rural hospitals had more favorable outcomes when compared with teaching, larger, urban hospitals, which are more likely to care for more complex, critically ill patients.²² These regional differences, coupled with hospital types, have implications for federal appropriations and funding priorities earmarked for quality initiatives.

As national efforts continue to promote health equity and enhance the value of healthcare, it is important to recognize the association between race, socioeconomic factors, and hospital star quality ratings. Allocated resources should ensure that hospitals serving racial minorities, low-income communities, and those in urban settings have the capacity to deliver comprehensive care based on the unique needs of the community. Hospitals that serve low-income communities may benefit from payment models and incentives that adjust for these differences—which could allow them to invest in quality improvement processes and social support services.

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

The authors did not receive external funding for this study.

Hospitals play important roles in the healthcare ecosystem. Currently, they account for approximately one-third of more than $3 trillion dollars spent on healthcare annually.¹ To contain costs, improve patient experience, and advance population health, there has been progress in standardizing quality metrics and increasing transparency around key performance metrics.

Launched in 2016, the Overall Hospital Quality Star Rating was developed by the Centers for Medicare & Medicaid Services (CMS) as a means of assessing quality and outcome measures. More importantly, star ratings are aimed to enhance the usability and accessibility of information about quality. The rating system evaluates seven quality categories: mortality, safety, readmission, patient experience, effectiveness, timeliness, and efficient use of medical imaging. Hospitals that have at least three measures within at least three measure categories, including one outcome group (mortality, safety, or readmission) are eligible for an overall rating based on a five-star system.²

While the intent of quality ratings is to summarize high-dimensional information to facilitate patients in choosing hospitals with better quality, it is unclear whether patients have equal geographic proximity to hospitals with high ratings. Although researchers have examined overall quality ratings by hospital type (community, specialty, teaching, bed size),³ there is an opportunity to expand the body of knowledge at the intersection of overall star rating and race/ethnicity, education attainment, income level, and geographic region.

This study complements prior investigations on the topic. For example, Osbourne et al found that comorbidities and socioeconomic barriers were leading factors in observed mortality disparities between Black and White patients.⁴ Since mortality ratings are factored into overall star ratings, hospitals that serve low-income communities of color with high-acuity volumes may be at risk for lower star quality ratings. Trivedi et al found that, compared with White patients, Black and Hispanic patients were more likely to use low-volume hospitals for cardiac procedures. In addition, Black patients experienced worse outcomes.⁵ Insurance barriers, limited access to specialty care providers, and residential segregation may explain the chasm. These factors, often beyond hospitals’ control, may impact readmissions, which are also factored into overall quality ratings. Additionally, Hu and Nerenz found that, on average, the most “stressed” cities have lower quality ratings than less “stressed” cities.⁶ Stress markers include poverty, unemployment, divorce rate, and adult health conditions. Other findings suggest readmission rates are correlated with patient provider ratios, community characteristics, and poor social and economic conditions that influence decision-making.^7-9 Some investigators have explored quality ratings in other sectors of healthcare. For example, residents in socioeconomically disadvantaged counties are less likely to access nursing homes with higher star ratings.⁹

In light of new and emerging value-based payment models, coupled with efforts to risk-adjust for socioeconomic conditions that may compromise desired outcomes, this study sought to expand the scope of knowledge by offering insight on the association between hospital quality ratings and socioeconomic factors and geographic indicators. Particularly, we focus on the minority population percentage, county-level household income, education, dual eligibility, rural/urban designation, and geographic region.

Data and Study Sample

Our analysis relies on data extracted from multiple sources. We obtained hospital overall quality ratings from the Hospital Compare website (www.medicare.gov/hospitalcompare) released in July 2018. We also included key hospital characteristics extracted by American Hospital Directory and Medicare cost reports. Socioeconomic and demographic variables were obtained from the Area Health Resources Files (AHRF) maintained by Health Resources & Services Administration. Hospital referral region data was downloaded from Dartmouth Atlas Project. We included only acute hospitals that were certified by CMS. Hospitals with missing overall star rating values were excluded. Our study included 3,075 acute care hospitals in 1,047 counties and 306 hospital referral regions.

Dependent Variable: Hospital Quality Ratings

Our main outcome variables are hospital quality ratings reported by CMS. The overall star ratings use 64 of more than 100 quality measures and ranges from one to five stars, with five stars representing the highest quality. Our study uses the hospital quality star rating released in July 2018. The measurement period starts in January 2014 and extends to September 2017. Because of space limitation, we only present the results on the overall rating. The full results of all seven quality domains are provided in appendices.

Key Independent Variables

Key variables of interest are the socioeconomic factors of the communities served by the hospital. Specifically, our analysis focuses on minority population percentage, household income, education attainment, Medicare/Medicaid dual eligibility, urban/rural designation, and geographic region. For these key variables except urban/rural designation and geographic region, we created categorical variables indicating whether the values are below the national median (low group), in the 3rd quartile (intermediate group), and in the 4th quartile (high group). Group cutoffs are based on socioeconomic and demographic variables reported by AHRF for all counties nationwide. Because we use the county averages as the cutoff values and each county has a different number of hospitals, the number of hospitals distributes unevenly in each quartile. Additionally, we grouped the 1st and 2nd quartiles as the low group because there are fewer hospitals in these two quartiles. Education attainment is measured by the percentage of population above 25 years old with a college degree. “Hospital access” is defined as a measure for the availability of services from competing hospitals, and we counted the number of hospitals available in a hospital referral region. For the 306 hospital referral regions, the number of hospitals ranges from 1 to 71 with an average of 12.

Statistical Model

To study the relationship between quality rating and socioeconomic factors, we used both logistic and multinomial logistic regression models. The regression model can be described as follows:

Q _i = Minority _i β ₁ + Income _i β ₂ + Population Age _i β ₃ + Education _i β ₄ + Access _i β ₅ + Dual_Eligible _i β ₆ + Rural _i β ₇ + Region _i β ₈ + Hosp _i γ + ϵ _i

In the logistic model, Q_i represents the dependent variable indicating whether a hospital has an overall quality star rating of either one star or five stars; we also ran a multinomial logistic regression model in which the hospital overall quality star rating ranges from one star to five stars with one-star increments. These ordinal regression models include key socioeconomic factors, such as percentage of population that is a minority, the average household income, the education attainment level, access to hospitals, the percentage of population that is Medicare/Medicaid dual-eligible, and the rurality of a hospital. We also include a set of dummy variables to control for region differences. [Hosp]_i is a vector of hospital characteristics, including ownership status, teaching status, and hospital size.

To examine extreme hospital quality (ie, one or five stars) overall ratings in relation to socioeconomic factors of serving communities, we first used the logistic regression model to predict probabilities of hospitals with either one-star or five-star ratings. We then compared the marginal probabilities of key socioeconomic factors. Finally, we treated the overall quality rating collectively, ranging from one to five stars, as an ordinal variable and applied multinomial logistic regression to produce odds ratios of relationship of key variables with higher quality rating hospitals. For all these models, standard errors are clustered at the hospital referral region level. Models are estimated by generalized estimating equations. Statistical analyses were conducted in SAS 9.2.

We first present the summary statistics of key variables in Table 1. The estimated marginal probabilities and odds ratios from the multivariate regressions are reported in Table 2.

Distribution of Quality Ratings

The distribution of hospital quality rating is shown in the Figure. About 8% of the hospitals received a one-star rating, whereas 9.95% of the hospitals had a five-star rating. Most of the hospitals received two, three, and four stars with frequencies of 21.63%, 30.80%, and 29.63%, respectively. The distribution of quality ratings with respect to socioeconomic and geographic factors are presented in Table 1. Most hospitals in our sample were located in counties where the minority population percentage was above the national median (8.21%). The hospitals in counties with highest minority presence had a lower overall rating (2.86). There is a clear gradient between the median household income and hospital overall rating. About 43% of hospitals were in counties in which the median household income was in the 4th quartile, whereas only 31% of hospitals are in counties with a median household income below the national median. Hospitals in counties with high income also have higher overall rating (3.24). In terms of urban/rural hospitals, there are more urban hospitals (70%) but with a lower overall rating of 3.04, compared with rural hospitals (30%, 3.31). We also found that the counties with higher education attainment and lower dual-eligible population tend to have higher hospital ratings. Geographically, hospitals in the Midwest and West have higher average overall quality ratings than do those in the Northeast and South.

Minority Population Percentage and Hospital Rating

As shown in Table 2, results from the logistic regression show that, compared with those in counties with low minority population percentage, hospitals in counties with high minority population percentage have higher marginal probabilities to have one-star ratings, and the result is statistically significant at the 1% level. At the same time, hospitals in counties with intermediate minority percentage have lower marginal probabilities of having a five-star rating. On the other hand, the odds ratio from the multinomial logistic regressions show that minority population percentage is negatively correlated with hospital rating, statistically significant at the 1% level.

Median Household Income and Hospital Rating

We found a statistically significant relationship between household income and hospital quality rating. Hospitals in lower income groups are more likely to have one-star ratings. The odds ratio analysis provides consistent evidence that higher household income is correlated with star ratings.

Education Attainment, Dual Eligibility, and Hospital Rating

In addition, we found a consistent and statistically significant relationship between education attainment and hospital ratings. Compared with counties with high education attainment (reference group), hospitals in counties with intermediate education attainment are more likely to have one-star ratings. Similarly, hospitals in counties with less and intermediate education attainment are less likely to be five-star rated. Consistently, odds ratios of hospitals in intermediate and lower education attainment counties with better quality are significantly lower, at the 1% level.

In terms of dual eligibility, hospitals in counties with higher percentage of dual-eligible residents are statistically significantly less likely to receive five-star ratings. Consistent evidence was found in odds ratios. However, dual eligibility is not statistically significantly correlated with the probabilities of receiving one-star ratings.

Rurality, Geographic Region, and Hospital Rating

Compared with urban hospitals, rural hospitals are less likely to receive five-star ratings. However, there is no difference in the probabilities of receiving one-star ratings and no statistically significant difference in overall ratings. Geographically, hospitals in the Northeast are more likely to have one-star ratings and less likely to be five-star rated. The odds ratio also suggests that Northeastern hospitals on average have lower quality rating compared with Midwestern hospitals. Hospitals in South and West are also less likely to have five-star ratings.

Consistent with findings in nursing homes,¹⁰ hospitals that serve lower income communities have comparatively lower quality ratings than did those that serve more affluent communities. Several factors may contribute to these outcomes. Higher volumes of uninsured patients and patients with public insurance impact how much revenue the hospital collects for services, hindering the capacity to reinvest in processes to advance quality. Moreover, these hospitals are likely to serve patients with higher acuity and complex psychosocial barriers that affect their experience, perceptions, and outcomes. Structural conditions of economically distressed communities also play a role. Limited access to a robust network of community-based resources for healthy living post surgery may contribute to higher rates of readmission, which may compromise overall quality ratings.

Furthermore, after adjustment for community characteristics, hospitals that serve higher volumes of racial minorities have higher probability of receiving one-star ratings and lower average quality rating. While more research is needed to examine specific measures in the quality rating formula that may disproportionately affect racial and ethnic minorities, Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) surveys may offer some insight. Some researchers have found that White respondents and those with higher levels of education are more likely to cite favorable HCAHPS responses than are minorities or persons with lower levels of education.¹¹ This has negative implications on the HCAPHS scores of hospitals that serve higher volumes of minority patients with low education attainment. Real or perceived discrimination, unconscious bias, miscommunication, and language discordance may explain the disparity between the survey results of White respondents and minorities.^12-16

While interpreting the results of this study, it is important to note that the research design examines the relationship between quality ratings, race, and community characteristics. Our analysis does not specifically examine clinical quality of care. It should not be assumed that hospitals with low ratings provide substandard clinical care.

While the intent of Hospital Quality Ratings is well received, there are varying perspectives on the calculation methodology—particularly the need for social risk adjustment.^17-19 There is also concern about community perception which affects consumer choice, decision making, and referral patterns. Hospitals with lower ratings are likely to have negative repercussions that perpetuate inequities. For example, in light of new and emerging pay-for-performance models, the publicity of star ratings has the potential to influence behaviors that exacerbate disparities.²⁰ Physicians and medical groups may explicitly or implicitly avoid patients with characteristics that may lower their quality scores. Patients with resources to fully cover their healthcare expenses may choose hospitals with higher quality ratings, leaving hospitals with lower quality ratings to serve the under- or uninsured. Over time, these patterns may jeopardize quality, safety, and the fiscal viability of hospitals that serve communities with lower socioeconomic status.

Among the geographic regions analyzed, quality ratings were higher in the Midwest. This finding aligns with a report from the Agency for Healthcare Research and Quality, which recognized five states from the Midwest for having the highest quality ratings (Iowa, Minnesota, Nebraska, North Dakota, and Wisconsin).²¹ Hospitals in the South and Northeast generally had lower quality ratings. As discovered by other investigators, nonteaching, smaller, rural hospitals had more favorable outcomes when compared with teaching, larger, urban hospitals, which are more likely to care for more complex, critically ill patients.²² These regional differences, coupled with hospital types, have implications for federal appropriations and funding priorities earmarked for quality initiatives.

As national efforts continue to promote health equity and enhance the value of healthcare, it is important to recognize the association between race, socioeconomic factors, and hospital star quality ratings. Allocated resources should ensure that hospitals serving racial minorities, low-income communities, and those in urban settings have the capacity to deliver comprehensive care based on the unique needs of the community. Hospitals that serve low-income communities may benefit from payment models and incentives that adjust for these differences—which could allow them to invest in quality improvement processes and social support services.

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

The authors did not receive external funding for this study.

Adding the CDK4/6 inhibitor abemaciclib (Verzenio) to endocrine therapy significantly reduces the risk of early recurrence in high-risk hormone receptor positive (HR+), human epidermal growth factor receptor 2 (HER2)–negative breast cancer, suggests a preplanned interim analysis of a phase 3 trial.

The research was presented Sept. 19 at the ESMO Virtual Congress 2020 and simultaneously published in the Journal of Clinical Oncology.

The monarchE trial compared 2 years of abemaciclib plus endocrine therapy vs endocrine therapy alone among 5,600 patients and found that the combination was associated with a 25% relative risk reduction in the primary endpoint – invasive disease-free survival (P =.0096; HR, 0.75; 95% CI, 0.60 - 0.93)

At 2 years, the rate of invasive disease-free survival was 92.2% in the abemaciclib arm vs 88.7% in the group that took endocrine therapy alone.

“This is the first time in more than 20 years that we have seen an advance in the adjuvant treatment of this form of breast cancer,” said lead investigator Stephen Johnston, MD, PhD, from the Royal Marsden Hospital NHS Foundation Trust in London, UK, in a meeting press release.

He told Medscape Medical News that the high-risk patients in their study “are predicted to relapse quite quickly” as a result of having a degree of endocrine resistance, “and by intervening early we are stopping these recurrences within the first 2 years.”

He continued: “The key issue ... is whether you need 2 years of treatment or perhaps even longer. One other trial is looking at 3 years with another drug, and we’ll just have to await further follow-up of the data to see if the [monarchE] curves continue to separate while on treatment.”

According to Giuseppe Curigliano, MD, PhD, head of the Division of Early Drug Development at the European Institute of Oncology, Milan, Italy, “This is a very important trial and the findings will change practice. Once approved for high risk HR+ HER2-negative early breast cancer, the new standard of care for these patients will be to add two years of abemaciclib to endocrine therapy.”

Curigliano, who was not involved with the study, further commented during a meeting press conference that a randomized trial will be needed to answer a new important question: Can these high-risk patients treated with a CDK4/6 inhibitor be spared chemotherapy?

Investigator Johnston pointed out that many patients diagnosed with HR+, HER2 breast cancer will not experience recurrence with standard-of-care therapies.

But he also explained “that up to 20% may develop recurrence or distant relapse in the first 10 years” and that the risk of recurrence is “much greater” for patients who have high-risk clinical or pathological features, “especially during the first few years on their adjuvant endocrine therapy.”
 

Study details

Abemaciclib was approved by the US Food and Drug Administration in 2017 and is approved in combination with the endocrine therapy fulvestrant for the treatment of HR+, HER2-negative advanced or metastatic breast cancer that has progressed after endocrine therapy.

The approval was, in part, based on data from the MONARCH-2 trial, which showed consistent overall survival benefits with the combination.

MonarchE, on the other hand, examined the impact of abemaciclib in the first-line adjuvant setting, enrolling patients with HR+, HER2-negative, node-positive early breast cancer who had a tumor size of ≥5 cm, histologic grade 3 disease, and/or Ki67 index of ≥20%.

They were randomly assigned in a 1:1 fashion to abemaciclib 150 mg twice daily for up to 2 years plus standard of care endocrine therapy or standard of care endocrine therapy alone.

The choice of endocrine therapy was left to the physician and was continued for 5-10 years, as clinically indicated.

The trial included 5,637 patients. An efficacy interim analysis was planned for when 75% of the estimated invasive disease-free survival events had occurred, which equated to 323 events in the intention-to-treat population.

This occurred after approximately 15.5 months of follow-up in each arm, when 12.5% of patients had completed the 2-year treatment period, leaving 70% still in treatment.

The intention-to-treat population included 2,808 patients from the abemaciclib plus endocrine therapy group and 2,829 in the group taking endocrine therapy alone.

The two groups were well balanced in terms of their baseline characteristics. The vast majority (approximately 85%) of patients were younger than 65 years, and 56.5% were postmenopausal.

Also, 37% had previously received neoadjuvant chemotherapy, and approximately 58% had adjuvant chemotherapy.

Distant relapse-free survival was significantly reduced with abemaciclib plus endocrine therapy vs endocrine therapy alone, at a hazard ratio of 0.72 (P = .0085), and a 2-year rate of 93.6% and 90.3%, respectively.

Johnston highlighted that not only was the number of patients with distant recurrences reduced with the combination therapy, at 92 vs 142 with endocrine therapy alone, but also the reductions were in key locations.

The number of patients with recurrences in the bone were 32 with abemaciclib and 81 with endocrine therapy alone; 29 patients with abemaciclib and 42 with endocrine therapy alone had recurrences in the liver.

The results show that the most frequent adverse events in the abemaciclib arm were diarrhea (82%), neutropenia (45%), and fatigue (38%), whereas arthralgia (31%), hot flush (21%), and fatigue (15%) were seen most often in the control group.

Venous thromboembolic events were recorded in 2.3% of patients in the abemaciclib group versus 0.5% of those on endocrine therapy alone; interstitial lung disease was seen in 2.7% and 1.2%, respectively.

Despite the protocol allowing dose reductions from 150 mg to 100 mg twice daily if required, 463 (16.6%) patients discontinued abemaciclib as a result of adverse events. Of those, 306 continued on endocrine therapy.

“Adherence to treatment will be an important issue to be considered in the real-life population of patients when this treatment is approved and used in clinical practice,” Johnston said.

Nevertheless, diarrhea frequency and severity decreased significantly over time, and only 4.8% of the abemaciclib group discontinued use as a result of this adverse event.
 

Questions remain

George W. Sledge Jr, MD, professor of medicine (oncology) at Stanford University Medical Center, Palo Alto, California, was the invited discussant after the presentation.

He said that “positive trials raise as many questions as they answer, and monarchE is no exception.”

For example, there is the conundrum posed by the negative results of the very similar PALLAS trial, which looked at the addition of palbociclib to adjuvant endocrine therapy for HR+, HER2-negative early breast cancer and was also presented at the ESMO meeting.

Returning to monarchE, Sledge asked what the ultimate increase in invasive disease- and distant relapse-free survival will be with the drug combination, noting that the trial has “very, very short follow-up.”

“Second, will the improvements seen in disease-free survival lead to what we really care about: improved overall survival? Again, time will tell, but health care systems and patients care deeply about the answer to this question.”

Sledge continued: “How about late recurrence? Do CDK4/6 inhibitors kill off dormant or slow-growing micro-mets that lead to recurrences 5 or more years out?”

He also asked what the optimum duration of therapy would be: “Is it more than we need, or not enough?”

Sledge wondered whether it is possible to determine who benefits “and why the drug fails some patients.”

Finally, Sledge said, “These drugs are expensive. ... 2 years of adjuvant therapy is simply out of reach for the majority of patients around the globe who might be candidates for adjuvant CDK4/6 inhibitor therapy.”

And he observed an important truism: “A patient cannot benefit from a drug she cannot take.”

The study was funded by Eli Lilly. Johnston, Sledge, and Curigliano have financial ties to Eli Lilly and multiple other drug companies.
 

This article first appeared on Medscape.com.

Adding the CDK4/6 inhibitor abemaciclib (Verzenio) to endocrine therapy significantly reduces the risk of early recurrence in high-risk hormone receptor positive (HR+), human epidermal growth factor receptor 2 (HER2)–negative breast cancer, suggests a preplanned interim analysis of a phase 3 trial.

The research was presented Sept. 19 at the ESMO Virtual Congress 2020 and simultaneously published in the Journal of Clinical Oncology.

The monarchE trial compared 2 years of abemaciclib plus endocrine therapy vs endocrine therapy alone among 5,600 patients and found that the combination was associated with a 25% relative risk reduction in the primary endpoint – invasive disease-free survival (P =.0096; HR, 0.75; 95% CI, 0.60 - 0.93)

At 2 years, the rate of invasive disease-free survival was 92.2% in the abemaciclib arm vs 88.7% in the group that took endocrine therapy alone.

“This is the first time in more than 20 years that we have seen an advance in the adjuvant treatment of this form of breast cancer,” said lead investigator Stephen Johnston, MD, PhD, from the Royal Marsden Hospital NHS Foundation Trust in London, UK, in a meeting press release.

He told Medscape Medical News that the high-risk patients in their study “are predicted to relapse quite quickly” as a result of having a degree of endocrine resistance, “and by intervening early we are stopping these recurrences within the first 2 years.”

He continued: “The key issue ... is whether you need 2 years of treatment or perhaps even longer. One other trial is looking at 3 years with another drug, and we’ll just have to await further follow-up of the data to see if the [monarchE] curves continue to separate while on treatment.”

According to Giuseppe Curigliano, MD, PhD, head of the Division of Early Drug Development at the European Institute of Oncology, Milan, Italy, “This is a very important trial and the findings will change practice. Once approved for high risk HR+ HER2-negative early breast cancer, the new standard of care for these patients will be to add two years of abemaciclib to endocrine therapy.”

Curigliano, who was not involved with the study, further commented during a meeting press conference that a randomized trial will be needed to answer a new important question: Can these high-risk patients treated with a CDK4/6 inhibitor be spared chemotherapy?

Investigator Johnston pointed out that many patients diagnosed with HR+, HER2 breast cancer will not experience recurrence with standard-of-care therapies.

But he also explained “that up to 20% may develop recurrence or distant relapse in the first 10 years” and that the risk of recurrence is “much greater” for patients who have high-risk clinical or pathological features, “especially during the first few years on their adjuvant endocrine therapy.”
 

Study details

Abemaciclib was approved by the US Food and Drug Administration in 2017 and is approved in combination with the endocrine therapy fulvestrant for the treatment of HR+, HER2-negative advanced or metastatic breast cancer that has progressed after endocrine therapy.

The approval was, in part, based on data from the MONARCH-2 trial, which showed consistent overall survival benefits with the combination.

MonarchE, on the other hand, examined the impact of abemaciclib in the first-line adjuvant setting, enrolling patients with HR+, HER2-negative, node-positive early breast cancer who had a tumor size of ≥5 cm, histologic grade 3 disease, and/or Ki67 index of ≥20%.

They were randomly assigned in a 1:1 fashion to abemaciclib 150 mg twice daily for up to 2 years plus standard of care endocrine therapy or standard of care endocrine therapy alone.

The choice of endocrine therapy was left to the physician and was continued for 5-10 years, as clinically indicated.

The trial included 5,637 patients. An efficacy interim analysis was planned for when 75% of the estimated invasive disease-free survival events had occurred, which equated to 323 events in the intention-to-treat population.

This occurred after approximately 15.5 months of follow-up in each arm, when 12.5% of patients had completed the 2-year treatment period, leaving 70% still in treatment.

The intention-to-treat population included 2,808 patients from the abemaciclib plus endocrine therapy group and 2,829 in the group taking endocrine therapy alone.

The two groups were well balanced in terms of their baseline characteristics. The vast majority (approximately 85%) of patients were younger than 65 years, and 56.5% were postmenopausal.

Also, 37% had previously received neoadjuvant chemotherapy, and approximately 58% had adjuvant chemotherapy.

Distant relapse-free survival was significantly reduced with abemaciclib plus endocrine therapy vs endocrine therapy alone, at a hazard ratio of 0.72 (P = .0085), and a 2-year rate of 93.6% and 90.3%, respectively.

Johnston highlighted that not only was the number of patients with distant recurrences reduced with the combination therapy, at 92 vs 142 with endocrine therapy alone, but also the reductions were in key locations.

The number of patients with recurrences in the bone were 32 with abemaciclib and 81 with endocrine therapy alone; 29 patients with abemaciclib and 42 with endocrine therapy alone had recurrences in the liver.

The results show that the most frequent adverse events in the abemaciclib arm were diarrhea (82%), neutropenia (45%), and fatigue (38%), whereas arthralgia (31%), hot flush (21%), and fatigue (15%) were seen most often in the control group.

Venous thromboembolic events were recorded in 2.3% of patients in the abemaciclib group versus 0.5% of those on endocrine therapy alone; interstitial lung disease was seen in 2.7% and 1.2%, respectively.

Despite the protocol allowing dose reductions from 150 mg to 100 mg twice daily if required, 463 (16.6%) patients discontinued abemaciclib as a result of adverse events. Of those, 306 continued on endocrine therapy.

“Adherence to treatment will be an important issue to be considered in the real-life population of patients when this treatment is approved and used in clinical practice,” Johnston said.

Nevertheless, diarrhea frequency and severity decreased significantly over time, and only 4.8% of the abemaciclib group discontinued use as a result of this adverse event.
 

Questions remain

George W. Sledge Jr, MD, professor of medicine (oncology) at Stanford University Medical Center, Palo Alto, California, was the invited discussant after the presentation.

He said that “positive trials raise as many questions as they answer, and monarchE is no exception.”

For example, there is the conundrum posed by the negative results of the very similar PALLAS trial, which looked at the addition of palbociclib to adjuvant endocrine therapy for HR+, HER2-negative early breast cancer and was also presented at the ESMO meeting.

Returning to monarchE, Sledge asked what the ultimate increase in invasive disease- and distant relapse-free survival will be with the drug combination, noting that the trial has “very, very short follow-up.”

“Second, will the improvements seen in disease-free survival lead to what we really care about: improved overall survival? Again, time will tell, but health care systems and patients care deeply about the answer to this question.”

Sledge continued: “How about late recurrence? Do CDK4/6 inhibitors kill off dormant or slow-growing micro-mets that lead to recurrences 5 or more years out?”

He also asked what the optimum duration of therapy would be: “Is it more than we need, or not enough?”

Sledge wondered whether it is possible to determine who benefits “and why the drug fails some patients.”

Finally, Sledge said, “These drugs are expensive. ... 2 years of adjuvant therapy is simply out of reach for the majority of patients around the globe who might be candidates for adjuvant CDK4/6 inhibitor therapy.”

And he observed an important truism: “A patient cannot benefit from a drug she cannot take.”

The study was funded by Eli Lilly. Johnston, Sledge, and Curigliano have financial ties to Eli Lilly and multiple other drug companies.
 

This article first appeared on Medscape.com.

Adding the CDK4/6 inhibitor abemaciclib (Verzenio) to endocrine therapy significantly reduces the risk of early recurrence in high-risk hormone receptor positive (HR+), human epidermal growth factor receptor 2 (HER2)–negative breast cancer, suggests a preplanned interim analysis of a phase 3 trial.

The research was presented Sept. 19 at the ESMO Virtual Congress 2020 and simultaneously published in the Journal of Clinical Oncology.

The monarchE trial compared 2 years of abemaciclib plus endocrine therapy vs endocrine therapy alone among 5,600 patients and found that the combination was associated with a 25% relative risk reduction in the primary endpoint – invasive disease-free survival (P =.0096; HR, 0.75; 95% CI, 0.60 - 0.93)

At 2 years, the rate of invasive disease-free survival was 92.2% in the abemaciclib arm vs 88.7% in the group that took endocrine therapy alone.

“This is the first time in more than 20 years that we have seen an advance in the adjuvant treatment of this form of breast cancer,” said lead investigator Stephen Johnston, MD, PhD, from the Royal Marsden Hospital NHS Foundation Trust in London, UK, in a meeting press release.

He told Medscape Medical News that the high-risk patients in their study “are predicted to relapse quite quickly” as a result of having a degree of endocrine resistance, “and by intervening early we are stopping these recurrences within the first 2 years.”

He continued: “The key issue ... is whether you need 2 years of treatment or perhaps even longer. One other trial is looking at 3 years with another drug, and we’ll just have to await further follow-up of the data to see if the [monarchE] curves continue to separate while on treatment.”

According to Giuseppe Curigliano, MD, PhD, head of the Division of Early Drug Development at the European Institute of Oncology, Milan, Italy, “This is a very important trial and the findings will change practice. Once approved for high risk HR+ HER2-negative early breast cancer, the new standard of care for these patients will be to add two years of abemaciclib to endocrine therapy.”

Curigliano, who was not involved with the study, further commented during a meeting press conference that a randomized trial will be needed to answer a new important question: Can these high-risk patients treated with a CDK4/6 inhibitor be spared chemotherapy?

Investigator Johnston pointed out that many patients diagnosed with HR+, HER2 breast cancer will not experience recurrence with standard-of-care therapies.

But he also explained “that up to 20% may develop recurrence or distant relapse in the first 10 years” and that the risk of recurrence is “much greater” for patients who have high-risk clinical or pathological features, “especially during the first few years on their adjuvant endocrine therapy.”
 

Study details

Abemaciclib was approved by the US Food and Drug Administration in 2017 and is approved in combination with the endocrine therapy fulvestrant for the treatment of HR+, HER2-negative advanced or metastatic breast cancer that has progressed after endocrine therapy.

The approval was, in part, based on data from the MONARCH-2 trial, which showed consistent overall survival benefits with the combination.

MonarchE, on the other hand, examined the impact of abemaciclib in the first-line adjuvant setting, enrolling patients with HR+, HER2-negative, node-positive early breast cancer who had a tumor size of ≥5 cm, histologic grade 3 disease, and/or Ki67 index of ≥20%.

They were randomly assigned in a 1:1 fashion to abemaciclib 150 mg twice daily for up to 2 years plus standard of care endocrine therapy or standard of care endocrine therapy alone.

The choice of endocrine therapy was left to the physician and was continued for 5-10 years, as clinically indicated.

The trial included 5,637 patients. An efficacy interim analysis was planned for when 75% of the estimated invasive disease-free survival events had occurred, which equated to 323 events in the intention-to-treat population.

This occurred after approximately 15.5 months of follow-up in each arm, when 12.5% of patients had completed the 2-year treatment period, leaving 70% still in treatment.

The intention-to-treat population included 2,808 patients from the abemaciclib plus endocrine therapy group and 2,829 in the group taking endocrine therapy alone.

The two groups were well balanced in terms of their baseline characteristics. The vast majority (approximately 85%) of patients were younger than 65 years, and 56.5% were postmenopausal.

Also, 37% had previously received neoadjuvant chemotherapy, and approximately 58% had adjuvant chemotherapy.

Distant relapse-free survival was significantly reduced with abemaciclib plus endocrine therapy vs endocrine therapy alone, at a hazard ratio of 0.72 (P = .0085), and a 2-year rate of 93.6% and 90.3%, respectively.

Johnston highlighted that not only was the number of patients with distant recurrences reduced with the combination therapy, at 92 vs 142 with endocrine therapy alone, but also the reductions were in key locations.

The number of patients with recurrences in the bone were 32 with abemaciclib and 81 with endocrine therapy alone; 29 patients with abemaciclib and 42 with endocrine therapy alone had recurrences in the liver.

The results show that the most frequent adverse events in the abemaciclib arm were diarrhea (82%), neutropenia (45%), and fatigue (38%), whereas arthralgia (31%), hot flush (21%), and fatigue (15%) were seen most often in the control group.

Venous thromboembolic events were recorded in 2.3% of patients in the abemaciclib group versus 0.5% of those on endocrine therapy alone; interstitial lung disease was seen in 2.7% and 1.2%, respectively.

Despite the protocol allowing dose reductions from 150 mg to 100 mg twice daily if required, 463 (16.6%) patients discontinued abemaciclib as a result of adverse events. Of those, 306 continued on endocrine therapy.

“Adherence to treatment will be an important issue to be considered in the real-life population of patients when this treatment is approved and used in clinical practice,” Johnston said.

Nevertheless, diarrhea frequency and severity decreased significantly over time, and only 4.8% of the abemaciclib group discontinued use as a result of this adverse event.
 

Questions remain

George W. Sledge Jr, MD, professor of medicine (oncology) at Stanford University Medical Center, Palo Alto, California, was the invited discussant after the presentation.

He said that “positive trials raise as many questions as they answer, and monarchE is no exception.”

For example, there is the conundrum posed by the negative results of the very similar PALLAS trial, which looked at the addition of palbociclib to adjuvant endocrine therapy for HR+, HER2-negative early breast cancer and was also presented at the ESMO meeting.

Returning to monarchE, Sledge asked what the ultimate increase in invasive disease- and distant relapse-free survival will be with the drug combination, noting that the trial has “very, very short follow-up.”

“Second, will the improvements seen in disease-free survival lead to what we really care about: improved overall survival? Again, time will tell, but health care systems and patients care deeply about the answer to this question.”

Sledge continued: “How about late recurrence? Do CDK4/6 inhibitors kill off dormant or slow-growing micro-mets that lead to recurrences 5 or more years out?”

He also asked what the optimum duration of therapy would be: “Is it more than we need, or not enough?”

Sledge wondered whether it is possible to determine who benefits “and why the drug fails some patients.”

Finally, Sledge said, “These drugs are expensive. ... 2 years of adjuvant therapy is simply out of reach for the majority of patients around the globe who might be candidates for adjuvant CDK4/6 inhibitor therapy.”

And he observed an important truism: “A patient cannot benefit from a drug she cannot take.”

The study was funded by Eli Lilly. Johnston, Sledge, and Curigliano have financial ties to Eli Lilly and multiple other drug companies.
 

This article first appeared on Medscape.com.

During my sophomore year in high school, we had to read a historical essay about cars, the author and name of which I’ve long forgotten. The basic point of it was that, as of 1982, no invention had changed Western culture more than the automobile.

In America, the car is king. A large portion of society revolves around cars and their trappings: modifications, sports, collectors auctions, parking lots and garages, and many others. The city of Detroit has become synonymous with one industry.

A few times a week I have to walk two to three blocks to and from a research office to see patients and do paperwork. This involves me cutting through a series of parking lots, including one garage, that service the office buildings in the area. For years they’ve always been full on weekdays.

Now, after 6 months of pandemic, they’re maybe 10% filled. Rows and rows of empty spaces certainly makes my walks easier.

But each time I walk there now I wonder where this will lead. The people who used to park still work there, just from home now. If they can work from home successfully for 6 months, why should they even come back to the office on a routine basis?

I don’t think it’s the end of the automobile by any means. The majority of us still depend on it for many things and will continue to do so for a long time to come. I need it to get to my office, the hospital, the store, to take my oldest to and from his job, and many other things.

But perhaps the pandemic will also bring a lasting change in how and where many do their jobs. It’s certainly driven a dramatic shift to Zoom, Teams, WebEx, Skype, and other remote platforms.

If they’re not really needed, having fewer cars on the road is probably a good thing. It saves commute time, reduces oil dependence and pollution, and provides a number of other benefits. If sustained, in the long term it will affect the calculus of office space and buildings, parking lot sizes, and a million other details.

My secretary has been working from home since late March now. While I miss having her and her daughter at the office, her lack of a commute means she starts taking calls an hour earlier and isn’t spending $60-$100 a week on gas.

We’ll have to see how it all plays out. Like other adverse events that change society, not all of the changes in the aftermath may be bad ones.

The car will be king in America for a long time to come, but its role in commuting may be fundamentally different after the pandemic, and the ripples from this may bring many more changes – hopefully for the better.

Dr. Block has a solo neurology practice in Scottsdale, Ariz.

During my sophomore year in high school, we had to read a historical essay about cars, the author and name of which I’ve long forgotten. The basic point of it was that, as of 1982, no invention had changed Western culture more than the automobile.

In America, the car is king. A large portion of society revolves around cars and their trappings: modifications, sports, collectors auctions, parking lots and garages, and many others. The city of Detroit has become synonymous with one industry.

A few times a week I have to walk two to three blocks to and from a research office to see patients and do paperwork. This involves me cutting through a series of parking lots, including one garage, that service the office buildings in the area. For years they’ve always been full on weekdays.

Now, after 6 months of pandemic, they’re maybe 10% filled. Rows and rows of empty spaces certainly makes my walks easier.

But each time I walk there now I wonder where this will lead. The people who used to park still work there, just from home now. If they can work from home successfully for 6 months, why should they even come back to the office on a routine basis?

I don’t think it’s the end of the automobile by any means. The majority of us still depend on it for many things and will continue to do so for a long time to come. I need it to get to my office, the hospital, the store, to take my oldest to and from his job, and many other things.

But perhaps the pandemic will also bring a lasting change in how and where many do their jobs. It’s certainly driven a dramatic shift to Zoom, Teams, WebEx, Skype, and other remote platforms.

If they’re not really needed, having fewer cars on the road is probably a good thing. It saves commute time, reduces oil dependence and pollution, and provides a number of other benefits. If sustained, in the long term it will affect the calculus of office space and buildings, parking lot sizes, and a million other details.

My secretary has been working from home since late March now. While I miss having her and her daughter at the office, her lack of a commute means she starts taking calls an hour earlier and isn’t spending $60-$100 a week on gas.

We’ll have to see how it all plays out. Like other adverse events that change society, not all of the changes in the aftermath may be bad ones.

The car will be king in America for a long time to come, but its role in commuting may be fundamentally different after the pandemic, and the ripples from this may bring many more changes – hopefully for the better.

Dr. Block has a solo neurology practice in Scottsdale, Ariz.

During my sophomore year in high school, we had to read a historical essay about cars, the author and name of which I’ve long forgotten. The basic point of it was that, as of 1982, no invention had changed Western culture more than the automobile.

In America, the car is king. A large portion of society revolves around cars and their trappings: modifications, sports, collectors auctions, parking lots and garages, and many others. The city of Detroit has become synonymous with one industry.

A few times a week I have to walk two to three blocks to and from a research office to see patients and do paperwork. This involves me cutting through a series of parking lots, including one garage, that service the office buildings in the area. For years they’ve always been full on weekdays.

Now, after 6 months of pandemic, they’re maybe 10% filled. Rows and rows of empty spaces certainly makes my walks easier.

But each time I walk there now I wonder where this will lead. The people who used to park still work there, just from home now. If they can work from home successfully for 6 months, why should they even come back to the office on a routine basis?

I don’t think it’s the end of the automobile by any means. The majority of us still depend on it for many things and will continue to do so for a long time to come. I need it to get to my office, the hospital, the store, to take my oldest to and from his job, and many other things.

But perhaps the pandemic will also bring a lasting change in how and where many do their jobs. It’s certainly driven a dramatic shift to Zoom, Teams, WebEx, Skype, and other remote platforms.

If they’re not really needed, having fewer cars on the road is probably a good thing. It saves commute time, reduces oil dependence and pollution, and provides a number of other benefits. If sustained, in the long term it will affect the calculus of office space and buildings, parking lot sizes, and a million other details.

My secretary has been working from home since late March now. While I miss having her and her daughter at the office, her lack of a commute means she starts taking calls an hour earlier and isn’t spending $60-$100 a week on gas.

We’ll have to see how it all plays out. Like other adverse events that change society, not all of the changes in the aftermath may be bad ones.

The car will be king in America for a long time to come, but its role in commuting may be fundamentally different after the pandemic, and the ripples from this may bring many more changes – hopefully for the better.

Dr. Block has a solo neurology practice in Scottsdale, Ariz.

More female physicians are becoming specialists, a Medscape survey finds, and five specialties have seen particularly large increases during the last 5 years.

kate_sept2004/E+

Obstetrician/gynecologists and pediatricians had the largest female representation at 58% and those percentages were both up from 50% in 2015, according to the Medscape Female Physician Compensation Report 2020.

Rheumatology saw a dramatic jump in numbers of women from 29% in 2015 to 54% now. Dermatology increased from 32% to 49%, and family medicine rose from 35% to 43% during that time.
 

Specialist pay gap narrows slightly

As in the past 10 years of the survey, female physicians continue to make less than their male colleagues. The gender gap was the same this year in primary care — women made 25% less ($212,000 vs. $264,000).

The gap in specialists narrowed slightly. Women made 31% less this year ($286,000 vs $375,000) instead of the 33% less reported in last year’s survey, a difference of $89,000 this year.

The gender pay gap was consistent across all race and age groups and was consistent in responses about net worth. Whereas 57% of male physicians had a net worth of $1 million or more, only 40% of female physicians did. Twice as many male physicians as female physicians had a net worth of more than $5 million (10% vs. 5%).

“Many physicians expect the gender pay gap to narrow in the coming years,” John Prescott, MD, chief academic officer of the Association of American Medical Colleges, said in an interview.

“Yet, it is a challenging task, requiring an institutional commitment to transparency, cross-campus collaboration, ongoing communication, dedicated resources, and enlightened leadership,” he said.

Female physicians working in office-based, solo practices made the most overall at $290,000; women in outpatient settings made the least at $223,000.

The survey included more than 4,500 responses. The responses were collected during the early part of the year and do not reflect changes in income expected from the COVID-19 pandemic.

An analysis in Health Affairs, for instance, predicted that primary care practices would lose $67,774 in gross revenue per full-time-equivalent physician in calendar year 2020 because of the pandemic.

Most physicians did not experience a significant financial loss in 2019, but COVID-19 may, at least temporarily, change those answers in next year’s report, physicians predicted.
 

Women more likely than men to live above their means

More women this year (39%) said they live below their means than answered that way last year (31%). Female physicians were more likely to say they lived above their means than were their male counterparts (8% vs. 6%).

Greenwald Wealth Management in St. Louis Park, Minn., says aiming for putting away 20% of total gross salary is a good financial goal.

Women in this year’s survey spent about 7% less time seeing patients than did their male counterparts (35.9 hours a week vs. 38.8). The average for all physicians was 37.8 hours a week. Add the 15.6 average hours per week physicians spend on paperwork, and they are putting in 53-hour workweeks on average overall.

Asked what parts of their job they found most rewarding, women were more likely than were men to say “gratitude/relationships with patients” (31% vs. 25%). They were less likely than were men to answer that the most rewarding part was “being very good at what I do/finding answers/diagnoses” (22% vs. 25%) or “making good money at a job I like” (9% vs. 13%).

Most female physicians — and physicians overall — said they would choose medicine again. But two specialties saw a substantial increase in that answer.

This year, 79% of those in physical medicine and rehabilitation said they would choose medicine again (compared with 66% last year) and 84% of gastroenterologists answered that way (compared with 76% in 2019).

Psychiatrists, however, were in the group least likely to say they would choose their specialty again along with those in internal medicine, family medicine, and diabetes and endocrinology.

Female physicians in orthopedics, radiology, and dermatology were most likely to choose their specialties again (91% - 92%).

Female physicians were less likely to use physician assistants in their practices than were their male colleagues (31% vs. 38%) but more likely to use NPs (52% vs. 50%). More than a third (38%) of male and female physicians reported they use neither.
 

A version of this article originally appeared on Medscape.com.

More female physicians are becoming specialists, a Medscape survey finds, and five specialties have seen particularly large increases during the last 5 years.

kate_sept2004/E+

Obstetrician/gynecologists and pediatricians had the largest female representation at 58% and those percentages were both up from 50% in 2015, according to the Medscape Female Physician Compensation Report 2020.

Rheumatology saw a dramatic jump in numbers of women from 29% in 2015 to 54% now. Dermatology increased from 32% to 49%, and family medicine rose from 35% to 43% during that time.
 

Specialist pay gap narrows slightly

As in the past 10 years of the survey, female physicians continue to make less than their male colleagues. The gender gap was the same this year in primary care — women made 25% less ($212,000 vs. $264,000).

The gap in specialists narrowed slightly. Women made 31% less this year ($286,000 vs $375,000) instead of the 33% less reported in last year’s survey, a difference of $89,000 this year.

The gender pay gap was consistent across all race and age groups and was consistent in responses about net worth. Whereas 57% of male physicians had a net worth of $1 million or more, only 40% of female physicians did. Twice as many male physicians as female physicians had a net worth of more than $5 million (10% vs. 5%).

“Many physicians expect the gender pay gap to narrow in the coming years,” John Prescott, MD, chief academic officer of the Association of American Medical Colleges, said in an interview.

“Yet, it is a challenging task, requiring an institutional commitment to transparency, cross-campus collaboration, ongoing communication, dedicated resources, and enlightened leadership,” he said.

Female physicians working in office-based, solo practices made the most overall at $290,000; women in outpatient settings made the least at $223,000.

The survey included more than 4,500 responses. The responses were collected during the early part of the year and do not reflect changes in income expected from the COVID-19 pandemic.

An analysis in Health Affairs, for instance, predicted that primary care practices would lose $67,774 in gross revenue per full-time-equivalent physician in calendar year 2020 because of the pandemic.

Most physicians did not experience a significant financial loss in 2019, but COVID-19 may, at least temporarily, change those answers in next year’s report, physicians predicted.
 

Women more likely than men to live above their means

More women this year (39%) said they live below their means than answered that way last year (31%). Female physicians were more likely to say they lived above their means than were their male counterparts (8% vs. 6%).

Greenwald Wealth Management in St. Louis Park, Minn., says aiming for putting away 20% of total gross salary is a good financial goal.

Women in this year’s survey spent about 7% less time seeing patients than did their male counterparts (35.9 hours a week vs. 38.8). The average for all physicians was 37.8 hours a week. Add the 15.6 average hours per week physicians spend on paperwork, and they are putting in 53-hour workweeks on average overall.

Asked what parts of their job they found most rewarding, women were more likely than were men to say “gratitude/relationships with patients” (31% vs. 25%). They were less likely than were men to answer that the most rewarding part was “being very good at what I do/finding answers/diagnoses” (22% vs. 25%) or “making good money at a job I like” (9% vs. 13%).

Most female physicians — and physicians overall — said they would choose medicine again. But two specialties saw a substantial increase in that answer.

This year, 79% of those in physical medicine and rehabilitation said they would choose medicine again (compared with 66% last year) and 84% of gastroenterologists answered that way (compared with 76% in 2019).

Psychiatrists, however, were in the group least likely to say they would choose their specialty again along with those in internal medicine, family medicine, and diabetes and endocrinology.

Female physicians in orthopedics, radiology, and dermatology were most likely to choose their specialties again (91% - 92%).

Female physicians were less likely to use physician assistants in their practices than were their male colleagues (31% vs. 38%) but more likely to use NPs (52% vs. 50%). More than a third (38%) of male and female physicians reported they use neither.
 

A version of this article originally appeared on Medscape.com.

More female physicians are becoming specialists, a Medscape survey finds, and five specialties have seen particularly large increases during the last 5 years.

kate_sept2004/E+

Obstetrician/gynecologists and pediatricians had the largest female representation at 58% and those percentages were both up from 50% in 2015, according to the Medscape Female Physician Compensation Report 2020.

Rheumatology saw a dramatic jump in numbers of women from 29% in 2015 to 54% now. Dermatology increased from 32% to 49%, and family medicine rose from 35% to 43% during that time.
 

Specialist pay gap narrows slightly

As in the past 10 years of the survey, female physicians continue to make less than their male colleagues. The gender gap was the same this year in primary care — women made 25% less ($212,000 vs. $264,000).

The gap in specialists narrowed slightly. Women made 31% less this year ($286,000 vs $375,000) instead of the 33% less reported in last year’s survey, a difference of $89,000 this year.

The gender pay gap was consistent across all race and age groups and was consistent in responses about net worth. Whereas 57% of male physicians had a net worth of $1 million or more, only 40% of female physicians did. Twice as many male physicians as female physicians had a net worth of more than $5 million (10% vs. 5%).

“Many physicians expect the gender pay gap to narrow in the coming years,” John Prescott, MD, chief academic officer of the Association of American Medical Colleges, said in an interview.

“Yet, it is a challenging task, requiring an institutional commitment to transparency, cross-campus collaboration, ongoing communication, dedicated resources, and enlightened leadership,” he said.

Female physicians working in office-based, solo practices made the most overall at $290,000; women in outpatient settings made the least at $223,000.

The survey included more than 4,500 responses. The responses were collected during the early part of the year and do not reflect changes in income expected from the COVID-19 pandemic.

An analysis in Health Affairs, for instance, predicted that primary care practices would lose $67,774 in gross revenue per full-time-equivalent physician in calendar year 2020 because of the pandemic.

Most physicians did not experience a significant financial loss in 2019, but COVID-19 may, at least temporarily, change those answers in next year’s report, physicians predicted.
 

Women more likely than men to live above their means

More women this year (39%) said they live below their means than answered that way last year (31%). Female physicians were more likely to say they lived above their means than were their male counterparts (8% vs. 6%).

Greenwald Wealth Management in St. Louis Park, Minn., says aiming for putting away 20% of total gross salary is a good financial goal.

Women in this year’s survey spent about 7% less time seeing patients than did their male counterparts (35.9 hours a week vs. 38.8). The average for all physicians was 37.8 hours a week. Add the 15.6 average hours per week physicians spend on paperwork, and they are putting in 53-hour workweeks on average overall.

Asked what parts of their job they found most rewarding, women were more likely than were men to say “gratitude/relationships with patients” (31% vs. 25%). They were less likely than were men to answer that the most rewarding part was “being very good at what I do/finding answers/diagnoses” (22% vs. 25%) or “making good money at a job I like” (9% vs. 13%).

Most female physicians — and physicians overall — said they would choose medicine again. But two specialties saw a substantial increase in that answer.

This year, 79% of those in physical medicine and rehabilitation said they would choose medicine again (compared with 66% last year) and 84% of gastroenterologists answered that way (compared with 76% in 2019).

Psychiatrists, however, were in the group least likely to say they would choose their specialty again along with those in internal medicine, family medicine, and diabetes and endocrinology.

Female physicians in orthopedics, radiology, and dermatology were most likely to choose their specialties again (91% - 92%).

Female physicians were less likely to use physician assistants in their practices than were their male colleagues (31% vs. 38%) but more likely to use NPs (52% vs. 50%). More than a third (38%) of male and female physicians reported they use neither.
 

A version of this article originally appeared on Medscape.com.

President Donald Trump, who seems intent on announcing a COVID-19 vaccine before Election Day, could legally authorize a vaccine over the objections of experts, officials at the Food and Drug Administration and even vaccine manufacturers, who have pledged not to release any vaccine unless it’s proved safe and effective.

In podcasts, public forums, social media and medical journals, a growing number of prominent health leaders say they fear that Mr. Trump – who has repeatedly signaled his desire for the swift approval of a vaccine and his displeasure with perceived delays at the FDA – will take matters into his own hands, running roughshod over the usual regulatory process.

It would reflect another attempt by a norm-breaking administration, poised to ram through a Supreme Court nominee opposed to existing abortion rights and the Affordable Care Act, to inject politics into sensitive public health decisions. Mr. Trump has repeatedly contradicted the advice of senior scientists on COVID-19 while pushing controversial treatments for the disease.

If the executive branch were to overrule the FDA’s scientific judgment, a vaccine of limited efficacy and, worse, unknown side effects could be rushed to market.

The worries intensified over the weekend, after Alex Azar, the administration’s secretary of Health & Human Services, asserted his agency’s rule-making authority over the FDA. HHS spokesperson Caitlin Oakley said Mr. Azar’s decision had no bearing on the vaccine approval process.

Vaccines are typically approved by the FDA. Alternatively, Mr. Azar – who reports directly to Mr. Trump – can issue an emergency use authorization, even before any vaccines have been shown to be safe and effective in late-stage clinical trials.

“Yes, this scenario is certainly possible legally and politically,” said Jerry Avorn, MD, a professor of medicine at Harvard Medical School, who outlined such an event in the New England Journal of Medicine. He said it “seems frighteningly more plausible each day.”

Vaccine experts and public health officials are particularly vexed by the possibility because it could ruin the fragile public confidence in a COVID-19 vaccine. It might put scientific authorities in the position of urging people not to be vaccinated after years of coaxing hesitant parents to ignore baseless fears.

Physicians might refuse to administer a vaccine approved with inadequate data, said Preeti Malani, MD, chief health officer and professor of medicine at the University of Michigan in Ann Arbor, in a recent webinar. “You could have a safe, effective vaccine that no one wants to take.” A recent KFF poll found that 54% of Americans would not submit to a COVID-19 vaccine authorized before Election Day.

After this story was published, an HHS official said that Mr. Azar “will defer completely to the FDA” as the agency weighs whether to approve a vaccine produced through the government’s Operation Warp Speed effort.

“The idea the Secretary would approve or authorize a vaccine over the FDA’s objections is preposterous and betrays ignorance of the transparent process that we’re following for the development of the OWS vaccines,” HHS chief of staff Brian Harrison wrote in an email.

White House spokesperson Judd Deere dismissed the scientists’ concerns, saying Trump cared only about the public’s safety and health. “This false narrative that the media and Democrats have created that politics is influencing approvals is not only false but is a danger to the American public,” he said.

Usually, the FDA approves vaccines only after companies submit years of data proving that a vaccine is safe and effective. But a 2004 law allows the FDA to issue an emergency use authorization with much less evidence, as long as the vaccine “may be effective” and its “known and potential benefits” outweigh its “known and potential risks.”

Many scientists doubt a vaccine could meet those criteria before the election. But the terms might be legally vague enough to allow the administration to take such steps.

Moncef Slaoui, chief scientific adviser to Operation Warp Speed, the government program aiming to more quickly develop COVID-19 vaccines, said it’s “extremely unlikely” that vaccine trial results will be ready before the end of October.

Mr. Trump, however, has insisted repeatedly that a vaccine to fight the pandemic that has claimed 200,000 American lives will be distributed starting next month. He reiterated that claim Saturday at a campaign rally in Fayetteville, N.C.

The vaccine will be ready “in a matter of weeks,” he said. “We will end the pandemic from China.”

Although pharmaceutical companies have launched three clinical trials in the United States, no one can say with certainty when those trials will have enough data to determine whether the vaccines are safe and effective.

Officials at Moderna, whose vaccine is being tested in 30,000 volunteers, have said their studies could produce a result by the end of the year, although the final analysis could take place next spring.

Pfizer executives, who have expanded their clinical trial to 44,000 participants, boast that they could know their vaccine works by the end of October.

AstraZeneca’s U.S. vaccine trial, which was scheduled to enroll 30,000 volunteers, is on hold pending an investigation of a possible vaccine-related illness.

Scientists have warned for months that the Trump administration could try to win the election with an “October surprise,” authorizing a vaccine that hasn’t been fully tested. “I don’t think people are crazy to be thinking about all of this,” said William Schultz, a partner in a Washington, D.C., law firm who served as a former FDA commissioner for policy and as general counsel for HHS.

“You’ve got a president saying you’ll have an approval in October. Everybody’s wondering how that could happen.”

In an opinion piece published in the Wall Street Journal, conservative former FDA commissioners Scott Gottlieb and Mark McClellan argued that presidential intrusion was unlikely because the FDA’s “thorough and transparent process doesn’t lend itself to meddling. Any deviation would quickly be apparent.”

But the administration has demonstrated a willingness to bend the agency to its will. The FDA has been criticized for issuing emergency authorizations for two COVID-19 treatments that were boosted by the president but lacked strong evidence to support them: hydroxychloroquine and convalescent plasma.

Mr. Azar has sidelined the FDA in other ways, such as by blocking the agency from regulating lab-developed tests, including tests for the novel coronavirus.

Although FDA Commissioner Stephen Hahn told the Financial Times he would be willing to approve emergency use of a vaccine before large-scale studies conclude, agency officials also have pledged to ensure the safety of any COVID-19 vaccines.

A senior FDA official who oversees vaccine approvals, Peter Marks, MD, has said he will quit if his agency rubber-stamps an unproven COVID-19 vaccine.

“I think there would be an outcry from the public health community second to none, which is my worst nightmare – my worst nightmare – because we will so confuse the public,” said Michael Osterholm, PhD, director of the Center for Infectious Disease Research and Policy at the University of Minnesota, in his weekly podcast.

Still, “even if a company did not want it to be done, even if the FDA did not want it to be done, he could still do that,” said Dr. Osterholm, in his podcast. “I hope that we’d never see that happen, but we have to entertain that’s a possibility.”

In the New England Journal editorial, Dr. Avorn and coauthor Aaron Kesselheim, MD, wondered whether Mr. Trump might invoke the 1950 Defense Production Act to force reluctant drug companies to manufacture their vaccines.

But Mr. Trump would have to sue a company to enforce the Defense Production Act, and the company would have a strong case in refusing, said Lawrence Gostin, director of Georgetown’s O’Neill Institute for National and Global Health Law.

Also, he noted that Mr. Trump could not invoke the Defense Production Act unless a vaccine were “scientifically justified and approved by the FDA.”

Kaiser Health News is a nonprofit news service covering health issues. It is an editorially independent program of KFF (Kaiser Family Foundation), which is not affiliated with Kaiser Permanente.

President Donald Trump, who seems intent on announcing a COVID-19 vaccine before Election Day, could legally authorize a vaccine over the objections of experts, officials at the Food and Drug Administration and even vaccine manufacturers, who have pledged not to release any vaccine unless it’s proved safe and effective.

In podcasts, public forums, social media and medical journals, a growing number of prominent health leaders say they fear that Mr. Trump – who has repeatedly signaled his desire for the swift approval of a vaccine and his displeasure with perceived delays at the FDA – will take matters into his own hands, running roughshod over the usual regulatory process.

It would reflect another attempt by a norm-breaking administration, poised to ram through a Supreme Court nominee opposed to existing abortion rights and the Affordable Care Act, to inject politics into sensitive public health decisions. Mr. Trump has repeatedly contradicted the advice of senior scientists on COVID-19 while pushing controversial treatments for the disease.

If the executive branch were to overrule the FDA’s scientific judgment, a vaccine of limited efficacy and, worse, unknown side effects could be rushed to market.

The worries intensified over the weekend, after Alex Azar, the administration’s secretary of Health & Human Services, asserted his agency’s rule-making authority over the FDA. HHS spokesperson Caitlin Oakley said Mr. Azar’s decision had no bearing on the vaccine approval process.

Vaccines are typically approved by the FDA. Alternatively, Mr. Azar – who reports directly to Mr. Trump – can issue an emergency use authorization, even before any vaccines have been shown to be safe and effective in late-stage clinical trials.

“Yes, this scenario is certainly possible legally and politically,” said Jerry Avorn, MD, a professor of medicine at Harvard Medical School, who outlined such an event in the New England Journal of Medicine. He said it “seems frighteningly more plausible each day.”

Vaccine experts and public health officials are particularly vexed by the possibility because it could ruin the fragile public confidence in a COVID-19 vaccine. It might put scientific authorities in the position of urging people not to be vaccinated after years of coaxing hesitant parents to ignore baseless fears.

Physicians might refuse to administer a vaccine approved with inadequate data, said Preeti Malani, MD, chief health officer and professor of medicine at the University of Michigan in Ann Arbor, in a recent webinar. “You could have a safe, effective vaccine that no one wants to take.” A recent KFF poll found that 54% of Americans would not submit to a COVID-19 vaccine authorized before Election Day.

After this story was published, an HHS official said that Mr. Azar “will defer completely to the FDA” as the agency weighs whether to approve a vaccine produced through the government’s Operation Warp Speed effort.

“The idea the Secretary would approve or authorize a vaccine over the FDA’s objections is preposterous and betrays ignorance of the transparent process that we’re following for the development of the OWS vaccines,” HHS chief of staff Brian Harrison wrote in an email.

White House spokesperson Judd Deere dismissed the scientists’ concerns, saying Trump cared only about the public’s safety and health. “This false narrative that the media and Democrats have created that politics is influencing approvals is not only false but is a danger to the American public,” he said.

Usually, the FDA approves vaccines only after companies submit years of data proving that a vaccine is safe and effective. But a 2004 law allows the FDA to issue an emergency use authorization with much less evidence, as long as the vaccine “may be effective” and its “known and potential benefits” outweigh its “known and potential risks.”

Many scientists doubt a vaccine could meet those criteria before the election. But the terms might be legally vague enough to allow the administration to take such steps.

Moncef Slaoui, chief scientific adviser to Operation Warp Speed, the government program aiming to more quickly develop COVID-19 vaccines, said it’s “extremely unlikely” that vaccine trial results will be ready before the end of October.

Mr. Trump, however, has insisted repeatedly that a vaccine to fight the pandemic that has claimed 200,000 American lives will be distributed starting next month. He reiterated that claim Saturday at a campaign rally in Fayetteville, N.C.

The vaccine will be ready “in a matter of weeks,” he said. “We will end the pandemic from China.”

Although pharmaceutical companies have launched three clinical trials in the United States, no one can say with certainty when those trials will have enough data to determine whether the vaccines are safe and effective.

Officials at Moderna, whose vaccine is being tested in 30,000 volunteers, have said their studies could produce a result by the end of the year, although the final analysis could take place next spring.

Pfizer executives, who have expanded their clinical trial to 44,000 participants, boast that they could know their vaccine works by the end of October.

AstraZeneca’s U.S. vaccine trial, which was scheduled to enroll 30,000 volunteers, is on hold pending an investigation of a possible vaccine-related illness.

Scientists have warned for months that the Trump administration could try to win the election with an “October surprise,” authorizing a vaccine that hasn’t been fully tested. “I don’t think people are crazy to be thinking about all of this,” said William Schultz, a partner in a Washington, D.C., law firm who served as a former FDA commissioner for policy and as general counsel for HHS.

“You’ve got a president saying you’ll have an approval in October. Everybody’s wondering how that could happen.”

In an opinion piece published in the Wall Street Journal, conservative former FDA commissioners Scott Gottlieb and Mark McClellan argued that presidential intrusion was unlikely because the FDA’s “thorough and transparent process doesn’t lend itself to meddling. Any deviation would quickly be apparent.”

But the administration has demonstrated a willingness to bend the agency to its will. The FDA has been criticized for issuing emergency authorizations for two COVID-19 treatments that were boosted by the president but lacked strong evidence to support them: hydroxychloroquine and convalescent plasma.

Mr. Azar has sidelined the FDA in other ways, such as by blocking the agency from regulating lab-developed tests, including tests for the novel coronavirus.

Although FDA Commissioner Stephen Hahn told the Financial Times he would be willing to approve emergency use of a vaccine before large-scale studies conclude, agency officials also have pledged to ensure the safety of any COVID-19 vaccines.

A senior FDA official who oversees vaccine approvals, Peter Marks, MD, has said he will quit if his agency rubber-stamps an unproven COVID-19 vaccine.

“I think there would be an outcry from the public health community second to none, which is my worst nightmare – my worst nightmare – because we will so confuse the public,” said Michael Osterholm, PhD, director of the Center for Infectious Disease Research and Policy at the University of Minnesota, in his weekly podcast.

Still, “even if a company did not want it to be done, even if the FDA did not want it to be done, he could still do that,” said Dr. Osterholm, in his podcast. “I hope that we’d never see that happen, but we have to entertain that’s a possibility.”

In the New England Journal editorial, Dr. Avorn and coauthor Aaron Kesselheim, MD, wondered whether Mr. Trump might invoke the 1950 Defense Production Act to force reluctant drug companies to manufacture their vaccines.

But Mr. Trump would have to sue a company to enforce the Defense Production Act, and the company would have a strong case in refusing, said Lawrence Gostin, director of Georgetown’s O’Neill Institute for National and Global Health Law.

Also, he noted that Mr. Trump could not invoke the Defense Production Act unless a vaccine were “scientifically justified and approved by the FDA.”

Kaiser Health News is a nonprofit news service covering health issues. It is an editorially independent program of KFF (Kaiser Family Foundation), which is not affiliated with Kaiser Permanente.

President Donald Trump, who seems intent on announcing a COVID-19 vaccine before Election Day, could legally authorize a vaccine over the objections of experts, officials at the Food and Drug Administration and even vaccine manufacturers, who have pledged not to release any vaccine unless it’s proved safe and effective.

In podcasts, public forums, social media and medical journals, a growing number of prominent health leaders say they fear that Mr. Trump – who has repeatedly signaled his desire for the swift approval of a vaccine and his displeasure with perceived delays at the FDA – will take matters into his own hands, running roughshod over the usual regulatory process.

It would reflect another attempt by a norm-breaking administration, poised to ram through a Supreme Court nominee opposed to existing abortion rights and the Affordable Care Act, to inject politics into sensitive public health decisions. Mr. Trump has repeatedly contradicted the advice of senior scientists on COVID-19 while pushing controversial treatments for the disease.

If the executive branch were to overrule the FDA’s scientific judgment, a vaccine of limited efficacy and, worse, unknown side effects could be rushed to market.

The worries intensified over the weekend, after Alex Azar, the administration’s secretary of Health & Human Services, asserted his agency’s rule-making authority over the FDA. HHS spokesperson Caitlin Oakley said Mr. Azar’s decision had no bearing on the vaccine approval process.

Vaccines are typically approved by the FDA. Alternatively, Mr. Azar – who reports directly to Mr. Trump – can issue an emergency use authorization, even before any vaccines have been shown to be safe and effective in late-stage clinical trials.

“Yes, this scenario is certainly possible legally and politically,” said Jerry Avorn, MD, a professor of medicine at Harvard Medical School, who outlined such an event in the New England Journal of Medicine. He said it “seems frighteningly more plausible each day.”

Vaccine experts and public health officials are particularly vexed by the possibility because it could ruin the fragile public confidence in a COVID-19 vaccine. It might put scientific authorities in the position of urging people not to be vaccinated after years of coaxing hesitant parents to ignore baseless fears.

Physicians might refuse to administer a vaccine approved with inadequate data, said Preeti Malani, MD, chief health officer and professor of medicine at the University of Michigan in Ann Arbor, in a recent webinar. “You could have a safe, effective vaccine that no one wants to take.” A recent KFF poll found that 54% of Americans would not submit to a COVID-19 vaccine authorized before Election Day.

After this story was published, an HHS official said that Mr. Azar “will defer completely to the FDA” as the agency weighs whether to approve a vaccine produced through the government’s Operation Warp Speed effort.

“The idea the Secretary would approve or authorize a vaccine over the FDA’s objections is preposterous and betrays ignorance of the transparent process that we’re following for the development of the OWS vaccines,” HHS chief of staff Brian Harrison wrote in an email.

White House spokesperson Judd Deere dismissed the scientists’ concerns, saying Trump cared only about the public’s safety and health. “This false narrative that the media and Democrats have created that politics is influencing approvals is not only false but is a danger to the American public,” he said.

Usually, the FDA approves vaccines only after companies submit years of data proving that a vaccine is safe and effective. But a 2004 law allows the FDA to issue an emergency use authorization with much less evidence, as long as the vaccine “may be effective” and its “known and potential benefits” outweigh its “known and potential risks.”

Many scientists doubt a vaccine could meet those criteria before the election. But the terms might be legally vague enough to allow the administration to take such steps.

Moncef Slaoui, chief scientific adviser to Operation Warp Speed, the government program aiming to more quickly develop COVID-19 vaccines, said it’s “extremely unlikely” that vaccine trial results will be ready before the end of October.

Mr. Trump, however, has insisted repeatedly that a vaccine to fight the pandemic that has claimed 200,000 American lives will be distributed starting next month. He reiterated that claim Saturday at a campaign rally in Fayetteville, N.C.

The vaccine will be ready “in a matter of weeks,” he said. “We will end the pandemic from China.”

Although pharmaceutical companies have launched three clinical trials in the United States, no one can say with certainty when those trials will have enough data to determine whether the vaccines are safe and effective.

Officials at Moderna, whose vaccine is being tested in 30,000 volunteers, have said their studies could produce a result by the end of the year, although the final analysis could take place next spring.

Pfizer executives, who have expanded their clinical trial to 44,000 participants, boast that they could know their vaccine works by the end of October.

AstraZeneca’s U.S. vaccine trial, which was scheduled to enroll 30,000 volunteers, is on hold pending an investigation of a possible vaccine-related illness.

Scientists have warned for months that the Trump administration could try to win the election with an “October surprise,” authorizing a vaccine that hasn’t been fully tested. “I don’t think people are crazy to be thinking about all of this,” said William Schultz, a partner in a Washington, D.C., law firm who served as a former FDA commissioner for policy and as general counsel for HHS.

“You’ve got a president saying you’ll have an approval in October. Everybody’s wondering how that could happen.”

In an opinion piece published in the Wall Street Journal, conservative former FDA commissioners Scott Gottlieb and Mark McClellan argued that presidential intrusion was unlikely because the FDA’s “thorough and transparent process doesn’t lend itself to meddling. Any deviation would quickly be apparent.”

But the administration has demonstrated a willingness to bend the agency to its will. The FDA has been criticized for issuing emergency authorizations for two COVID-19 treatments that were boosted by the president but lacked strong evidence to support them: hydroxychloroquine and convalescent plasma.

Mr. Azar has sidelined the FDA in other ways, such as by blocking the agency from regulating lab-developed tests, including tests for the novel coronavirus.

Although FDA Commissioner Stephen Hahn told the Financial Times he would be willing to approve emergency use of a vaccine before large-scale studies conclude, agency officials also have pledged to ensure the safety of any COVID-19 vaccines.

A senior FDA official who oversees vaccine approvals, Peter Marks, MD, has said he will quit if his agency rubber-stamps an unproven COVID-19 vaccine.

“I think there would be an outcry from the public health community second to none, which is my worst nightmare – my worst nightmare – because we will so confuse the public,” said Michael Osterholm, PhD, director of the Center for Infectious Disease Research and Policy at the University of Minnesota, in his weekly podcast.

Still, “even if a company did not want it to be done, even if the FDA did not want it to be done, he could still do that,” said Dr. Osterholm, in his podcast. “I hope that we’d never see that happen, but we have to entertain that’s a possibility.”

In the New England Journal editorial, Dr. Avorn and coauthor Aaron Kesselheim, MD, wondered whether Mr. Trump might invoke the 1950 Defense Production Act to force reluctant drug companies to manufacture their vaccines.

But Mr. Trump would have to sue a company to enforce the Defense Production Act, and the company would have a strong case in refusing, said Lawrence Gostin, director of Georgetown’s O’Neill Institute for National and Global Health Law.

Also, he noted that Mr. Trump could not invoke the Defense Production Act unless a vaccine were “scientifically justified and approved by the FDA.”

Kaiser Health News is a nonprofit news service covering health issues. It is an editorially independent program of KFF (Kaiser Family Foundation), which is not affiliated with Kaiser Permanente.

From the University of Mississippi Medical Center, Department of Neurology, Division of Neuroscience Intensive Care, Jackson, MS.

Abstract

Objective: To test a coronavirus disease 2019 (COVID-19) screening tool to identify patients who qualify for testing among patients with neurologic dysfunction who are unable to answer the usual screening questions, which could help to prevent unprotected exposure of patients and health care workers to COVID-19.

Methods: The Neuro-COVID-19 Time-out Process and Checklist (NCOT-PC) was implemented at our institution for 1 week as a quality improvement project to improve the pathway for COVID-19 screening and testing among patients with neurologic dysfunction.

Results: A total of 14 new patients were admitted into the neuroscience intensive care unit (NSICU) service during the pilot period. The NCOT-PC was utilized on 9 (64%) patients with neurologic dysfunction; 7 of these patients were found to have a likelihood of requiring testing based on the NCOT-PC and were subsequently screened for COVID-19 testing by contacting the institution’s COVID-19 testing hotline (Med-Com). All these patients were subsequently transitioned into person-under-investigation status based on the determination from Med-Com. The NSICU staff involved were able to utilize NCOT-PC without issues. The NCOT-PC was immediately adopted into the NSICU process.

Conclusion: Use of the NCOT-PC tool was found to be feasible and improved the screening methodology of patients with neurologic dysfunction.

Keywords: coronavirus; health care planning; quality improvement; patient safety; medical decision-making; neuroscience intensive care unit. 

The coronavirus disease 2019 (COVID-19) pandemic has altered various standard emergent care pathways. Current recommendations regarding COVID-19 screening for testing involve asking patients about their symptoms, including fever, cough, chest pain, and dyspnea.¹ This standard screening method poses a problem when caring for patients with neurologic dysfunction. COVID-19 patients may pre-sent with conditions that affect their ability to answer questions, such as stroke, encephalitis, neuromuscular disorders, or headache, and that may preclude the use of standard screening for testing.² Patients with acute neurologic dysfunction who cannot undergo standard screening may leave the emergency department (ED) and transition into the neuroscience intensive care unit (NSICU) or any intensive care unit (ICU) without a reliable COVID-19 screening test.

The Protected Code Stroke pathway offers protection in the emergent setting for patients with stroke when their COVID-19 status is unknown.³ A similar process has been applied at our institution for emergent management of patients with cerebrovascular disease (stroke, intracerebral hemorrhage, and subarachnoid hemorrhage). However, the process from the ED after designating “difficult to screen” patients as persons under investigation (PUI) is unclear. The Centers for Disease Control and Prevention (CDC) has delineated the priorities for testing, with not all declared PUIs requiring testing.⁴ This poses a great challenge, because patients designated as PUIs require the same management as a COVID-19-positive patient, with negative-pressure isolation rooms as well as use of protective personal equipment (PPE), which may not be readily available. It was also recognized that, because the ED staff can be overwhelmed by COVID-19 patients, there may not be enough time to perform detailed screening of patients with neurologic dysfunction and that “reverse masking” may not be done consistently for nonintubated patients. This may place patients and health care workers at risk of unprotected exposure.

Recognizing these challenges, we created a Neuro-COVID-19 Time-out Process and Checklist (NCOT-PC) as a quality improvement project. The aim of this project was to improve and standardize the current process of identifying patients with neurologic dysfunction who require COVID-19 testing to decrease the risk of unprotected exposure of patients and health care workers.

Methods

Patients and Definitions

This quality improvement project was undertaken at the University of Mississippi Medical Center NSICU. Because this was a quality improvement project, an Institutional Review Board exemption was granted.

The NCOT-PC was utilized in consecutive patients with neurologic dysfunction admitted to the NSICU during a period of 1 week. “Neurologic dysfunction” encompasses any neurologic illness affecting the mental status and/or level of alertness, subsequently precluding the ability to reliably screen the patient utilizing standard COVID-19 screening. “Med-Com” at our institution is the equivalent of the national COVID-19 testing hotline, where our institution’s infectious diseases experts screen calls for testing and determine whether testing is warranted. “Unprotected exposure” means exposure to COVID-19 without adequate and appropriate PPE.

Quality Improvement Process

As more PUIs were being admitted to the institution, we used the Plan-Do-Study-Act method for process improvements in the NSICU.⁵ NSICU stakeholders, including attendings, the nurse manager, and nurse practitioners (NPs), developed an algorithm to facilitate the coordination of the NSICU staff in screening patients to identify those with a high likelihood of needing COVID-19 testing upon arrival in the NSICU (Figure 1). Once the NCOT-PC was finalized, NSICU stakeholders were educated regarding the use of this screening tool.

The checklist clinicians review when screening patients is shown in Figure 2. The risk factors comprising the checklist include patient history and clinical and radiographic characteristics that have been shown to be relevant for identifying patients with COVID-19.^6,7 The imaging criteria utilize imaging that is part of the standard of care for NSICU patients. For example, computed tomography angiogram of the head and neck performed as part of the acute stroke protocol captures the upper part of the chest. These images are utilized for their incidental findings, such as apical ground-glass opacities and tree-in-bud formation. The risk factors applicable to the patient determine whether the clinician will call Med-Com for testing approval. Institutional COVID-19 processes were then followed accordingly.⁸ The decision from Med-Com was considered final, and no deviation from institutional policies was allowed.

NCOT-PC was utilized for consecutive days for 1 week before re-evaluation of its feasibility and adaptability.

Data Collection and Analysis

Consecutive patients with neurologic dysfunction admitted into the NSICU were assigned nonlinkable patient numbers. No identifiers were collected for the purpose of this project. The primary diagnosis for admission, the neurologic dysfunction that precluded standard screening, and checklist components that the patient fulfilled were collected.

To assess the tool’s feasibility, feedback regarding the ease of use of the NCOT-PC was gathered from the nurses, NPs, charge nurses, fellows, and other attendings. To assess the utility of the NCOT-PC in identifying patients who will be approved for COVID-19 testing, we calculated the proportion of patients who were deemed to have a high likelihood of testing and the proportion of patients who were approved for testing. Descriptive statistics were used, as applicable for the project, to summarize the utility of the NCOT-PC.

Results

We found that the NCOT-PC can be easily used by clinicians. The NSICU staff did not communicate any implementation issues, and since the NCOT-PC was implemented, no problems have been identified.

During the pilot period of the NCOT-PC, 14 new patients were admitted to the NSICU service. Nine (64%) of these had neurologic dysfunction, and the NCOT-PC was used to determine whether Med-Com should be called based on the patients’ likelihood (high vs low) of needing a COVID-19 test. Of those patients with neurologic dysfunction, 7 (78%) were deemed to have a high likelihood of needing a COVID-19 test based on the NCOT-PC. Med-Com was contacted regarding these patients, and all were deemed to require the COVID-19 test by Med-Com and were transitioned into PUI status per institutional policy (Table).

Discussion

The NCOT-PC project improved and standardized the process of identifying and screening patients with neurologic dysfunction for COVID-19 testing. The screening tool is feasible to use, and it decreased inadvertent unprotected exposure of patients and health care workers.

The NCOT-PC was easy to administer. Educating the staff regarding the new process took only a few minutes and involved a meeting with the nurse manager, NPs, fellows, residents, and attendings. We found that this process works well in tandem with the standard institutional processes in place in terms of Protected Code Stroke pathway, PUI isolation, PPE use, and Med-Com screening for COVID-19 testing. Med-Com was called only if the patient fulfilled the checklist criteria. In addition, no extra cost was attributed to implementing the NCOT-PC, since we utilized imaging that was already done as part of the standard of care for patients with neurologic dysfunction.

The standardization of the process of screening for COVID-19 testing among patients with neurologic dysfunction improved patient selection. Before the NCOT-PC, there was no consistency in terms of who should get tested and the reason for testing patients with neurologic dysfunction. Patients can pass through the ED and arrive in the NSICU with an unclear screening status, which may cause inadvertent patient and health care worker exposure to COVID-19. With the NCOT-PC, we have avoided instances of inadvertent staff or patient exposure in the NSICU.

The NCOT-PC was adopted into the NSICU process after the first week it was piloted. Beyond the NSICU, the application of the NCOT-PC can be extended to any patient presentation that precludes standard screening, such as ED and interhospital transfers for stroke codes, trauma codes, code blue, or myocardial infarction codes. In our department, as we started the process of PCS for stroke codes, we included NCOT-PC for stroke patients with neurologic dysfunction.

The results of our initiative are largely limited by the decision-making process of Med-Com when patients are called in for testing. At the time of our project, there were no specific criteria used for patients with altered mental status, except for the standard screening methods, and it was through clinician-to-clinician discussion that testing decisions were made. Another limitation is the short period of time that the NCOT-PC was applied before adoption.

In summary, the NCOT-PC tool improved the screening process for COVID-19 testing in patients with neurologic dysfunction admitted to the NSICU. It was feasible and prevented unprotected staff and patient exposure to COVID-19. The NCOT-PC functionality was compatible with institutional COVID-19 policies in place, which contributed to its overall sustainability.

The Standards for Quality Improvement Reporting Excellence (SQUIRE 2.0) were utilized in preparing this manuscript.⁹

Acknowledgment: The authors thank the University of Mississippi Medical Center NSICU staff for their input with implementation of the NCOT-PC. 

Corresponding author: Prashant A. Natteru, MD, University of Mississippi Medical Center, Department of Neurology, 2500 North State St., Jackson, MS 39216; [email protected]. 

Financial disclosures: None.

From the University of Mississippi Medical Center, Department of Neurology, Division of Neuroscience Intensive Care, Jackson, MS.

Abstract

Objective: To test a coronavirus disease 2019 (COVID-19) screening tool to identify patients who qualify for testing among patients with neurologic dysfunction who are unable to answer the usual screening questions, which could help to prevent unprotected exposure of patients and health care workers to COVID-19.

Methods: The Neuro-COVID-19 Time-out Process and Checklist (NCOT-PC) was implemented at our institution for 1 week as a quality improvement project to improve the pathway for COVID-19 screening and testing among patients with neurologic dysfunction.

Results: A total of 14 new patients were admitted into the neuroscience intensive care unit (NSICU) service during the pilot period. The NCOT-PC was utilized on 9 (64%) patients with neurologic dysfunction; 7 of these patients were found to have a likelihood of requiring testing based on the NCOT-PC and were subsequently screened for COVID-19 testing by contacting the institution’s COVID-19 testing hotline (Med-Com). All these patients were subsequently transitioned into person-under-investigation status based on the determination from Med-Com. The NSICU staff involved were able to utilize NCOT-PC without issues. The NCOT-PC was immediately adopted into the NSICU process.

Conclusion: Use of the NCOT-PC tool was found to be feasible and improved the screening methodology of patients with neurologic dysfunction.

Keywords: coronavirus; health care planning; quality improvement; patient safety; medical decision-making; neuroscience intensive care unit. 

The coronavirus disease 2019 (COVID-19) pandemic has altered various standard emergent care pathways. Current recommendations regarding COVID-19 screening for testing involve asking patients about their symptoms, including fever, cough, chest pain, and dyspnea.¹ This standard screening method poses a problem when caring for patients with neurologic dysfunction. COVID-19 patients may pre-sent with conditions that affect their ability to answer questions, such as stroke, encephalitis, neuromuscular disorders, or headache, and that may preclude the use of standard screening for testing.² Patients with acute neurologic dysfunction who cannot undergo standard screening may leave the emergency department (ED) and transition into the neuroscience intensive care unit (NSICU) or any intensive care unit (ICU) without a reliable COVID-19 screening test.

The Protected Code Stroke pathway offers protection in the emergent setting for patients with stroke when their COVID-19 status is unknown.³ A similar process has been applied at our institution for emergent management of patients with cerebrovascular disease (stroke, intracerebral hemorrhage, and subarachnoid hemorrhage). However, the process from the ED after designating “difficult to screen” patients as persons under investigation (PUI) is unclear. The Centers for Disease Control and Prevention (CDC) has delineated the priorities for testing, with not all declared PUIs requiring testing.⁴ This poses a great challenge, because patients designated as PUIs require the same management as a COVID-19-positive patient, with negative-pressure isolation rooms as well as use of protective personal equipment (PPE), which may not be readily available. It was also recognized that, because the ED staff can be overwhelmed by COVID-19 patients, there may not be enough time to perform detailed screening of patients with neurologic dysfunction and that “reverse masking” may not be done consistently for nonintubated patients. This may place patients and health care workers at risk of unprotected exposure.

Recognizing these challenges, we created a Neuro-COVID-19 Time-out Process and Checklist (NCOT-PC) as a quality improvement project. The aim of this project was to improve and standardize the current process of identifying patients with neurologic dysfunction who require COVID-19 testing to decrease the risk of unprotected exposure of patients and health care workers.

Methods

Patients and Definitions

This quality improvement project was undertaken at the University of Mississippi Medical Center NSICU. Because this was a quality improvement project, an Institutional Review Board exemption was granted.

The NCOT-PC was utilized in consecutive patients with neurologic dysfunction admitted to the NSICU during a period of 1 week. “Neurologic dysfunction” encompasses any neurologic illness affecting the mental status and/or level of alertness, subsequently precluding the ability to reliably screen the patient utilizing standard COVID-19 screening. “Med-Com” at our institution is the equivalent of the national COVID-19 testing hotline, where our institution’s infectious diseases experts screen calls for testing and determine whether testing is warranted. “Unprotected exposure” means exposure to COVID-19 without adequate and appropriate PPE.

Quality Improvement Process

As more PUIs were being admitted to the institution, we used the Plan-Do-Study-Act method for process improvements in the NSICU.⁵ NSICU stakeholders, including attendings, the nurse manager, and nurse practitioners (NPs), developed an algorithm to facilitate the coordination of the NSICU staff in screening patients to identify those with a high likelihood of needing COVID-19 testing upon arrival in the NSICU (Figure 1). Once the NCOT-PC was finalized, NSICU stakeholders were educated regarding the use of this screening tool.

The checklist clinicians review when screening patients is shown in Figure 2. The risk factors comprising the checklist include patient history and clinical and radiographic characteristics that have been shown to be relevant for identifying patients with COVID-19.^6,7 The imaging criteria utilize imaging that is part of the standard of care for NSICU patients. For example, computed tomography angiogram of the head and neck performed as part of the acute stroke protocol captures the upper part of the chest. These images are utilized for their incidental findings, such as apical ground-glass opacities and tree-in-bud formation. The risk factors applicable to the patient determine whether the clinician will call Med-Com for testing approval. Institutional COVID-19 processes were then followed accordingly.⁸ The decision from Med-Com was considered final, and no deviation from institutional policies was allowed.

NCOT-PC was utilized for consecutive days for 1 week before re-evaluation of its feasibility and adaptability.

Data Collection and Analysis

Consecutive patients with neurologic dysfunction admitted into the NSICU were assigned nonlinkable patient numbers. No identifiers were collected for the purpose of this project. The primary diagnosis for admission, the neurologic dysfunction that precluded standard screening, and checklist components that the patient fulfilled were collected.

To assess the tool’s feasibility, feedback regarding the ease of use of the NCOT-PC was gathered from the nurses, NPs, charge nurses, fellows, and other attendings. To assess the utility of the NCOT-PC in identifying patients who will be approved for COVID-19 testing, we calculated the proportion of patients who were deemed to have a high likelihood of testing and the proportion of patients who were approved for testing. Descriptive statistics were used, as applicable for the project, to summarize the utility of the NCOT-PC.

Results

We found that the NCOT-PC can be easily used by clinicians. The NSICU staff did not communicate any implementation issues, and since the NCOT-PC was implemented, no problems have been identified.

During the pilot period of the NCOT-PC, 14 new patients were admitted to the NSICU service. Nine (64%) of these had neurologic dysfunction, and the NCOT-PC was used to determine whether Med-Com should be called based on the patients’ likelihood (high vs low) of needing a COVID-19 test. Of those patients with neurologic dysfunction, 7 (78%) were deemed to have a high likelihood of needing a COVID-19 test based on the NCOT-PC. Med-Com was contacted regarding these patients, and all were deemed to require the COVID-19 test by Med-Com and were transitioned into PUI status per institutional policy (Table).

Discussion

The NCOT-PC project improved and standardized the process of identifying and screening patients with neurologic dysfunction for COVID-19 testing. The screening tool is feasible to use, and it decreased inadvertent unprotected exposure of patients and health care workers.

The NCOT-PC was easy to administer. Educating the staff regarding the new process took only a few minutes and involved a meeting with the nurse manager, NPs, fellows, residents, and attendings. We found that this process works well in tandem with the standard institutional processes in place in terms of Protected Code Stroke pathway, PUI isolation, PPE use, and Med-Com screening for COVID-19 testing. Med-Com was called only if the patient fulfilled the checklist criteria. In addition, no extra cost was attributed to implementing the NCOT-PC, since we utilized imaging that was already done as part of the standard of care for patients with neurologic dysfunction.

The standardization of the process of screening for COVID-19 testing among patients with neurologic dysfunction improved patient selection. Before the NCOT-PC, there was no consistency in terms of who should get tested and the reason for testing patients with neurologic dysfunction. Patients can pass through the ED and arrive in the NSICU with an unclear screening status, which may cause inadvertent patient and health care worker exposure to COVID-19. With the NCOT-PC, we have avoided instances of inadvertent staff or patient exposure in the NSICU.

The NCOT-PC was adopted into the NSICU process after the first week it was piloted. Beyond the NSICU, the application of the NCOT-PC can be extended to any patient presentation that precludes standard screening, such as ED and interhospital transfers for stroke codes, trauma codes, code blue, or myocardial infarction codes. In our department, as we started the process of PCS for stroke codes, we included NCOT-PC for stroke patients with neurologic dysfunction.

The results of our initiative are largely limited by the decision-making process of Med-Com when patients are called in for testing. At the time of our project, there were no specific criteria used for patients with altered mental status, except for the standard screening methods, and it was through clinician-to-clinician discussion that testing decisions were made. Another limitation is the short period of time that the NCOT-PC was applied before adoption.

In summary, the NCOT-PC tool improved the screening process for COVID-19 testing in patients with neurologic dysfunction admitted to the NSICU. It was feasible and prevented unprotected staff and patient exposure to COVID-19. The NCOT-PC functionality was compatible with institutional COVID-19 policies in place, which contributed to its overall sustainability.

The Standards for Quality Improvement Reporting Excellence (SQUIRE 2.0) were utilized in preparing this manuscript.⁹

Acknowledgment: The authors thank the University of Mississippi Medical Center NSICU staff for their input with implementation of the NCOT-PC. 

Corresponding author: Prashant A. Natteru, MD, University of Mississippi Medical Center, Department of Neurology, 2500 North State St., Jackson, MS 39216; [email protected]. 

Financial disclosures: None.

From the University of Mississippi Medical Center, Department of Neurology, Division of Neuroscience Intensive Care, Jackson, MS.

Abstract

Objective: To test a coronavirus disease 2019 (COVID-19) screening tool to identify patients who qualify for testing among patients with neurologic dysfunction who are unable to answer the usual screening questions, which could help to prevent unprotected exposure of patients and health care workers to COVID-19.

Methods: The Neuro-COVID-19 Time-out Process and Checklist (NCOT-PC) was implemented at our institution for 1 week as a quality improvement project to improve the pathway for COVID-19 screening and testing among patients with neurologic dysfunction.

Results: A total of 14 new patients were admitted into the neuroscience intensive care unit (NSICU) service during the pilot period. The NCOT-PC was utilized on 9 (64%) patients with neurologic dysfunction; 7 of these patients were found to have a likelihood of requiring testing based on the NCOT-PC and were subsequently screened for COVID-19 testing by contacting the institution’s COVID-19 testing hotline (Med-Com). All these patients were subsequently transitioned into person-under-investigation status based on the determination from Med-Com. The NSICU staff involved were able to utilize NCOT-PC without issues. The NCOT-PC was immediately adopted into the NSICU process.

Conclusion: Use of the NCOT-PC tool was found to be feasible and improved the screening methodology of patients with neurologic dysfunction.

Keywords: coronavirus; health care planning; quality improvement; patient safety; medical decision-making; neuroscience intensive care unit. 

The coronavirus disease 2019 (COVID-19) pandemic has altered various standard emergent care pathways. Current recommendations regarding COVID-19 screening for testing involve asking patients about their symptoms, including fever, cough, chest pain, and dyspnea.¹ This standard screening method poses a problem when caring for patients with neurologic dysfunction. COVID-19 patients may pre-sent with conditions that affect their ability to answer questions, such as stroke, encephalitis, neuromuscular disorders, or headache, and that may preclude the use of standard screening for testing.² Patients with acute neurologic dysfunction who cannot undergo standard screening may leave the emergency department (ED) and transition into the neuroscience intensive care unit (NSICU) or any intensive care unit (ICU) without a reliable COVID-19 screening test.

The Protected Code Stroke pathway offers protection in the emergent setting for patients with stroke when their COVID-19 status is unknown.³ A similar process has been applied at our institution for emergent management of patients with cerebrovascular disease (stroke, intracerebral hemorrhage, and subarachnoid hemorrhage). However, the process from the ED after designating “difficult to screen” patients as persons under investigation (PUI) is unclear. The Centers for Disease Control and Prevention (CDC) has delineated the priorities for testing, with not all declared PUIs requiring testing.⁴ This poses a great challenge, because patients designated as PUIs require the same management as a COVID-19-positive patient, with negative-pressure isolation rooms as well as use of protective personal equipment (PPE), which may not be readily available. It was also recognized that, because the ED staff can be overwhelmed by COVID-19 patients, there may not be enough time to perform detailed screening of patients with neurologic dysfunction and that “reverse masking” may not be done consistently for nonintubated patients. This may place patients and health care workers at risk of unprotected exposure.

Recognizing these challenges, we created a Neuro-COVID-19 Time-out Process and Checklist (NCOT-PC) as a quality improvement project. The aim of this project was to improve and standardize the current process of identifying patients with neurologic dysfunction who require COVID-19 testing to decrease the risk of unprotected exposure of patients and health care workers.

Methods

Patients and Definitions

This quality improvement project was undertaken at the University of Mississippi Medical Center NSICU. Because this was a quality improvement project, an Institutional Review Board exemption was granted.

The NCOT-PC was utilized in consecutive patients with neurologic dysfunction admitted to the NSICU during a period of 1 week. “Neurologic dysfunction” encompasses any neurologic illness affecting the mental status and/or level of alertness, subsequently precluding the ability to reliably screen the patient utilizing standard COVID-19 screening. “Med-Com” at our institution is the equivalent of the national COVID-19 testing hotline, where our institution’s infectious diseases experts screen calls for testing and determine whether testing is warranted. “Unprotected exposure” means exposure to COVID-19 without adequate and appropriate PPE.

Quality Improvement Process

As more PUIs were being admitted to the institution, we used the Plan-Do-Study-Act method for process improvements in the NSICU.⁵ NSICU stakeholders, including attendings, the nurse manager, and nurse practitioners (NPs), developed an algorithm to facilitate the coordination of the NSICU staff in screening patients to identify those with a high likelihood of needing COVID-19 testing upon arrival in the NSICU (Figure 1). Once the NCOT-PC was finalized, NSICU stakeholders were educated regarding the use of this screening tool.

The checklist clinicians review when screening patients is shown in Figure 2. The risk factors comprising the checklist include patient history and clinical and radiographic characteristics that have been shown to be relevant for identifying patients with COVID-19.^6,7 The imaging criteria utilize imaging that is part of the standard of care for NSICU patients. For example, computed tomography angiogram of the head and neck performed as part of the acute stroke protocol captures the upper part of the chest. These images are utilized for their incidental findings, such as apical ground-glass opacities and tree-in-bud formation. The risk factors applicable to the patient determine whether the clinician will call Med-Com for testing approval. Institutional COVID-19 processes were then followed accordingly.⁸ The decision from Med-Com was considered final, and no deviation from institutional policies was allowed.

NCOT-PC was utilized for consecutive days for 1 week before re-evaluation of its feasibility and adaptability.

Data Collection and Analysis

Consecutive patients with neurologic dysfunction admitted into the NSICU were assigned nonlinkable patient numbers. No identifiers were collected for the purpose of this project. The primary diagnosis for admission, the neurologic dysfunction that precluded standard screening, and checklist components that the patient fulfilled were collected.

To assess the tool’s feasibility, feedback regarding the ease of use of the NCOT-PC was gathered from the nurses, NPs, charge nurses, fellows, and other attendings. To assess the utility of the NCOT-PC in identifying patients who will be approved for COVID-19 testing, we calculated the proportion of patients who were deemed to have a high likelihood of testing and the proportion of patients who were approved for testing. Descriptive statistics were used, as applicable for the project, to summarize the utility of the NCOT-PC.

Results

We found that the NCOT-PC can be easily used by clinicians. The NSICU staff did not communicate any implementation issues, and since the NCOT-PC was implemented, no problems have been identified.

During the pilot period of the NCOT-PC, 14 new patients were admitted to the NSICU service. Nine (64%) of these had neurologic dysfunction, and the NCOT-PC was used to determine whether Med-Com should be called based on the patients’ likelihood (high vs low) of needing a COVID-19 test. Of those patients with neurologic dysfunction, 7 (78%) were deemed to have a high likelihood of needing a COVID-19 test based on the NCOT-PC. Med-Com was contacted regarding these patients, and all were deemed to require the COVID-19 test by Med-Com and were transitioned into PUI status per institutional policy (Table).

Discussion

The NCOT-PC project improved and standardized the process of identifying and screening patients with neurologic dysfunction for COVID-19 testing. The screening tool is feasible to use, and it decreased inadvertent unprotected exposure of patients and health care workers.

The NCOT-PC was easy to administer. Educating the staff regarding the new process took only a few minutes and involved a meeting with the nurse manager, NPs, fellows, residents, and attendings. We found that this process works well in tandem with the standard institutional processes in place in terms of Protected Code Stroke pathway, PUI isolation, PPE use, and Med-Com screening for COVID-19 testing. Med-Com was called only if the patient fulfilled the checklist criteria. In addition, no extra cost was attributed to implementing the NCOT-PC, since we utilized imaging that was already done as part of the standard of care for patients with neurologic dysfunction.

The standardization of the process of screening for COVID-19 testing among patients with neurologic dysfunction improved patient selection. Before the NCOT-PC, there was no consistency in terms of who should get tested and the reason for testing patients with neurologic dysfunction. Patients can pass through the ED and arrive in the NSICU with an unclear screening status, which may cause inadvertent patient and health care worker exposure to COVID-19. With the NCOT-PC, we have avoided instances of inadvertent staff or patient exposure in the NSICU.

The NCOT-PC was adopted into the NSICU process after the first week it was piloted. Beyond the NSICU, the application of the NCOT-PC can be extended to any patient presentation that precludes standard screening, such as ED and interhospital transfers for stroke codes, trauma codes, code blue, or myocardial infarction codes. In our department, as we started the process of PCS for stroke codes, we included NCOT-PC for stroke patients with neurologic dysfunction.

The results of our initiative are largely limited by the decision-making process of Med-Com when patients are called in for testing. At the time of our project, there were no specific criteria used for patients with altered mental status, except for the standard screening methods, and it was through clinician-to-clinician discussion that testing decisions were made. Another limitation is the short period of time that the NCOT-PC was applied before adoption.

In summary, the NCOT-PC tool improved the screening process for COVID-19 testing in patients with neurologic dysfunction admitted to the NSICU. It was feasible and prevented unprotected staff and patient exposure to COVID-19. The NCOT-PC functionality was compatible with institutional COVID-19 policies in place, which contributed to its overall sustainability.

The Standards for Quality Improvement Reporting Excellence (SQUIRE 2.0) were utilized in preparing this manuscript.⁹

Acknowledgment: The authors thank the University of Mississippi Medical Center NSICU staff for their input with implementation of the NCOT-PC. 

Corresponding author: Prashant A. Natteru, MD, University of Mississippi Medical Center, Department of Neurology, 2500 North State St., Jackson, MS 39216; [email protected]. 

Financial disclosures: None.

From the Hospital of Central Connecticut, New Britain, CT (Dr. Caulfield and Dr. Shepard); Hartford Hospital, Hartford, CT (Dr. Linder and Dr. Dempsey); and the Hartford HealthCare Research Program, Hartford, CT (Dr. O’Sullivan).

Abstract

• Objective: To assess the utility of methicillin-resistant Staphylococcus aureus (MRSA) polymerase chain reaction (PCR) nasal swab testing in patients with lower respiratory tract infections (LRTI).
• Design and setting: Multicenter, retrospective, electronic chart review conducted within the Hartford HealthCare system.
• Participants: Patients who were treated for LRTIs at the Hospital of Central Connecticut or Hartford Hospital between July 1, 2018, and June 30, 2019.
• Measurements: The primary outcome was anti-MRSA days of therapy (DOT) in patients who underwent MRSA PCR testing versus those who did not. In a subgroup analysis, we compared anti-MRSA DOT among patients with appropriate versus inappropriate utilization of the MRSA PCR test.
• Results: Of the 319 patients treated for LRTIs, 155 (48.6%) had a MRSA PCR ordered, and appropriate utilization occurred in 94 (60.6%) of these patients. Anti-MRSA DOT in the MRSA PCR group (n = 155) was shorter than in the group that did not undergo MRSA PCR testing (n = 164), but this difference did not reach statistical significance (1.68 days [interquartile range {IQR}, 0.80-2.74] vs 1.86 days [IQR, 0.56-3.33], P = 0.458). In the subgroup analysis, anti-MRSA DOT was significantly shorter in the MRSA PCR group with appropriate utilization compared to the inappropriate utilization group (1.16 [IQR, 0.44-1.88] vs 2.68 [IQR, 1.75-3.76], P < 0.001)
• Conclusion: Appropriate utilization of MRSA PCR nasal swab testing can reduce DOT in patients with LRTI. Further education is necessary to expand the appropriate use of the MRSA PCR test across our health system.

Keywords: MRSA; LRTI; pneumonia; antimicrobial stewardship; antibiotic resistance.

More than 300,000 patients were hospitalized with methicillin-resistant Staphylococcus aureus (MRSA) infections in the United States in 2017, and at least 10,000 of these cases resulted in mortality.¹ While MRSA infections overall are decreasing, it is crucial to continue to employ antimicrobial stewardship tactics to keep these infections at bay. Recently, strains of S. aureus have become resistant to vancomycin, making this bacterium even more difficult to treat.²

A novel tactic in antimicrobial stewardship involves the use of MRSA polymerase chain reaction (PCR) nasal swab testing to rule out the presence of MRSA in patients with lower respiratory tract infections (LRTI). If used appropriately, this approach may decrease the number of days patients are treated with anti-MRSA antimicrobials. Waiting for cultures to speciate can take up to 72 hours,³ meaning that patients may be exposed to 3 days of unnecessary broad-spectrum antibiotics. Results of MRSA PCR assay of nasal swab specimens can be available in 1 to 2 hours,⁴ allowing for more rapid de-escalation of therapy. Numerous studies have shown that this test has a negative predictive value (NPV) greater than 95%, indicating that a negative nasal swab result may be useful to guide de-escalation of antibiotic therapy.^5-8 The purpose of this study was to assess the utility of MRSA PCR nasal swab testing in patients with LRTI throughout the Hartford HealthCare system.

Methods

Design

This study was a multicenter, retrospective, electronic chart review. It was approved by the Hartford HealthCare Institutional Review Board (HHC-2019-0169).

Selection of Participants

Patients were identified through electronic medical record reports based on ICD-10 codes. Records were categorized into 2 groups: patients who received a MRSA PCR nasal swab testing and patients who did not. Patients who received the MRSA PCR were further categorized by appropriate or inappropriate utilization. Appropriate utilization of the MRSA PCR was defined as MRSA PCR ordered within 48 hours of a new vancomycin or linezolid order, and anti-MRSA therapy discontinued within 24 hours of a negative result. Inappropriate utilization of the MRSA PCR was defined as MRSA PCR ordered more than 48 hours after a new vancomycin or linezolid order, or continuation of anti-MRSA therapy despite a negative MRSA PCR and no other evidence of a MRSA infection.

Patients were included if they met all of the following criteria: age 18 years or older, with no upper age limit; treated for a LRTI, identified by ICD-10 codes (J13-22, J44, J85); treated with empiric antibiotics active against MRSA, specifically vancomycin or linezolid; and treated at the Hospital of Central Connecticut (HOCC) or Hartford Hospital (HH) between July 1, 2018, and June 30, 2019, inclusive. Patients were excluded if they met 1 or more of the following criteria: age less than 18 years old; admitted for 48 hours or fewer or discharged from the emergency department; not treated at either facility; treated before July 1, 2018, or after June 30, 2019; treated for ventilator-associated pneumonia; received anti-MRSA therapy within 30 days prior to admission; or treated for a concurrent bacterial infection requiring anti-MRSA therapy.

Outcome Measures

The primary outcome was anti-MRSA days of therapy (DOT) in patients who underwent MRSA PCR testing compared to patients who did not undergo MRSA PCR testing. A subgroup analysis was completed to compare anti-MRSA DOT within patients in the MRSA PCR group. Patients in the subgroup were categorized by appropriate or inappropriate utilization, and anti-MRSA DOT were compared between these groups. Secondary outcomes that were evaluated included length of stay (LOS), 30-day readmission rate, and incidence of acute kidney injury (AKI). Thirty-day readmission was defined as admission to HOCC, HH, or any institution within Hartford HealthCare within 30 days of discharge. AKI was defined as an increase in serum creatinine by ≥ 0.3 mg/dL in 48 hours, increase ≥ 1.5 times baseline, or a urine volume < 0.5 mL/kg/hr for 6 hours.

Statistical Analyses

The study was powered for the primary outcome, anti-MRSA DOT, with a clinically meaningful difference of 1 day. Group sample sizes of 240 in the MRSA PCR group and 160 in the no MRSA PCR group would have afforded 92% power to detect that difference, if the null hypothesis was that both group means were 4 days and the alternative hypothesis was that the mean of the MRSA PCR group was 3 days, with estimated group standard deviations of 80% of each mean. This estimate used an alpha level of 0.05 with a 2-sided t-test. Among those who received a MRSA PCR test, a clinically meaningful difference between appropriate and inappropriate utilization was 5%.

Descriptive statistics were provided for all variables as a function of the individual hospital and for the combined data set. Continuous data were summarized with means and standard deviations (SD), or with median and interquartile ranges (IQR), depending on distribution. Categorical variables were reported as frequencies, using percentages. All data were evaluated for normality of distribution. Inferential statistics comprised a Student’s t-test to compare normally distributed, continuous data between groups. Nonparametric distributions were compared using a Mann-Whitney U test. Categorical comparisons were made using a Fisher’s exact test for 2×2 tables and a Pearson chi-square test for comparisons involving more than 2 groups.

Since anti-MRSA DOT (primary outcome) and LOS (secondary outcome) are often non-normally distributed, they have been transformed (eg, log or square root, again depending on distribution). Whichever native variable or transformation variable was appropriate was used as the outcome measure in a linear regression model to account for the influence of factors (covariates) that show significant univariate differences. Given the relatively small sample size, a maximum of 10 variables were included in the model. All factors were iterated in a forward regression model (most influential first) until no significant changes were observed.

All calculations were performed with SPSS v. 21 (IBM; Armonk, NY) using an a priori alpha level of 0.05, such that all results yielding P < 0.05 were deemed statistically significant.

Results

Of the 561 patient records reviewed, 319 patients were included and 242 patients were excluded. Reasons for exclusion included 65 patients admitted for a duration of 48 hours or less or discharged from the emergency department; 61 patients having another infection requiring anti-MRSA therapy; 60 patients not having a diagnosis of a LRTI or not receiving anti-MRSA therapy; 52 patients having received anti-MRSA therapy within 30 days prior to admission; and 4 patients treated outside of the specified date range.

Of the 319 patients included, 155 (48.6%) were in the MRSA PCR group and 164 (51.4%) were in the group that did not undergo MRSA PCR (Table 1). Of the 155 patients with a MRSA PCR ordered, the test was utilized appropriately in 94 (60.6%) patients and inappropriately in 61 (39.4%) patients (Table 2). In the MRSA PCR group, 135 patients had a negative result on PCR assay, with 133 of those patients having negative respiratory cultures, resulting in a NPV of 98.5%. Differences in baseline characteristics between the MRSA PCR and no MRSA PCR groups were observed. The patients in the MRSA PCR group appeared to be significantly more ill than those in the no MRSA PCR group, as indicated by statistically significant differences in intensive care unit (ICU) admissions (P = 0.001), positive chest radiographs (P = 0.034), sepsis at time of anti-MRSA initiation (P = 0.013), pulmonary consults placed (P = 0.003), and carbapenem usage (P = 0.047).

Outcomes

Median anti-MRSA DOT in the MRSA PCR group was shorter than DOT in the no MRSA PCR group, but this difference did not reach statistical significance (1.68 [IQR, 0.80-2.74] vs 1.86 days [IQR, 0.56-3.33], P = 0.458; Table 3). LOS in the MRSA PCR group was longer than in the no MRSA PCR group (6.0 [IQR, 4.0-10.0] vs 5.0 [IQR, 3.0-7.0] days, P = 0.001). There was no difference in 30-day readmissions that were related to the previous visit or incidence of AKI between groups.

In the subgroup analysis, anti-MRSA DOT in the MRSA PCR group with appropriate utilization was shorter than DOT in the MRSA PCR group with inappropriate utilization (1.16 [IQR, 0.44-1.88] vs 2.68 [IQR, 1.75-3.76] days, P < 0.001; Table 4). LOS in the MRSA PCR group with appropriate utilization was shorter than LOS in the inappropriate utilization group (5.0 [IQR, 4.0-7.0] vs 7.0 [IQR, 5.0-12.0] days, P < 0.001). Thirty-day readmissions that were related to the previous visit were significantly higher in patients in the MRSA PCR group with appropriate utilization (13 vs 2, P = 0.030). There was no difference in incidence of AKI between the groups.

A multivariate analysis was completed to determine whether the sicker MRSA PCR population was confounding outcomes, particularly the secondary outcome of LOS, which was noted to be longer in the MRSA PCR group (Table 5). When comparing LOS in the MRSA PCR and the no MRSA PCR patients, the multivariate analysis showed that admission to the ICU and carbapenem use were associated with a longer LOS (P < 0.001 and P = 0.009, respectively). The incidence of admission to the ICU and carbapenem use were higher in the MRSA PCR group (P = 0.001 and P = 0.047). Therefore, longer LOS in the MRSA PCR patients could be a result of the higher prevalence of ICU admissions and infections requiring carbapenem therapy rather than the result of the MRSA PCR itself.

Discussion

A MRSA PCR nasal swab protocol can be used to minimize a patient’s exposure to unnecessary broad-spectrum antibiotics, thereby preventing antimicrobial resistance. Thus, it is important to assess how our health system is utilizing this antimicrobial stewardship tactic. With the MRSA PCR’s high NPV, providers can be confident that MRSA pneumonia is unlikely in the absence of MRSA colonization. Our study established a NPV of 98.5%, which is similar to other studies, all of which have shown NPVs greater than 95%.^5-8 Despite the high NPV, this study demonstrated that only 51.4% of patients with LRTI had orders for a MRSA PCR. Of the 155 patients with a MRSA PCR, the test was utilized appropriately only 60.6% of the time. A majority of the inappropriately utilized tests were due to MRSA PCR orders placed more than 48 hours after anti-MRSA therapy initiation. To our knowledge, no other studies have assessed the clinical utility of MRSA PCR nasal swabs as an antimicrobial stewardship tool in a diverse health system; therefore, these results are useful to guide future practices at our institution. There is a clear need for provider and pharmacist education to increase the use of MRSA PCR nasal swab testing for patients with LRTI being treated with anti-MRSA therapy. Additionally, clinician education regarding the initial timing of the MRSA PCR order and the proper utilization of the results of the MRSA PCR likely will benefit patient outcomes at our institution.

When evaluating anti-MRSA DOT, this study demonstrated a reduction of only 0.18 days (about 4 hours) of anti-MRSA therapy in the patients who received MRSA PCR testing compared to the patients without a MRSA PCR ordered. Our anti-MRSA DOT reduction was lower than what has been reported in similar studies. For example, Baby et al found that the use of the MRSA PCR was associated with 46.6 fewer hours of unnecessary antimicrobial treatment. Willis et al evaluated a pharmacist-driven protocol that resulted in a reduction of 1.8 days of anti-MRSA therapy, despite a protocol compliance rate of only 55%.^9,10 In our study, the patients in the MRSA PCR group appeared to be significantly more ill than those in the no MRSA PCR group, which may be the reason for the incongruences in our results compared to the current literature. Characteristics such as ICU admissions, positive chest radiographs, sepsis cases, pulmonary consults, and carbapenem usage—all of which are indicative of a sicker population—were more prevalent in the MRSA PCR group. This sicker population could have underestimated the reduction of DOT in the MRSA PCR group compared to the no MRSA PCR group.

After isolating the MRSA PCR patients in the subgroup analysis, anti-MRSA DOT was 1.5 days shorter when the test was appropriately utilized, which is more comparable to what has been reported in the literature.^9,10 Only 60.6% of the MRSA PCR patients had their anti-MRSA therapy appropriately managed based on the MRSA PCR. Interestingly, a majority of patients in the inappropriate utilization group had MRSA PCR tests ordered more than 48 hours after beginning anti-MRSA therapy. More prompt and efficient ordering of the MRSA PCR may have resulted in more opportunities for earlier de-escalation of therapy. Due to these factors, the patients in the inappropriate utilization group could have further contributed to the underestimated difference in anti-MRSA DOT between the MRSA PCR and no MRSA PCR patients in the primary outcome. Additionally, there were no notable differences between the appropriate and inappropriate utilization groups, unlike in the MRSA PCR and no MRSA PCR groups, which is why we were able to draw more robust conclusions in the subgroup analysis. Therefore, the subgroup analysis confirmed that if the results of the MRSA PCR are used appropriately to guide anti-MRSA therapy, patients can potentially avoid 36 hours of broad-spectrum antibiotics.

Data on how the utilization of the MRSA PCR nasal swab can affect LOS are limited; however, one study did report a 2.8-day reduction in LOS after implementation of a pharmacist-driven MRSA PCR nasal swab protocol.¹¹ Our study demonstrated that LOS was significantly longer in the MRSA PCR group than in the no MRSA PCR group. This result was likely affected by the aforementioned sicker MRSA PCR population. Our multivariate analysis further confirmed that ICU admissions were associated with a longer LOS, and, given that the MRSA PCR group had a significantly higher ICU population, this likely confounded these results. If our 2 groups had had more evenly distributed characteristics, it is possible that we could have found a shorter LOS in the MRSA PCR group, similar to what is reported in the literature. In the subgroup analysis, LOS was 2 days shorter in the appropriate utilization group compared to the inappropriate utilization group. This further affirms that the results of the MRSA PCR must be used appropriately in order for patient outcomes, like LOS, to benefit.

The effects of the MRSA PCR nasal swab on 30-day readmission rates and incidence of AKI are not well-documented in the literature. One study did report 30-day readmission rates as an outcome, but did not cite any difference after the implementation of a protocol that utilized MRSA PCR nasal swab testing.¹² The outcome of AKI is slightly better represented in the literature, but the results are conflicting. Some studies report no difference after the implementation of a MRSA PCR-based protocol,¹¹ and others report a significant decrease in AKI with the use of the MRSA PCR.⁹ Our study detected no difference in 30-day readmission rates related to the previous admission or in AKI between the MRSA PCR and no MRSA PCR populations. In the subgroup analysis, 30-day readmission rates were significantly higher in the MRSA PCR group with appropriate utilization than in the group with inappropriate utilization; however, our study was not powered to detect a difference in this secondary outcome.

This study had some limitations that may have affected our results. First, this study was a retrospective chart review. Additionally, the baseline characteristics were not well balanced across the different groups. There were sicker patients in the MRSA PCR group, which may have led to an underestimate of the reduction in DOT and LOS in these patients. Finally, we did not include enough patient records to reach power in the MRSA PCR group due to a higher than expected number of patients meeting exclusion criteria. Had we attained sufficient power, there may have been more profound reductions in DOT and LOS.

Conclusion

MRSA infections are a common cause for hospitalization, and there is a growing need for antimicrobial stewardship efforts to limit unnecessary antibiotic usage in order to prevent resistance. As illustrated in our study, appropriate utilization of the MRSA PCR can reduce DOT up to 1.5 days. However, our results suggest that there is room for provider and pharmacist education to increase the use of MRSA PCR nasal swab testing in patients with LRTI receiving anti-MRSA therapy. Further emphasis on the appropriate utilization of the MRSA PCR within our health care system is essential.

Corresponding author: Casey Dempsey, PharmD, BCIDP, 80 Seymour St., Hartford, CT 06106; [email protected].

Financial disclosures: None.

From the Hospital of Central Connecticut, New Britain, CT (Dr. Caulfield and Dr. Shepard); Hartford Hospital, Hartford, CT (Dr. Linder and Dr. Dempsey); and the Hartford HealthCare Research Program, Hartford, CT (Dr. O’Sullivan).

Abstract

• Objective: To assess the utility of methicillin-resistant Staphylococcus aureus (MRSA) polymerase chain reaction (PCR) nasal swab testing in patients with lower respiratory tract infections (LRTI).
• Design and setting: Multicenter, retrospective, electronic chart review conducted within the Hartford HealthCare system.
• Participants: Patients who were treated for LRTIs at the Hospital of Central Connecticut or Hartford Hospital between July 1, 2018, and June 30, 2019.
• Measurements: The primary outcome was anti-MRSA days of therapy (DOT) in patients who underwent MRSA PCR testing versus those who did not. In a subgroup analysis, we compared anti-MRSA DOT among patients with appropriate versus inappropriate utilization of the MRSA PCR test.
• Results: Of the 319 patients treated for LRTIs, 155 (48.6%) had a MRSA PCR ordered, and appropriate utilization occurred in 94 (60.6%) of these patients. Anti-MRSA DOT in the MRSA PCR group (n = 155) was shorter than in the group that did not undergo MRSA PCR testing (n = 164), but this difference did not reach statistical significance (1.68 days [interquartile range {IQR}, 0.80-2.74] vs 1.86 days [IQR, 0.56-3.33], P = 0.458). In the subgroup analysis, anti-MRSA DOT was significantly shorter in the MRSA PCR group with appropriate utilization compared to the inappropriate utilization group (1.16 [IQR, 0.44-1.88] vs 2.68 [IQR, 1.75-3.76], P < 0.001)
• Conclusion: Appropriate utilization of MRSA PCR nasal swab testing can reduce DOT in patients with LRTI. Further education is necessary to expand the appropriate use of the MRSA PCR test across our health system.

Keywords: MRSA; LRTI; pneumonia; antimicrobial stewardship; antibiotic resistance.

More than 300,000 patients were hospitalized with methicillin-resistant Staphylococcus aureus (MRSA) infections in the United States in 2017, and at least 10,000 of these cases resulted in mortality.¹ While MRSA infections overall are decreasing, it is crucial to continue to employ antimicrobial stewardship tactics to keep these infections at bay. Recently, strains of S. aureus have become resistant to vancomycin, making this bacterium even more difficult to treat.²

A novel tactic in antimicrobial stewardship involves the use of MRSA polymerase chain reaction (PCR) nasal swab testing to rule out the presence of MRSA in patients with lower respiratory tract infections (LRTI). If used appropriately, this approach may decrease the number of days patients are treated with anti-MRSA antimicrobials. Waiting for cultures to speciate can take up to 72 hours,³ meaning that patients may be exposed to 3 days of unnecessary broad-spectrum antibiotics. Results of MRSA PCR assay of nasal swab specimens can be available in 1 to 2 hours,⁴ allowing for more rapid de-escalation of therapy. Numerous studies have shown that this test has a negative predictive value (NPV) greater than 95%, indicating that a negative nasal swab result may be useful to guide de-escalation of antibiotic therapy.^5-8 The purpose of this study was to assess the utility of MRSA PCR nasal swab testing in patients with LRTI throughout the Hartford HealthCare system.

Methods

Design

This study was a multicenter, retrospective, electronic chart review. It was approved by the Hartford HealthCare Institutional Review Board (HHC-2019-0169).

Selection of Participants

Patients were identified through electronic medical record reports based on ICD-10 codes. Records were categorized into 2 groups: patients who received a MRSA PCR nasal swab testing and patients who did not. Patients who received the MRSA PCR were further categorized by appropriate or inappropriate utilization. Appropriate utilization of the MRSA PCR was defined as MRSA PCR ordered within 48 hours of a new vancomycin or linezolid order, and anti-MRSA therapy discontinued within 24 hours of a negative result. Inappropriate utilization of the MRSA PCR was defined as MRSA PCR ordered more than 48 hours after a new vancomycin or linezolid order, or continuation of anti-MRSA therapy despite a negative MRSA PCR and no other evidence of a MRSA infection.

Patients were included if they met all of the following criteria: age 18 years or older, with no upper age limit; treated for a LRTI, identified by ICD-10 codes (J13-22, J44, J85); treated with empiric antibiotics active against MRSA, specifically vancomycin or linezolid; and treated at the Hospital of Central Connecticut (HOCC) or Hartford Hospital (HH) between July 1, 2018, and June 30, 2019, inclusive. Patients were excluded if they met 1 or more of the following criteria: age less than 18 years old; admitted for 48 hours or fewer or discharged from the emergency department; not treated at either facility; treated before July 1, 2018, or after June 30, 2019; treated for ventilator-associated pneumonia; received anti-MRSA therapy within 30 days prior to admission; or treated for a concurrent bacterial infection requiring anti-MRSA therapy.

Outcome Measures

The primary outcome was anti-MRSA days of therapy (DOT) in patients who underwent MRSA PCR testing compared to patients who did not undergo MRSA PCR testing. A subgroup analysis was completed to compare anti-MRSA DOT within patients in the MRSA PCR group. Patients in the subgroup were categorized by appropriate or inappropriate utilization, and anti-MRSA DOT were compared between these groups. Secondary outcomes that were evaluated included length of stay (LOS), 30-day readmission rate, and incidence of acute kidney injury (AKI). Thirty-day readmission was defined as admission to HOCC, HH, or any institution within Hartford HealthCare within 30 days of discharge. AKI was defined as an increase in serum creatinine by ≥ 0.3 mg/dL in 48 hours, increase ≥ 1.5 times baseline, or a urine volume < 0.5 mL/kg/hr for 6 hours.

Statistical Analyses

The study was powered for the primary outcome, anti-MRSA DOT, with a clinically meaningful difference of 1 day. Group sample sizes of 240 in the MRSA PCR group and 160 in the no MRSA PCR group would have afforded 92% power to detect that difference, if the null hypothesis was that both group means were 4 days and the alternative hypothesis was that the mean of the MRSA PCR group was 3 days, with estimated group standard deviations of 80% of each mean. This estimate used an alpha level of 0.05 with a 2-sided t-test. Among those who received a MRSA PCR test, a clinically meaningful difference between appropriate and inappropriate utilization was 5%.

Descriptive statistics were provided for all variables as a function of the individual hospital and for the combined data set. Continuous data were summarized with means and standard deviations (SD), or with median and interquartile ranges (IQR), depending on distribution. Categorical variables were reported as frequencies, using percentages. All data were evaluated for normality of distribution. Inferential statistics comprised a Student’s t-test to compare normally distributed, continuous data between groups. Nonparametric distributions were compared using a Mann-Whitney U test. Categorical comparisons were made using a Fisher’s exact test for 2×2 tables and a Pearson chi-square test for comparisons involving more than 2 groups.

Since anti-MRSA DOT (primary outcome) and LOS (secondary outcome) are often non-normally distributed, they have been transformed (eg, log or square root, again depending on distribution). Whichever native variable or transformation variable was appropriate was used as the outcome measure in a linear regression model to account for the influence of factors (covariates) that show significant univariate differences. Given the relatively small sample size, a maximum of 10 variables were included in the model. All factors were iterated in a forward regression model (most influential first) until no significant changes were observed.

All calculations were performed with SPSS v. 21 (IBM; Armonk, NY) using an a priori alpha level of 0.05, such that all results yielding P < 0.05 were deemed statistically significant.

Results

Of the 561 patient records reviewed, 319 patients were included and 242 patients were excluded. Reasons for exclusion included 65 patients admitted for a duration of 48 hours or less or discharged from the emergency department; 61 patients having another infection requiring anti-MRSA therapy; 60 patients not having a diagnosis of a LRTI or not receiving anti-MRSA therapy; 52 patients having received anti-MRSA therapy within 30 days prior to admission; and 4 patients treated outside of the specified date range.

Of the 319 patients included, 155 (48.6%) were in the MRSA PCR group and 164 (51.4%) were in the group that did not undergo MRSA PCR (Table 1). Of the 155 patients with a MRSA PCR ordered, the test was utilized appropriately in 94 (60.6%) patients and inappropriately in 61 (39.4%) patients (Table 2). In the MRSA PCR group, 135 patients had a negative result on PCR assay, with 133 of those patients having negative respiratory cultures, resulting in a NPV of 98.5%. Differences in baseline characteristics between the MRSA PCR and no MRSA PCR groups were observed. The patients in the MRSA PCR group appeared to be significantly more ill than those in the no MRSA PCR group, as indicated by statistically significant differences in intensive care unit (ICU) admissions (P = 0.001), positive chest radiographs (P = 0.034), sepsis at time of anti-MRSA initiation (P = 0.013), pulmonary consults placed (P = 0.003), and carbapenem usage (P = 0.047).

Outcomes

Median anti-MRSA DOT in the MRSA PCR group was shorter than DOT in the no MRSA PCR group, but this difference did not reach statistical significance (1.68 [IQR, 0.80-2.74] vs 1.86 days [IQR, 0.56-3.33], P = 0.458; Table 3). LOS in the MRSA PCR group was longer than in the no MRSA PCR group (6.0 [IQR, 4.0-10.0] vs 5.0 [IQR, 3.0-7.0] days, P = 0.001). There was no difference in 30-day readmissions that were related to the previous visit or incidence of AKI between groups.

In the subgroup analysis, anti-MRSA DOT in the MRSA PCR group with appropriate utilization was shorter than DOT in the MRSA PCR group with inappropriate utilization (1.16 [IQR, 0.44-1.88] vs 2.68 [IQR, 1.75-3.76] days, P < 0.001; Table 4). LOS in the MRSA PCR group with appropriate utilization was shorter than LOS in the inappropriate utilization group (5.0 [IQR, 4.0-7.0] vs 7.0 [IQR, 5.0-12.0] days, P < 0.001). Thirty-day readmissions that were related to the previous visit were significantly higher in patients in the MRSA PCR group with appropriate utilization (13 vs 2, P = 0.030). There was no difference in incidence of AKI between the groups.

A multivariate analysis was completed to determine whether the sicker MRSA PCR population was confounding outcomes, particularly the secondary outcome of LOS, which was noted to be longer in the MRSA PCR group (Table 5). When comparing LOS in the MRSA PCR and the no MRSA PCR patients, the multivariate analysis showed that admission to the ICU and carbapenem use were associated with a longer LOS (P < 0.001 and P = 0.009, respectively). The incidence of admission to the ICU and carbapenem use were higher in the MRSA PCR group (P = 0.001 and P = 0.047). Therefore, longer LOS in the MRSA PCR patients could be a result of the higher prevalence of ICU admissions and infections requiring carbapenem therapy rather than the result of the MRSA PCR itself.

Discussion

A MRSA PCR nasal swab protocol can be used to minimize a patient’s exposure to unnecessary broad-spectrum antibiotics, thereby preventing antimicrobial resistance. Thus, it is important to assess how our health system is utilizing this antimicrobial stewardship tactic. With the MRSA PCR’s high NPV, providers can be confident that MRSA pneumonia is unlikely in the absence of MRSA colonization. Our study established a NPV of 98.5%, which is similar to other studies, all of which have shown NPVs greater than 95%.^5-8 Despite the high NPV, this study demonstrated that only 51.4% of patients with LRTI had orders for a MRSA PCR. Of the 155 patients with a MRSA PCR, the test was utilized appropriately only 60.6% of the time. A majority of the inappropriately utilized tests were due to MRSA PCR orders placed more than 48 hours after anti-MRSA therapy initiation. To our knowledge, no other studies have assessed the clinical utility of MRSA PCR nasal swabs as an antimicrobial stewardship tool in a diverse health system; therefore, these results are useful to guide future practices at our institution. There is a clear need for provider and pharmacist education to increase the use of MRSA PCR nasal swab testing for patients with LRTI being treated with anti-MRSA therapy. Additionally, clinician education regarding the initial timing of the MRSA PCR order and the proper utilization of the results of the MRSA PCR likely will benefit patient outcomes at our institution.

When evaluating anti-MRSA DOT, this study demonstrated a reduction of only 0.18 days (about 4 hours) of anti-MRSA therapy in the patients who received MRSA PCR testing compared to the patients without a MRSA PCR ordered. Our anti-MRSA DOT reduction was lower than what has been reported in similar studies. For example, Baby et al found that the use of the MRSA PCR was associated with 46.6 fewer hours of unnecessary antimicrobial treatment. Willis et al evaluated a pharmacist-driven protocol that resulted in a reduction of 1.8 days of anti-MRSA therapy, despite a protocol compliance rate of only 55%.^9,10 In our study, the patients in the MRSA PCR group appeared to be significantly more ill than those in the no MRSA PCR group, which may be the reason for the incongruences in our results compared to the current literature. Characteristics such as ICU admissions, positive chest radiographs, sepsis cases, pulmonary consults, and carbapenem usage—all of which are indicative of a sicker population—were more prevalent in the MRSA PCR group. This sicker population could have underestimated the reduction of DOT in the MRSA PCR group compared to the no MRSA PCR group.

After isolating the MRSA PCR patients in the subgroup analysis, anti-MRSA DOT was 1.5 days shorter when the test was appropriately utilized, which is more comparable to what has been reported in the literature.^9,10 Only 60.6% of the MRSA PCR patients had their anti-MRSA therapy appropriately managed based on the MRSA PCR. Interestingly, a majority of patients in the inappropriate utilization group had MRSA PCR tests ordered more than 48 hours after beginning anti-MRSA therapy. More prompt and efficient ordering of the MRSA PCR may have resulted in more opportunities for earlier de-escalation of therapy. Due to these factors, the patients in the inappropriate utilization group could have further contributed to the underestimated difference in anti-MRSA DOT between the MRSA PCR and no MRSA PCR patients in the primary outcome. Additionally, there were no notable differences between the appropriate and inappropriate utilization groups, unlike in the MRSA PCR and no MRSA PCR groups, which is why we were able to draw more robust conclusions in the subgroup analysis. Therefore, the subgroup analysis confirmed that if the results of the MRSA PCR are used appropriately to guide anti-MRSA therapy, patients can potentially avoid 36 hours of broad-spectrum antibiotics.

Data on how the utilization of the MRSA PCR nasal swab can affect LOS are limited; however, one study did report a 2.8-day reduction in LOS after implementation of a pharmacist-driven MRSA PCR nasal swab protocol.¹¹ Our study demonstrated that LOS was significantly longer in the MRSA PCR group than in the no MRSA PCR group. This result was likely affected by the aforementioned sicker MRSA PCR population. Our multivariate analysis further confirmed that ICU admissions were associated with a longer LOS, and, given that the MRSA PCR group had a significantly higher ICU population, this likely confounded these results. If our 2 groups had had more evenly distributed characteristics, it is possible that we could have found a shorter LOS in the MRSA PCR group, similar to what is reported in the literature. In the subgroup analysis, LOS was 2 days shorter in the appropriate utilization group compared to the inappropriate utilization group. This further affirms that the results of the MRSA PCR must be used appropriately in order for patient outcomes, like LOS, to benefit.

The effects of the MRSA PCR nasal swab on 30-day readmission rates and incidence of AKI are not well-documented in the literature. One study did report 30-day readmission rates as an outcome, but did not cite any difference after the implementation of a protocol that utilized MRSA PCR nasal swab testing.¹² The outcome of AKI is slightly better represented in the literature, but the results are conflicting. Some studies report no difference after the implementation of a MRSA PCR-based protocol,¹¹ and others report a significant decrease in AKI with the use of the MRSA PCR.⁹ Our study detected no difference in 30-day readmission rates related to the previous admission or in AKI between the MRSA PCR and no MRSA PCR populations. In the subgroup analysis, 30-day readmission rates were significantly higher in the MRSA PCR group with appropriate utilization than in the group with inappropriate utilization; however, our study was not powered to detect a difference in this secondary outcome.

This study had some limitations that may have affected our results. First, this study was a retrospective chart review. Additionally, the baseline characteristics were not well balanced across the different groups. There were sicker patients in the MRSA PCR group, which may have led to an underestimate of the reduction in DOT and LOS in these patients. Finally, we did not include enough patient records to reach power in the MRSA PCR group due to a higher than expected number of patients meeting exclusion criteria. Had we attained sufficient power, there may have been more profound reductions in DOT and LOS.

Conclusion

MRSA infections are a common cause for hospitalization, and there is a growing need for antimicrobial stewardship efforts to limit unnecessary antibiotic usage in order to prevent resistance. As illustrated in our study, appropriate utilization of the MRSA PCR can reduce DOT up to 1.5 days. However, our results suggest that there is room for provider and pharmacist education to increase the use of MRSA PCR nasal swab testing in patients with LRTI receiving anti-MRSA therapy. Further emphasis on the appropriate utilization of the MRSA PCR within our health care system is essential.

Corresponding author: Casey Dempsey, PharmD, BCIDP, 80 Seymour St., Hartford, CT 06106; [email protected].

Financial disclosures: None.

From the Hospital of Central Connecticut, New Britain, CT (Dr. Caulfield and Dr. Shepard); Hartford Hospital, Hartford, CT (Dr. Linder and Dr. Dempsey); and the Hartford HealthCare Research Program, Hartford, CT (Dr. O’Sullivan).

Abstract

• Objective: To assess the utility of methicillin-resistant Staphylococcus aureus (MRSA) polymerase chain reaction (PCR) nasal swab testing in patients with lower respiratory tract infections (LRTI).
• Design and setting: Multicenter, retrospective, electronic chart review conducted within the Hartford HealthCare system.
• Participants: Patients who were treated for LRTIs at the Hospital of Central Connecticut or Hartford Hospital between July 1, 2018, and June 30, 2019.
• Measurements: The primary outcome was anti-MRSA days of therapy (DOT) in patients who underwent MRSA PCR testing versus those who did not. In a subgroup analysis, we compared anti-MRSA DOT among patients with appropriate versus inappropriate utilization of the MRSA PCR test.
• Results: Of the 319 patients treated for LRTIs, 155 (48.6%) had a MRSA PCR ordered, and appropriate utilization occurred in 94 (60.6%) of these patients. Anti-MRSA DOT in the MRSA PCR group (n = 155) was shorter than in the group that did not undergo MRSA PCR testing (n = 164), but this difference did not reach statistical significance (1.68 days [interquartile range {IQR}, 0.80-2.74] vs 1.86 days [IQR, 0.56-3.33], P = 0.458). In the subgroup analysis, anti-MRSA DOT was significantly shorter in the MRSA PCR group with appropriate utilization compared to the inappropriate utilization group (1.16 [IQR, 0.44-1.88] vs 2.68 [IQR, 1.75-3.76], P < 0.001)
• Conclusion: Appropriate utilization of MRSA PCR nasal swab testing can reduce DOT in patients with LRTI. Further education is necessary to expand the appropriate use of the MRSA PCR test across our health system.

Keywords: MRSA; LRTI; pneumonia; antimicrobial stewardship; antibiotic resistance.

More than 300,000 patients were hospitalized with methicillin-resistant Staphylococcus aureus (MRSA) infections in the United States in 2017, and at least 10,000 of these cases resulted in mortality.¹ While MRSA infections overall are decreasing, it is crucial to continue to employ antimicrobial stewardship tactics to keep these infections at bay. Recently, strains of S. aureus have become resistant to vancomycin, making this bacterium even more difficult to treat.²

A novel tactic in antimicrobial stewardship involves the use of MRSA polymerase chain reaction (PCR) nasal swab testing to rule out the presence of MRSA in patients with lower respiratory tract infections (LRTI). If used appropriately, this approach may decrease the number of days patients are treated with anti-MRSA antimicrobials. Waiting for cultures to speciate can take up to 72 hours,³ meaning that patients may be exposed to 3 days of unnecessary broad-spectrum antibiotics. Results of MRSA PCR assay of nasal swab specimens can be available in 1 to 2 hours,⁴ allowing for more rapid de-escalation of therapy. Numerous studies have shown that this test has a negative predictive value (NPV) greater than 95%, indicating that a negative nasal swab result may be useful to guide de-escalation of antibiotic therapy.^5-8 The purpose of this study was to assess the utility of MRSA PCR nasal swab testing in patients with LRTI throughout the Hartford HealthCare system.

Methods

Design

This study was a multicenter, retrospective, electronic chart review. It was approved by the Hartford HealthCare Institutional Review Board (HHC-2019-0169).

Selection of Participants

Patients were identified through electronic medical record reports based on ICD-10 codes. Records were categorized into 2 groups: patients who received a MRSA PCR nasal swab testing and patients who did not. Patients who received the MRSA PCR were further categorized by appropriate or inappropriate utilization. Appropriate utilization of the MRSA PCR was defined as MRSA PCR ordered within 48 hours of a new vancomycin or linezolid order, and anti-MRSA therapy discontinued within 24 hours of a negative result. Inappropriate utilization of the MRSA PCR was defined as MRSA PCR ordered more than 48 hours after a new vancomycin or linezolid order, or continuation of anti-MRSA therapy despite a negative MRSA PCR and no other evidence of a MRSA infection.

Patients were included if they met all of the following criteria: age 18 years or older, with no upper age limit; treated for a LRTI, identified by ICD-10 codes (J13-22, J44, J85); treated with empiric antibiotics active against MRSA, specifically vancomycin or linezolid; and treated at the Hospital of Central Connecticut (HOCC) or Hartford Hospital (HH) between July 1, 2018, and June 30, 2019, inclusive. Patients were excluded if they met 1 or more of the following criteria: age less than 18 years old; admitted for 48 hours or fewer or discharged from the emergency department; not treated at either facility; treated before July 1, 2018, or after June 30, 2019; treated for ventilator-associated pneumonia; received anti-MRSA therapy within 30 days prior to admission; or treated for a concurrent bacterial infection requiring anti-MRSA therapy.

Outcome Measures

The primary outcome was anti-MRSA days of therapy (DOT) in patients who underwent MRSA PCR testing compared to patients who did not undergo MRSA PCR testing. A subgroup analysis was completed to compare anti-MRSA DOT within patients in the MRSA PCR group. Patients in the subgroup were categorized by appropriate or inappropriate utilization, and anti-MRSA DOT were compared between these groups. Secondary outcomes that were evaluated included length of stay (LOS), 30-day readmission rate, and incidence of acute kidney injury (AKI). Thirty-day readmission was defined as admission to HOCC, HH, or any institution within Hartford HealthCare within 30 days of discharge. AKI was defined as an increase in serum creatinine by ≥ 0.3 mg/dL in 48 hours, increase ≥ 1.5 times baseline, or a urine volume < 0.5 mL/kg/hr for 6 hours.

Statistical Analyses

The study was powered for the primary outcome, anti-MRSA DOT, with a clinically meaningful difference of 1 day. Group sample sizes of 240 in the MRSA PCR group and 160 in the no MRSA PCR group would have afforded 92% power to detect that difference, if the null hypothesis was that both group means were 4 days and the alternative hypothesis was that the mean of the MRSA PCR group was 3 days, with estimated group standard deviations of 80% of each mean. This estimate used an alpha level of 0.05 with a 2-sided t-test. Among those who received a MRSA PCR test, a clinically meaningful difference between appropriate and inappropriate utilization was 5%.

Descriptive statistics were provided for all variables as a function of the individual hospital and for the combined data set. Continuous data were summarized with means and standard deviations (SD), or with median and interquartile ranges (IQR), depending on distribution. Categorical variables were reported as frequencies, using percentages. All data were evaluated for normality of distribution. Inferential statistics comprised a Student’s t-test to compare normally distributed, continuous data between groups. Nonparametric distributions were compared using a Mann-Whitney U test. Categorical comparisons were made using a Fisher’s exact test for 2×2 tables and a Pearson chi-square test for comparisons involving more than 2 groups.

Since anti-MRSA DOT (primary outcome) and LOS (secondary outcome) are often non-normally distributed, they have been transformed (eg, log or square root, again depending on distribution). Whichever native variable or transformation variable was appropriate was used as the outcome measure in a linear regression model to account for the influence of factors (covariates) that show significant univariate differences. Given the relatively small sample size, a maximum of 10 variables were included in the model. All factors were iterated in a forward regression model (most influential first) until no significant changes were observed.

All calculations were performed with SPSS v. 21 (IBM; Armonk, NY) using an a priori alpha level of 0.05, such that all results yielding P < 0.05 were deemed statistically significant.

Results

Of the 561 patient records reviewed, 319 patients were included and 242 patients were excluded. Reasons for exclusion included 65 patients admitted for a duration of 48 hours or less or discharged from the emergency department; 61 patients having another infection requiring anti-MRSA therapy; 60 patients not having a diagnosis of a LRTI or not receiving anti-MRSA therapy; 52 patients having received anti-MRSA therapy within 30 days prior to admission; and 4 patients treated outside of the specified date range.

Of the 319 patients included, 155 (48.6%) were in the MRSA PCR group and 164 (51.4%) were in the group that did not undergo MRSA PCR (Table 1). Of the 155 patients with a MRSA PCR ordered, the test was utilized appropriately in 94 (60.6%) patients and inappropriately in 61 (39.4%) patients (Table 2). In the MRSA PCR group, 135 patients had a negative result on PCR assay, with 133 of those patients having negative respiratory cultures, resulting in a NPV of 98.5%. Differences in baseline characteristics between the MRSA PCR and no MRSA PCR groups were observed. The patients in the MRSA PCR group appeared to be significantly more ill than those in the no MRSA PCR group, as indicated by statistically significant differences in intensive care unit (ICU) admissions (P = 0.001), positive chest radiographs (P = 0.034), sepsis at time of anti-MRSA initiation (P = 0.013), pulmonary consults placed (P = 0.003), and carbapenem usage (P = 0.047).

Outcomes

Median anti-MRSA DOT in the MRSA PCR group was shorter than DOT in the no MRSA PCR group, but this difference did not reach statistical significance (1.68 [IQR, 0.80-2.74] vs 1.86 days [IQR, 0.56-3.33], P = 0.458; Table 3). LOS in the MRSA PCR group was longer than in the no MRSA PCR group (6.0 [IQR, 4.0-10.0] vs 5.0 [IQR, 3.0-7.0] days, P = 0.001). There was no difference in 30-day readmissions that were related to the previous visit or incidence of AKI between groups.

In the subgroup analysis, anti-MRSA DOT in the MRSA PCR group with appropriate utilization was shorter than DOT in the MRSA PCR group with inappropriate utilization (1.16 [IQR, 0.44-1.88] vs 2.68 [IQR, 1.75-3.76] days, P < 0.001; Table 4). LOS in the MRSA PCR group with appropriate utilization was shorter than LOS in the inappropriate utilization group (5.0 [IQR, 4.0-7.0] vs 7.0 [IQR, 5.0-12.0] days, P < 0.001). Thirty-day readmissions that were related to the previous visit were significantly higher in patients in the MRSA PCR group with appropriate utilization (13 vs 2, P = 0.030). There was no difference in incidence of AKI between the groups.

A multivariate analysis was completed to determine whether the sicker MRSA PCR population was confounding outcomes, particularly the secondary outcome of LOS, which was noted to be longer in the MRSA PCR group (Table 5). When comparing LOS in the MRSA PCR and the no MRSA PCR patients, the multivariate analysis showed that admission to the ICU and carbapenem use were associated with a longer LOS (P < 0.001 and P = 0.009, respectively). The incidence of admission to the ICU and carbapenem use were higher in the MRSA PCR group (P = 0.001 and P = 0.047). Therefore, longer LOS in the MRSA PCR patients could be a result of the higher prevalence of ICU admissions and infections requiring carbapenem therapy rather than the result of the MRSA PCR itself.

Discussion

A MRSA PCR nasal swab protocol can be used to minimize a patient’s exposure to unnecessary broad-spectrum antibiotics, thereby preventing antimicrobial resistance. Thus, it is important to assess how our health system is utilizing this antimicrobial stewardship tactic. With the MRSA PCR’s high NPV, providers can be confident that MRSA pneumonia is unlikely in the absence of MRSA colonization. Our study established a NPV of 98.5%, which is similar to other studies, all of which have shown NPVs greater than 95%.^5-8 Despite the high NPV, this study demonstrated that only 51.4% of patients with LRTI had orders for a MRSA PCR. Of the 155 patients with a MRSA PCR, the test was utilized appropriately only 60.6% of the time. A majority of the inappropriately utilized tests were due to MRSA PCR orders placed more than 48 hours after anti-MRSA therapy initiation. To our knowledge, no other studies have assessed the clinical utility of MRSA PCR nasal swabs as an antimicrobial stewardship tool in a diverse health system; therefore, these results are useful to guide future practices at our institution. There is a clear need for provider and pharmacist education to increase the use of MRSA PCR nasal swab testing for patients with LRTI being treated with anti-MRSA therapy. Additionally, clinician education regarding the initial timing of the MRSA PCR order and the proper utilization of the results of the MRSA PCR likely will benefit patient outcomes at our institution.

When evaluating anti-MRSA DOT, this study demonstrated a reduction of only 0.18 days (about 4 hours) of anti-MRSA therapy in the patients who received MRSA PCR testing compared to the patients without a MRSA PCR ordered. Our anti-MRSA DOT reduction was lower than what has been reported in similar studies. For example, Baby et al found that the use of the MRSA PCR was associated with 46.6 fewer hours of unnecessary antimicrobial treatment. Willis et al evaluated a pharmacist-driven protocol that resulted in a reduction of 1.8 days of anti-MRSA therapy, despite a protocol compliance rate of only 55%.^9,10 In our study, the patients in the MRSA PCR group appeared to be significantly more ill than those in the no MRSA PCR group, which may be the reason for the incongruences in our results compared to the current literature. Characteristics such as ICU admissions, positive chest radiographs, sepsis cases, pulmonary consults, and carbapenem usage—all of which are indicative of a sicker population—were more prevalent in the MRSA PCR group. This sicker population could have underestimated the reduction of DOT in the MRSA PCR group compared to the no MRSA PCR group.

After isolating the MRSA PCR patients in the subgroup analysis, anti-MRSA DOT was 1.5 days shorter when the test was appropriately utilized, which is more comparable to what has been reported in the literature.^9,10 Only 60.6% of the MRSA PCR patients had their anti-MRSA therapy appropriately managed based on the MRSA PCR. Interestingly, a majority of patients in the inappropriate utilization group had MRSA PCR tests ordered more than 48 hours after beginning anti-MRSA therapy. More prompt and efficient ordering of the MRSA PCR may have resulted in more opportunities for earlier de-escalation of therapy. Due to these factors, the patients in the inappropriate utilization group could have further contributed to the underestimated difference in anti-MRSA DOT between the MRSA PCR and no MRSA PCR patients in the primary outcome. Additionally, there were no notable differences between the appropriate and inappropriate utilization groups, unlike in the MRSA PCR and no MRSA PCR groups, which is why we were able to draw more robust conclusions in the subgroup analysis. Therefore, the subgroup analysis confirmed that if the results of the MRSA PCR are used appropriately to guide anti-MRSA therapy, patients can potentially avoid 36 hours of broad-spectrum antibiotics.

Data on how the utilization of the MRSA PCR nasal swab can affect LOS are limited; however, one study did report a 2.8-day reduction in LOS after implementation of a pharmacist-driven MRSA PCR nasal swab protocol.¹¹ Our study demonstrated that LOS was significantly longer in the MRSA PCR group than in the no MRSA PCR group. This result was likely affected by the aforementioned sicker MRSA PCR population. Our multivariate analysis further confirmed that ICU admissions were associated with a longer LOS, and, given that the MRSA PCR group had a significantly higher ICU population, this likely confounded these results. If our 2 groups had had more evenly distributed characteristics, it is possible that we could have found a shorter LOS in the MRSA PCR group, similar to what is reported in the literature. In the subgroup analysis, LOS was 2 days shorter in the appropriate utilization group compared to the inappropriate utilization group. This further affirms that the results of the MRSA PCR must be used appropriately in order for patient outcomes, like LOS, to benefit.

The effects of the MRSA PCR nasal swab on 30-day readmission rates and incidence of AKI are not well-documented in the literature. One study did report 30-day readmission rates as an outcome, but did not cite any difference after the implementation of a protocol that utilized MRSA PCR nasal swab testing.¹² The outcome of AKI is slightly better represented in the literature, but the results are conflicting. Some studies report no difference after the implementation of a MRSA PCR-based protocol,¹¹ and others report a significant decrease in AKI with the use of the MRSA PCR.⁹ Our study detected no difference in 30-day readmission rates related to the previous admission or in AKI between the MRSA PCR and no MRSA PCR populations. In the subgroup analysis, 30-day readmission rates were significantly higher in the MRSA PCR group with appropriate utilization than in the group with inappropriate utilization; however, our study was not powered to detect a difference in this secondary outcome.

This study had some limitations that may have affected our results. First, this study was a retrospective chart review. Additionally, the baseline characteristics were not well balanced across the different groups. There were sicker patients in the MRSA PCR group, which may have led to an underestimate of the reduction in DOT and LOS in these patients. Finally, we did not include enough patient records to reach power in the MRSA PCR group due to a higher than expected number of patients meeting exclusion criteria. Had we attained sufficient power, there may have been more profound reductions in DOT and LOS.

Conclusion

MRSA infections are a common cause for hospitalization, and there is a growing need for antimicrobial stewardship efforts to limit unnecessary antibiotic usage in order to prevent resistance. As illustrated in our study, appropriate utilization of the MRSA PCR can reduce DOT up to 1.5 days. However, our results suggest that there is room for provider and pharmacist education to increase the use of MRSA PCR nasal swab testing in patients with LRTI receiving anti-MRSA therapy. Further emphasis on the appropriate utilization of the MRSA PCR within our health care system is essential.

Corresponding author: Casey Dempsey, PharmD, BCIDP, 80 Seymour St., Hartford, CT 06106; [email protected].

Financial disclosures: None.

The Children’s Hospital of Philadelphia, Philadelphia, PA.

The effects of COVID-19 on children’s health are multifaceted. In comparison to adults, children typically experience far milder physical consequences when infected with the virus. A notable exception is the newly described multisystem inflammatory syndrome associated with COVID-19 (MIS-C), which has proven to be a source of significant morbidity among the children it affects.¹ Nevertheless, even those children not infected with COVID-19 have suffered due to the disease. School closures have deprived children of opportunities for social and academic growth and, in some cases, the provision of food, social services, medication administration, and many different therapies. Social distancing rules have limited play among children, which is crucial to their development and mental health. The impact on children who have lost family members, including parents, is monumental. Amidst all of this observable suffering, however, the pandemic poses a less visible threat to the health of children.

It is well documented that concern about exposure to COVID-19 has led many adults to avoid emergency departments (EDs) around the world. We believe parents may be avoiding ED visits for their children for the same reason. In the United States, ED volumes dropped approximately 50% during spring 2020.² While EDs saw increasing, and at times overwhelming, numbers of patients with COVID-19, the number of patients presenting with other life-threatening medical issues, including heart attacks and strokes, declined.^3,4 Data from the National Center for Health Statistics this past spring revealed nationwide increases in deaths due to nonrespiratory causes such as diabetes, heart disease, and stroke.⁵ ED avoidance and unprecedented lack of access to outpatient care, though with the intent to reduce overall risk, are likely significant contributors to these deaths.

Pediatric patients, especially the most vulnerable, are similarly at risk for deleterious health-related consequences from ED avoidance and from limited access to primary and outpatient specialty care. Data from Europe indicate dramatic drops in pediatric ED (PED) volumes, as well as an increase in the proportion of ED visits leading to hospitalization.^6,7 These studies suggest that when patients do ultimately present to the PED, they may be more seriously ill.

At our institution, we have seen many COVID-19-negative patients whose medical care has been negatively influenced by the pandemic. A few months ago, a 1-month-old infant with an underlying health condition presented to the PED in extremis after weeks of progressively worsening feeding issues. The infant had been closely followed by the primary care provider (PCP) and subspecialty team via phone calls, televisits, and some office visits. Both physicians and parents had tried to resolve the feeding issues within the outpatient context, explicitly hoping to avoid potential exposure of this fragile patient to COVID-19 in the hospital. On eventual presentation to the PED, the infant was profoundly dehydrated, with significant electrolyte derangement and an acute abdomen, requiring admission to the intensive care unit. Ultimately, a new diagnosis of Hirschsprung disease was made, and the infant was hospitalized for several weeks for weight gain.

Later this summer, a school-aged child with a history of poorly controlled type 1 diabetes presented to an affiliated community hospital comatose and with Kussmaul respirations. Prior to the pandemic, a school nurse administered the child’s morning insulin. Since school closed, the patient had been responsible for administering this dose of insulin while the parents worked outside the home. Despite close and frequent communication between the patient’s endocrinology team and the family, the patient’s glucose and ketone levels began to rise. The parent administered repeated boluses of insulin at home in an attempt to avoid the perceived exposure risk associated with an ED visit. On presentation to the PED, the patient was profoundly altered, with a pH of 7.0. When transfer to a tertiary care center was recommended, the patient’s parent expressed persistent concerns about COVID-19 exposure in the larger hospital, although ultimately consent to transfer was given.

A third case from this summer provides an example of a different type of patient affected by COVID-19: the neonate whose birth circumstances were altered due to the virus. A 3-day-old, full-term infant presented to the ED with hypothermia after PCP referral. The parents had considered both home birth and hospital delivery earlier in the pregnancy, ultimately opting for home birth due to concerns about COVID-19 exposure in the hospital. The pregnancy and delivery were uncomplicated. The neonate did not receive the first hepatitis B vaccine, erythromycin eye ointment, or vitamin K after delivery. In the first 3 days of life, the patient had voided once and stooled once per day. The patient’s mother, inexperienced with breastfeeding and without access to a lactation consultant, was unsure about latch or emptying of her breasts. At the first pediatrician visit, the infant was noted to be hypothermic to 35°C, intermittently bradycardic to the 80s, and with diminished arousal. In the PED, a full sepsis work-up was initiated. Though multiple attempts were made by different providers, only a minimal amount of blood could be drawn, presumably due to dehydration. Of note, the neonate received vitamin K subcutaneously prior to lumbar puncture.

Pediatricians across the country have gone to great lengths to protect their patients and to provide high-quality care both inside and outside the office during this unprecedented time. Nevertheless, these 3 cases illustrate the detrimental effects of COVID-19 on the delivery of pediatric health care. The first 2 cases in particular demonstrate the limitations of even close and consistent phone and televisit follow-up. Telehealth has provided a lifeline for patients and families during the pandemic, and, in most cases, has provided an excellent temporary substitution for office visits. There are, however, limitations to care without physical evaluation. Had the children in the first 2 cases been evaluated in person sooner, they may have been referred to a higher level of care more expediently. Likewise, in all 3 cases, parental reservations about exposing their children to COVID-19 through a trip to the hospital, however well-intentioned, likely played a role in the eventual severity of illness with which each child presented to the hospital.

If we are encountering children in the PED with severe illness due to delayed presentation to care, what about the children we aren’t seeing? As COVID-19 cases rise daily in the United States, we must be aware of the possibility of ED avoidance. We propose a multimodal approach to combat this dangerous phenomenon. Inpatient and ED-based pediatricians must maintain clear and open lines of communication with outpatient colleagues so that we can partner in considering which cases warrant prompt ED evaluation, even in the midst of a pandemic. All pediatricians must remind families that our hospitals remain open and ready to treat children safely. We must promote community awareness of the numerous safety precautions we take every day so that patients and families can feel comfortable seeking care at the hospital; the message of ED and hospital safety must be even more robust for caregivers of our particularly vulnerable children. As always, how we communicate with patients and their families matters. Validating and addressing concerns about COVID-19 exposure, while providing reassurance about the safety of our hospitals, could save children’s lives.

Acknowledgment: Thank you to Dr. Cynthia Mollen and Dr. Kathy Shaw for their reviews of the manuscript.

Corresponding author: Regina L. Toto, MD, Department of Pediatrics, The Children’s Hospital of Philadelphia, 3401 Civic Center Blvd., Philadelphia, PA 19104; [email protected].

Financial disclosures: None.

Keywords: coronavirus; pediatric; children; access to care; emergency department.

The Children’s Hospital of Philadelphia, Philadelphia, PA.

The effects of COVID-19 on children’s health are multifaceted. In comparison to adults, children typically experience far milder physical consequences when infected with the virus. A notable exception is the newly described multisystem inflammatory syndrome associated with COVID-19 (MIS-C), which has proven to be a source of significant morbidity among the children it affects.¹ Nevertheless, even those children not infected with COVID-19 have suffered due to the disease. School closures have deprived children of opportunities for social and academic growth and, in some cases, the provision of food, social services, medication administration, and many different therapies. Social distancing rules have limited play among children, which is crucial to their development and mental health. The impact on children who have lost family members, including parents, is monumental. Amidst all of this observable suffering, however, the pandemic poses a less visible threat to the health of children.

It is well documented that concern about exposure to COVID-19 has led many adults to avoid emergency departments (EDs) around the world. We believe parents may be avoiding ED visits for their children for the same reason. In the United States, ED volumes dropped approximately 50% during spring 2020.² While EDs saw increasing, and at times overwhelming, numbers of patients with COVID-19, the number of patients presenting with other life-threatening medical issues, including heart attacks and strokes, declined.^3,4 Data from the National Center for Health Statistics this past spring revealed nationwide increases in deaths due to nonrespiratory causes such as diabetes, heart disease, and stroke.⁵ ED avoidance and unprecedented lack of access to outpatient care, though with the intent to reduce overall risk, are likely significant contributors to these deaths.

Pediatric patients, especially the most vulnerable, are similarly at risk for deleterious health-related consequences from ED avoidance and from limited access to primary and outpatient specialty care. Data from Europe indicate dramatic drops in pediatric ED (PED) volumes, as well as an increase in the proportion of ED visits leading to hospitalization.^6,7 These studies suggest that when patients do ultimately present to the PED, they may be more seriously ill.

At our institution, we have seen many COVID-19-negative patients whose medical care has been negatively influenced by the pandemic. A few months ago, a 1-month-old infant with an underlying health condition presented to the PED in extremis after weeks of progressively worsening feeding issues. The infant had been closely followed by the primary care provider (PCP) and subspecialty team via phone calls, televisits, and some office visits. Both physicians and parents had tried to resolve the feeding issues within the outpatient context, explicitly hoping to avoid potential exposure of this fragile patient to COVID-19 in the hospital. On eventual presentation to the PED, the infant was profoundly dehydrated, with significant electrolyte derangement and an acute abdomen, requiring admission to the intensive care unit. Ultimately, a new diagnosis of Hirschsprung disease was made, and the infant was hospitalized for several weeks for weight gain.

Later this summer, a school-aged child with a history of poorly controlled type 1 diabetes presented to an affiliated community hospital comatose and with Kussmaul respirations. Prior to the pandemic, a school nurse administered the child’s morning insulin. Since school closed, the patient had been responsible for administering this dose of insulin while the parents worked outside the home. Despite close and frequent communication between the patient’s endocrinology team and the family, the patient’s glucose and ketone levels began to rise. The parent administered repeated boluses of insulin at home in an attempt to avoid the perceived exposure risk associated with an ED visit. On presentation to the PED, the patient was profoundly altered, with a pH of 7.0. When transfer to a tertiary care center was recommended, the patient’s parent expressed persistent concerns about COVID-19 exposure in the larger hospital, although ultimately consent to transfer was given.

A third case from this summer provides an example of a different type of patient affected by COVID-19: the neonate whose birth circumstances were altered due to the virus. A 3-day-old, full-term infant presented to the ED with hypothermia after PCP referral. The parents had considered both home birth and hospital delivery earlier in the pregnancy, ultimately opting for home birth due to concerns about COVID-19 exposure in the hospital. The pregnancy and delivery were uncomplicated. The neonate did not receive the first hepatitis B vaccine, erythromycin eye ointment, or vitamin K after delivery. In the first 3 days of life, the patient had voided once and stooled once per day. The patient’s mother, inexperienced with breastfeeding and without access to a lactation consultant, was unsure about latch or emptying of her breasts. At the first pediatrician visit, the infant was noted to be hypothermic to 35°C, intermittently bradycardic to the 80s, and with diminished arousal. In the PED, a full sepsis work-up was initiated. Though multiple attempts were made by different providers, only a minimal amount of blood could be drawn, presumably due to dehydration. Of note, the neonate received vitamin K subcutaneously prior to lumbar puncture.

Pediatricians across the country have gone to great lengths to protect their patients and to provide high-quality care both inside and outside the office during this unprecedented time. Nevertheless, these 3 cases illustrate the detrimental effects of COVID-19 on the delivery of pediatric health care. The first 2 cases in particular demonstrate the limitations of even close and consistent phone and televisit follow-up. Telehealth has provided a lifeline for patients and families during the pandemic, and, in most cases, has provided an excellent temporary substitution for office visits. There are, however, limitations to care without physical evaluation. Had the children in the first 2 cases been evaluated in person sooner, they may have been referred to a higher level of care more expediently. Likewise, in all 3 cases, parental reservations about exposing their children to COVID-19 through a trip to the hospital, however well-intentioned, likely played a role in the eventual severity of illness with which each child presented to the hospital.

If we are encountering children in the PED with severe illness due to delayed presentation to care, what about the children we aren’t seeing? As COVID-19 cases rise daily in the United States, we must be aware of the possibility of ED avoidance. We propose a multimodal approach to combat this dangerous phenomenon. Inpatient and ED-based pediatricians must maintain clear and open lines of communication with outpatient colleagues so that we can partner in considering which cases warrant prompt ED evaluation, even in the midst of a pandemic. All pediatricians must remind families that our hospitals remain open and ready to treat children safely. We must promote community awareness of the numerous safety precautions we take every day so that patients and families can feel comfortable seeking care at the hospital; the message of ED and hospital safety must be even more robust for caregivers of our particularly vulnerable children. As always, how we communicate with patients and their families matters. Validating and addressing concerns about COVID-19 exposure, while providing reassurance about the safety of our hospitals, could save children’s lives.

Acknowledgment: Thank you to Dr. Cynthia Mollen and Dr. Kathy Shaw for their reviews of the manuscript.

Corresponding author: Regina L. Toto, MD, Department of Pediatrics, The Children’s Hospital of Philadelphia, 3401 Civic Center Blvd., Philadelphia, PA 19104; [email protected].

Financial disclosures: None.

Keywords: coronavirus; pediatric; children; access to care; emergency department.

The Children’s Hospital of Philadelphia, Philadelphia, PA.

The effects of COVID-19 on children’s health are multifaceted. In comparison to adults, children typically experience far milder physical consequences when infected with the virus. A notable exception is the newly described multisystem inflammatory syndrome associated with COVID-19 (MIS-C), which has proven to be a source of significant morbidity among the children it affects.¹ Nevertheless, even those children not infected with COVID-19 have suffered due to the disease. School closures have deprived children of opportunities for social and academic growth and, in some cases, the provision of food, social services, medication administration, and many different therapies. Social distancing rules have limited play among children, which is crucial to their development and mental health. The impact on children who have lost family members, including parents, is monumental. Amidst all of this observable suffering, however, the pandemic poses a less visible threat to the health of children.

It is well documented that concern about exposure to COVID-19 has led many adults to avoid emergency departments (EDs) around the world. We believe parents may be avoiding ED visits for their children for the same reason. In the United States, ED volumes dropped approximately 50% during spring 2020.² While EDs saw increasing, and at times overwhelming, numbers of patients with COVID-19, the number of patients presenting with other life-threatening medical issues, including heart attacks and strokes, declined.^3,4 Data from the National Center for Health Statistics this past spring revealed nationwide increases in deaths due to nonrespiratory causes such as diabetes, heart disease, and stroke.⁵ ED avoidance and unprecedented lack of access to outpatient care, though with the intent to reduce overall risk, are likely significant contributors to these deaths.

Pediatric patients, especially the most vulnerable, are similarly at risk for deleterious health-related consequences from ED avoidance and from limited access to primary and outpatient specialty care. Data from Europe indicate dramatic drops in pediatric ED (PED) volumes, as well as an increase in the proportion of ED visits leading to hospitalization.^6,7 These studies suggest that when patients do ultimately present to the PED, they may be more seriously ill.

At our institution, we have seen many COVID-19-negative patients whose medical care has been negatively influenced by the pandemic. A few months ago, a 1-month-old infant with an underlying health condition presented to the PED in extremis after weeks of progressively worsening feeding issues. The infant had been closely followed by the primary care provider (PCP) and subspecialty team via phone calls, televisits, and some office visits. Both physicians and parents had tried to resolve the feeding issues within the outpatient context, explicitly hoping to avoid potential exposure of this fragile patient to COVID-19 in the hospital. On eventual presentation to the PED, the infant was profoundly dehydrated, with significant electrolyte derangement and an acute abdomen, requiring admission to the intensive care unit. Ultimately, a new diagnosis of Hirschsprung disease was made, and the infant was hospitalized for several weeks for weight gain.

Later this summer, a school-aged child with a history of poorly controlled type 1 diabetes presented to an affiliated community hospital comatose and with Kussmaul respirations. Prior to the pandemic, a school nurse administered the child’s morning insulin. Since school closed, the patient had been responsible for administering this dose of insulin while the parents worked outside the home. Despite close and frequent communication between the patient’s endocrinology team and the family, the patient’s glucose and ketone levels began to rise. The parent administered repeated boluses of insulin at home in an attempt to avoid the perceived exposure risk associated with an ED visit. On presentation to the PED, the patient was profoundly altered, with a pH of 7.0. When transfer to a tertiary care center was recommended, the patient’s parent expressed persistent concerns about COVID-19 exposure in the larger hospital, although ultimately consent to transfer was given.

A third case from this summer provides an example of a different type of patient affected by COVID-19: the neonate whose birth circumstances were altered due to the virus. A 3-day-old, full-term infant presented to the ED with hypothermia after PCP referral. The parents had considered both home birth and hospital delivery earlier in the pregnancy, ultimately opting for home birth due to concerns about COVID-19 exposure in the hospital. The pregnancy and delivery were uncomplicated. The neonate did not receive the first hepatitis B vaccine, erythromycin eye ointment, or vitamin K after delivery. In the first 3 days of life, the patient had voided once and stooled once per day. The patient’s mother, inexperienced with breastfeeding and without access to a lactation consultant, was unsure about latch or emptying of her breasts. At the first pediatrician visit, the infant was noted to be hypothermic to 35°C, intermittently bradycardic to the 80s, and with diminished arousal. In the PED, a full sepsis work-up was initiated. Though multiple attempts were made by different providers, only a minimal amount of blood could be drawn, presumably due to dehydration. Of note, the neonate received vitamin K subcutaneously prior to lumbar puncture.

Pediatricians across the country have gone to great lengths to protect their patients and to provide high-quality care both inside and outside the office during this unprecedented time. Nevertheless, these 3 cases illustrate the detrimental effects of COVID-19 on the delivery of pediatric health care. The first 2 cases in particular demonstrate the limitations of even close and consistent phone and televisit follow-up. Telehealth has provided a lifeline for patients and families during the pandemic, and, in most cases, has provided an excellent temporary substitution for office visits. There are, however, limitations to care without physical evaluation. Had the children in the first 2 cases been evaluated in person sooner, they may have been referred to a higher level of care more expediently. Likewise, in all 3 cases, parental reservations about exposing their children to COVID-19 through a trip to the hospital, however well-intentioned, likely played a role in the eventual severity of illness with which each child presented to the hospital.

If we are encountering children in the PED with severe illness due to delayed presentation to care, what about the children we aren’t seeing? As COVID-19 cases rise daily in the United States, we must be aware of the possibility of ED avoidance. We propose a multimodal approach to combat this dangerous phenomenon. Inpatient and ED-based pediatricians must maintain clear and open lines of communication with outpatient colleagues so that we can partner in considering which cases warrant prompt ED evaluation, even in the midst of a pandemic. All pediatricians must remind families that our hospitals remain open and ready to treat children safely. We must promote community awareness of the numerous safety precautions we take every day so that patients and families can feel comfortable seeking care at the hospital; the message of ED and hospital safety must be even more robust for caregivers of our particularly vulnerable children. As always, how we communicate with patients and their families matters. Validating and addressing concerns about COVID-19 exposure, while providing reassurance about the safety of our hospitals, could save children’s lives.

Acknowledgment: Thank you to Dr. Cynthia Mollen and Dr. Kathy Shaw for their reviews of the manuscript.

Corresponding author: Regina L. Toto, MD, Department of Pediatrics, The Children’s Hospital of Philadelphia, 3401 Civic Center Blvd., Philadelphia, PA 19104; [email protected].

Financial disclosures: None.

Keywords: coronavirus; pediatric; children; access to care; emergency department.