Hospital Medicine

There is growing evidence that gender may be associated with COVID-19 infection, presentation, and prognosis.^1-4 Most published evidence, however, has focused on individual aspects, such as specific symptoms or prognoses. We sought to provide a comprehensive analysis of gender and COVID-19 infection from admission to 30 days after discharge in a large, multinational cohort.

The registry HOPE-COVID-19 (Health Outcome Predictive Evaluation for COVID-19, NCT04334291) is an international investigator-initiated study.⁵ The study was approved by the ethics committee of the promoting center and was appraised and accepted by the institutional review board or local committee of each participating hospital. It was designed as an ambispective cohort study. Patients are eligible for enrollment when discharged (whether dead or alive) after an in-hospital admission with a positive COVID-19 test or if their attending physician considered them highly likely to have presented with SARS-CoV-2 infection. All decisions and clinical procedures were performed by the attending physician team independently of this study, following the local regular practice and protocols. The information presented here corresponds to the HOPE-COVID-19 Registry, with a cutoff date of April 18, 2020.

Study methods and definitions are available in Appendix 1 and Appendix 2, respectively, and detailed in a previous paper⁵ and online on the web page of the study.⁶

Enrolled patients were divided into two groups according to their gender, then propensity score matching (PSM) analysis was performed (1:1 nearest neighbor matching, caliper = 0.01, without replacement and maximizing execution performance). Our primary end point was all-cause mortality at 30 days. Other clinically relevant events were recorded as secondary end points: invasive mechanical ventilation, noninvasive mechanical ventilation, pronation, respiratory insufficiency, heart failure, renal failure, upper respiratory tract involvement, pneumonia, sepsis, systemic inflammatory response syndrome, clinically relevant bleeding, hemoptysis, and embolic events. Events were allocated based on HOPE-COVID-19 registry definitions, following local researchers’ criteria. Abnormal blood test values were classified according to the reference values of local laboratories (Appendix 2).

Statistical analysis methods are outlined in Appendix 1.

Of the 2,798 patients consecutively enrolled in the HOPE registry, 1,111 were women (39.7%) and 1,687 were men (60.3%). Of the 2,375 (84.9%) patients who had a nasopharyngeal swab positive for COVID-19, 962 were women and 1,413 were men. Among the 2,798 patients initially included in the analysis, 876 gender-balanced pairs were selected after PSM.

Baseline Characteristics and Clinical Presentation

The baseline characteristics and clinical presentation of the overall population included in the study are summarized in Appendix Table 1. In the raw population, men had a significantly higher prevalence of conventional cardiovascular risk factors, such as diabetes, dyslipidemia, and smoking history, as well as a history of lung and cardiovascular diseases. On presentation, the most common symptoms for all patients were fever, cough, and dyspnea. Fever was more common in men, whereas vomiting, diarrhea, and upper airway symptoms (eg, sore throat, hyposmia/anosmia, dysgeusia) were more common in women.

Most patients had increased values of acute phase reactants. C-reactive protein (CRP) was elevated in 90.2% and D-dimer in 64.2% of patients, both significantly more often in men. Lymphocytopenia was present in 75.4% of patients, more commonly among men. Bilateral pneumonia occurred in 69.2% of the population, more frequently in men.

After PSM analysis (Appendix Table 2), a higher prevalence of hyposmia/anosmia and gastrointestinal symptoms in women was confirmed, as well as a higher prevalence of fever in men. Laboratory tests in men still presented alterations consistent with a more severe COVID-19 infection (significantly higher CRP, troponin, transaminases, lymphocytopenia, thrombocytopenia, and ferritin). There was no significant difference in the time between onset of symptoms and hospital admission by gender (6.2 ± 7.1 days in women vs 5.9 ± 7.6 days in men; P = .472).

The main findings after PSM analysis are summarized in Appendix Figure 1 and Appendix Figure 2.

In-Hospital Management and Outcomes

The supportive and pharmacologic treatments of study patients and their outcomes are summarized in Appendix Table 3. During the in-hospital stay, men required oxygen supplementation more frequently than women. Noninvasive mechanical ventilation, invasive mechanical ventilation, and pronation were more commonly used in men. Chloroquine/hydroxychloroquine, antivirals, and antibiotics were the medications most widely used in our population (84.5%, 65.8%, and 74.4% of patients, respectively), without significant differences between male and female patients, with the exception of antibiotics, which were used more often in men (76.6% vs 71.1%). Immunomodulators (corticosteroids, tocilizumab, and interferon) were used more often in male patients.

After PSM (Table), men more frequently received immunomodulators (corticosteroids and tocilizumab), antibiotics, and pronation. No differences in invasive and noninvasive mechanical ventilation were observed.

Thirty-day outcome data were available for all patients included in the analysis. During the in-hospital stay, 48% of patients developed respiratory insufficiency, 18.8% systemic inflammatory response syndrome (SIRS), and 13.2% overt sepsis. Respiratory insufficiency and SIRS were more common in male patients. Mortality at 30 days in the raw population was 21.4%, and men died more often than women (23.5% vs 18.2%; P = .001).

The PSM analysis continued to show a higher 30-day mortality rate among men (Figure), as well as greater need for oxygen, pronation, and use of immunomodulators and antibiotics (Table).

The results of our study confirm that among patients with COVID-19, men have a poorer prognosis than women. Because of the design of the study, it is not possible to determine if men are more prone to SARS-CoV-2 infection in our population; however, given the prevalence of men in our unselected, all-comers population, we can assume that men are either infected more often and/or more frequently symptomatic.

After PSM analysis, the 30-day all-cause mortality remained higher among men than women. The poorer prognosis of male patients is attributable not only to a higher burden of cardiovascular risk factors, but may also be related to unmodifiable biological factors, such as sex differences in angiotensin-converting enzyme 2 expression.^7,8 The worse prognosis observed in our study confirms the higher incidence of death in male patients that was observed in previous studies.⁹ Liu et al questioned the role of gender as an independent prognostic factor in COVID-19¹⁰; however, that study included fewer patients, who were also younger and had less severe disease.

The clinical presentation of COVID-19 also differed by gender in our study. Gastrointestinal symptoms and hyposmia/anosmia were more common in women, whereas fever was more common in men. The prevalence of olfactory and gustatory dysfunction in women has already been described,^11,12 and these symptoms have been linked with milder disease.¹³ It is possible that women presenting to the hospital had milder forms of COVID-19, or that there were systematic differences in how men and women sought medical care. The results of our study emphasize the need for a high level of suspicion for COVID-19 infection in women, even in the presence of mild mucosal or gastrointestinal symptoms and/or relatively minor laboratory abnormalities.

Laboratory values indicative of more severe COVID-19 infection in men could suggest a higher inflammatory response to the infection. Men also received more immunomodulators and antibiotics in this study. A recent paper from Scully et al¹⁴ pointed out the different immune response to viruses observed in men that could partially explain the higher level of inflammation markers and the more severe disease observed in men.

Our study has several limitations. As an observational study of hospitalized patients, it may represent patients with more severe COVID-19. Men and women may have sought hospital care differently. Diagnosis, testing, and treatment were not standardized and may have been influenced by patient gender. Although we attempted to match patients on baseline medical conditions, we may not have completely controlled for differences in preexisting health. Finally, gender data were collected as binary and so did not capture other gender categories.

In our multicenter cohort of hospitalized COVID-19 patients, men had a higher burden of risk factors; different clinical presentations, with more fever and less olfactory and gastrointestinal symptoms; and a significantly poorer prognosis than women did at 30 days.

The authors thank Cardiovascular Excellence SL for their essential support regarding the database and HOPE web page as well as all HOPE researchers. The authors also thank Michael Andrews for his valuable contribution to the English revision.

There is growing evidence that gender may be associated with COVID-19 infection, presentation, and prognosis.^1-4 Most published evidence, however, has focused on individual aspects, such as specific symptoms or prognoses. We sought to provide a comprehensive analysis of gender and COVID-19 infection from admission to 30 days after discharge in a large, multinational cohort.

The registry HOPE-COVID-19 (Health Outcome Predictive Evaluation for COVID-19, NCT04334291) is an international investigator-initiated study.⁵ The study was approved by the ethics committee of the promoting center and was appraised and accepted by the institutional review board or local committee of each participating hospital. It was designed as an ambispective cohort study. Patients are eligible for enrollment when discharged (whether dead or alive) after an in-hospital admission with a positive COVID-19 test or if their attending physician considered them highly likely to have presented with SARS-CoV-2 infection. All decisions and clinical procedures were performed by the attending physician team independently of this study, following the local regular practice and protocols. The information presented here corresponds to the HOPE-COVID-19 Registry, with a cutoff date of April 18, 2020.

Study methods and definitions are available in Appendix 1 and Appendix 2, respectively, and detailed in a previous paper⁵ and online on the web page of the study.⁶

Enrolled patients were divided into two groups according to their gender, then propensity score matching (PSM) analysis was performed (1:1 nearest neighbor matching, caliper = 0.01, without replacement and maximizing execution performance). Our primary end point was all-cause mortality at 30 days. Other clinically relevant events were recorded as secondary end points: invasive mechanical ventilation, noninvasive mechanical ventilation, pronation, respiratory insufficiency, heart failure, renal failure, upper respiratory tract involvement, pneumonia, sepsis, systemic inflammatory response syndrome, clinically relevant bleeding, hemoptysis, and embolic events. Events were allocated based on HOPE-COVID-19 registry definitions, following local researchers’ criteria. Abnormal blood test values were classified according to the reference values of local laboratories (Appendix 2).

Statistical analysis methods are outlined in Appendix 1.

Of the 2,798 patients consecutively enrolled in the HOPE registry, 1,111 were women (39.7%) and 1,687 were men (60.3%). Of the 2,375 (84.9%) patients who had a nasopharyngeal swab positive for COVID-19, 962 were women and 1,413 were men. Among the 2,798 patients initially included in the analysis, 876 gender-balanced pairs were selected after PSM.

Baseline Characteristics and Clinical Presentation

The baseline characteristics and clinical presentation of the overall population included in the study are summarized in Appendix Table 1. In the raw population, men had a significantly higher prevalence of conventional cardiovascular risk factors, such as diabetes, dyslipidemia, and smoking history, as well as a history of lung and cardiovascular diseases. On presentation, the most common symptoms for all patients were fever, cough, and dyspnea. Fever was more common in men, whereas vomiting, diarrhea, and upper airway symptoms (eg, sore throat, hyposmia/anosmia, dysgeusia) were more common in women.

Most patients had increased values of acute phase reactants. C-reactive protein (CRP) was elevated in 90.2% and D-dimer in 64.2% of patients, both significantly more often in men. Lymphocytopenia was present in 75.4% of patients, more commonly among men. Bilateral pneumonia occurred in 69.2% of the population, more frequently in men.

After PSM analysis (Appendix Table 2), a higher prevalence of hyposmia/anosmia and gastrointestinal symptoms in women was confirmed, as well as a higher prevalence of fever in men. Laboratory tests in men still presented alterations consistent with a more severe COVID-19 infection (significantly higher CRP, troponin, transaminases, lymphocytopenia, thrombocytopenia, and ferritin). There was no significant difference in the time between onset of symptoms and hospital admission by gender (6.2 ± 7.1 days in women vs 5.9 ± 7.6 days in men; P = .472).

The main findings after PSM analysis are summarized in Appendix Figure 1 and Appendix Figure 2.

In-Hospital Management and Outcomes

The supportive and pharmacologic treatments of study patients and their outcomes are summarized in Appendix Table 3. During the in-hospital stay, men required oxygen supplementation more frequently than women. Noninvasive mechanical ventilation, invasive mechanical ventilation, and pronation were more commonly used in men. Chloroquine/hydroxychloroquine, antivirals, and antibiotics were the medications most widely used in our population (84.5%, 65.8%, and 74.4% of patients, respectively), without significant differences between male and female patients, with the exception of antibiotics, which were used more often in men (76.6% vs 71.1%). Immunomodulators (corticosteroids, tocilizumab, and interferon) were used more often in male patients.

After PSM (Table), men more frequently received immunomodulators (corticosteroids and tocilizumab), antibiotics, and pronation. No differences in invasive and noninvasive mechanical ventilation were observed.

Thirty-day outcome data were available for all patients included in the analysis. During the in-hospital stay, 48% of patients developed respiratory insufficiency, 18.8% systemic inflammatory response syndrome (SIRS), and 13.2% overt sepsis. Respiratory insufficiency and SIRS were more common in male patients. Mortality at 30 days in the raw population was 21.4%, and men died more often than women (23.5% vs 18.2%; P = .001).

The PSM analysis continued to show a higher 30-day mortality rate among men (Figure), as well as greater need for oxygen, pronation, and use of immunomodulators and antibiotics (Table).

The results of our study confirm that among patients with COVID-19, men have a poorer prognosis than women. Because of the design of the study, it is not possible to determine if men are more prone to SARS-CoV-2 infection in our population; however, given the prevalence of men in our unselected, all-comers population, we can assume that men are either infected more often and/or more frequently symptomatic.

After PSM analysis, the 30-day all-cause mortality remained higher among men than women. The poorer prognosis of male patients is attributable not only to a higher burden of cardiovascular risk factors, but may also be related to unmodifiable biological factors, such as sex differences in angiotensin-converting enzyme 2 expression.^7,8 The worse prognosis observed in our study confirms the higher incidence of death in male patients that was observed in previous studies.⁹ Liu et al questioned the role of gender as an independent prognostic factor in COVID-19¹⁰; however, that study included fewer patients, who were also younger and had less severe disease.

The clinical presentation of COVID-19 also differed by gender in our study. Gastrointestinal symptoms and hyposmia/anosmia were more common in women, whereas fever was more common in men. The prevalence of olfactory and gustatory dysfunction in women has already been described,^11,12 and these symptoms have been linked with milder disease.¹³ It is possible that women presenting to the hospital had milder forms of COVID-19, or that there were systematic differences in how men and women sought medical care. The results of our study emphasize the need for a high level of suspicion for COVID-19 infection in women, even in the presence of mild mucosal or gastrointestinal symptoms and/or relatively minor laboratory abnormalities.

Laboratory values indicative of more severe COVID-19 infection in men could suggest a higher inflammatory response to the infection. Men also received more immunomodulators and antibiotics in this study. A recent paper from Scully et al¹⁴ pointed out the different immune response to viruses observed in men that could partially explain the higher level of inflammation markers and the more severe disease observed in men.

Our study has several limitations. As an observational study of hospitalized patients, it may represent patients with more severe COVID-19. Men and women may have sought hospital care differently. Diagnosis, testing, and treatment were not standardized and may have been influenced by patient gender. Although we attempted to match patients on baseline medical conditions, we may not have completely controlled for differences in preexisting health. Finally, gender data were collected as binary and so did not capture other gender categories.

In our multicenter cohort of hospitalized COVID-19 patients, men had a higher burden of risk factors; different clinical presentations, with more fever and less olfactory and gastrointestinal symptoms; and a significantly poorer prognosis than women did at 30 days.

The authors thank Cardiovascular Excellence SL for their essential support regarding the database and HOPE web page as well as all HOPE researchers. The authors also thank Michael Andrews for his valuable contribution to the English revision.

There is growing evidence that gender may be associated with COVID-19 infection, presentation, and prognosis.^1-4 Most published evidence, however, has focused on individual aspects, such as specific symptoms or prognoses. We sought to provide a comprehensive analysis of gender and COVID-19 infection from admission to 30 days after discharge in a large, multinational cohort.

The registry HOPE-COVID-19 (Health Outcome Predictive Evaluation for COVID-19, NCT04334291) is an international investigator-initiated study.⁵ The study was approved by the ethics committee of the promoting center and was appraised and accepted by the institutional review board or local committee of each participating hospital. It was designed as an ambispective cohort study. Patients are eligible for enrollment when discharged (whether dead or alive) after an in-hospital admission with a positive COVID-19 test or if their attending physician considered them highly likely to have presented with SARS-CoV-2 infection. All decisions and clinical procedures were performed by the attending physician team independently of this study, following the local regular practice and protocols. The information presented here corresponds to the HOPE-COVID-19 Registry, with a cutoff date of April 18, 2020.

Study methods and definitions are available in Appendix 1 and Appendix 2, respectively, and detailed in a previous paper⁵ and online on the web page of the study.⁶

Enrolled patients were divided into two groups according to their gender, then propensity score matching (PSM) analysis was performed (1:1 nearest neighbor matching, caliper = 0.01, without replacement and maximizing execution performance). Our primary end point was all-cause mortality at 30 days. Other clinically relevant events were recorded as secondary end points: invasive mechanical ventilation, noninvasive mechanical ventilation, pronation, respiratory insufficiency, heart failure, renal failure, upper respiratory tract involvement, pneumonia, sepsis, systemic inflammatory response syndrome, clinically relevant bleeding, hemoptysis, and embolic events. Events were allocated based on HOPE-COVID-19 registry definitions, following local researchers’ criteria. Abnormal blood test values were classified according to the reference values of local laboratories (Appendix 2).

Statistical analysis methods are outlined in Appendix 1.

Of the 2,798 patients consecutively enrolled in the HOPE registry, 1,111 were women (39.7%) and 1,687 were men (60.3%). Of the 2,375 (84.9%) patients who had a nasopharyngeal swab positive for COVID-19, 962 were women and 1,413 were men. Among the 2,798 patients initially included in the analysis, 876 gender-balanced pairs were selected after PSM.

Baseline Characteristics and Clinical Presentation

The baseline characteristics and clinical presentation of the overall population included in the study are summarized in Appendix Table 1. In the raw population, men had a significantly higher prevalence of conventional cardiovascular risk factors, such as diabetes, dyslipidemia, and smoking history, as well as a history of lung and cardiovascular diseases. On presentation, the most common symptoms for all patients were fever, cough, and dyspnea. Fever was more common in men, whereas vomiting, diarrhea, and upper airway symptoms (eg, sore throat, hyposmia/anosmia, dysgeusia) were more common in women.

Most patients had increased values of acute phase reactants. C-reactive protein (CRP) was elevated in 90.2% and D-dimer in 64.2% of patients, both significantly more often in men. Lymphocytopenia was present in 75.4% of patients, more commonly among men. Bilateral pneumonia occurred in 69.2% of the population, more frequently in men.

After PSM analysis (Appendix Table 2), a higher prevalence of hyposmia/anosmia and gastrointestinal symptoms in women was confirmed, as well as a higher prevalence of fever in men. Laboratory tests in men still presented alterations consistent with a more severe COVID-19 infection (significantly higher CRP, troponin, transaminases, lymphocytopenia, thrombocytopenia, and ferritin). There was no significant difference in the time between onset of symptoms and hospital admission by gender (6.2 ± 7.1 days in women vs 5.9 ± 7.6 days in men; P = .472).

The main findings after PSM analysis are summarized in Appendix Figure 1 and Appendix Figure 2.

In-Hospital Management and Outcomes

The supportive and pharmacologic treatments of study patients and their outcomes are summarized in Appendix Table 3. During the in-hospital stay, men required oxygen supplementation more frequently than women. Noninvasive mechanical ventilation, invasive mechanical ventilation, and pronation were more commonly used in men. Chloroquine/hydroxychloroquine, antivirals, and antibiotics were the medications most widely used in our population (84.5%, 65.8%, and 74.4% of patients, respectively), without significant differences between male and female patients, with the exception of antibiotics, which were used more often in men (76.6% vs 71.1%). Immunomodulators (corticosteroids, tocilizumab, and interferon) were used more often in male patients.

After PSM (Table), men more frequently received immunomodulators (corticosteroids and tocilizumab), antibiotics, and pronation. No differences in invasive and noninvasive mechanical ventilation were observed.

Thirty-day outcome data were available for all patients included in the analysis. During the in-hospital stay, 48% of patients developed respiratory insufficiency, 18.8% systemic inflammatory response syndrome (SIRS), and 13.2% overt sepsis. Respiratory insufficiency and SIRS were more common in male patients. Mortality at 30 days in the raw population was 21.4%, and men died more often than women (23.5% vs 18.2%; P = .001).

The PSM analysis continued to show a higher 30-day mortality rate among men (Figure), as well as greater need for oxygen, pronation, and use of immunomodulators and antibiotics (Table).

The results of our study confirm that among patients with COVID-19, men have a poorer prognosis than women. Because of the design of the study, it is not possible to determine if men are more prone to SARS-CoV-2 infection in our population; however, given the prevalence of men in our unselected, all-comers population, we can assume that men are either infected more often and/or more frequently symptomatic.

After PSM analysis, the 30-day all-cause mortality remained higher among men than women. The poorer prognosis of male patients is attributable not only to a higher burden of cardiovascular risk factors, but may also be related to unmodifiable biological factors, such as sex differences in angiotensin-converting enzyme 2 expression.^7,8 The worse prognosis observed in our study confirms the higher incidence of death in male patients that was observed in previous studies.⁹ Liu et al questioned the role of gender as an independent prognostic factor in COVID-19¹⁰; however, that study included fewer patients, who were also younger and had less severe disease.

The clinical presentation of COVID-19 also differed by gender in our study. Gastrointestinal symptoms and hyposmia/anosmia were more common in women, whereas fever was more common in men. The prevalence of olfactory and gustatory dysfunction in women has already been described,^11,12 and these symptoms have been linked with milder disease.¹³ It is possible that women presenting to the hospital had milder forms of COVID-19, or that there were systematic differences in how men and women sought medical care. The results of our study emphasize the need for a high level of suspicion for COVID-19 infection in women, even in the presence of mild mucosal or gastrointestinal symptoms and/or relatively minor laboratory abnormalities.

Laboratory values indicative of more severe COVID-19 infection in men could suggest a higher inflammatory response to the infection. Men also received more immunomodulators and antibiotics in this study. A recent paper from Scully et al¹⁴ pointed out the different immune response to viruses observed in men that could partially explain the higher level of inflammation markers and the more severe disease observed in men.

Our study has several limitations. As an observational study of hospitalized patients, it may represent patients with more severe COVID-19. Men and women may have sought hospital care differently. Diagnosis, testing, and treatment were not standardized and may have been influenced by patient gender. Although we attempted to match patients on baseline medical conditions, we may not have completely controlled for differences in preexisting health. Finally, gender data were collected as binary and so did not capture other gender categories.

In our multicenter cohort of hospitalized COVID-19 patients, men had a higher burden of risk factors; different clinical presentations, with more fever and less olfactory and gastrointestinal symptoms; and a significantly poorer prognosis than women did at 30 days.

The authors thank Cardiovascular Excellence SL for their essential support regarding the database and HOPE web page as well as all HOPE researchers. The authors also thank Michael Andrews for his valuable contribution to the English revision.

The COVID-19 pandemic has disrupted the educational experience of medical trainees around the world, and this has been especially true for those in New York City (NYC), the early epicenter of the global outbreak.¹ The pandemic’s surge required redeployment of trainees away from scheduled rotations, focused didactics around emerging COVID-19 data, and seemingly narrowed trainees’ clinical exposure to a single respiratory infection.

While there is a small body of literature describing the programmatic responses^2,3 and educational adaptations^4-7 that have come about as a result of the pandemic’s disruptive force, a characterization of exactly how trainees’ clinical experiences have been affected is lacking. A detailed understanding of how trainees’ inpatient care activities evolved during the pandemic could provide valuable practice habits feedback, allow for comparisons across training sites, focus content selection for didactic learning and self-study, and potentially help forecast similar clinical changes in the event of a subsequent wave. Perhaps most important, as internal medicine (IM) trainees require broad exposure to diverse clinical conditions to mature toward independent practice, a characterization of exactly how the pandemic has narrowed the diversity of clinical exposure could inform changes in how trainees attain clinical competence.

Profiling IM residents’ clinical experiences in a meaningful way is particularly challenging given the extraordinary breadth of the field. We recently developed a strategy by which resident-attributed International Classification of Diseases, Tenth Revision (ICD-10) principal diagnosis codes are mapped to an educational taxonomy of medical content categories, yielding clinical exposure profiles.⁸ Here, we apply this mapping strategy to all four training hospitals of a large NYC IM residency program to catalogue the evolution of clinical diversity experienced by residents during the COVID-19 pandemic.

Study Population

The NYU IM Residency Program comprises 225 resident physicians rotating at four inpatient training sites: NYU Langone Hospital–Brooklyn (NYU-BK), NYU Langone Hospitals–Manhattan (NYU-MN), Bellevue Hospital (BH), and VA–New York Harbor Healthcare (VA). The study period was defined as February 1, 2020, to May 31, 2020, to capture clinical exposure during baseline, surge, and immediate post-surge periods. The NYU IM residency program declared pandemic emergency status on March 23, 2020, after which all residents were assigned to inpatient acute care and intensive care rotations to augment the inpatient workforce.

Data Source

Clinical data at each training hospital are collected and stored, allowing for asynchronous querying. Given differences in data reporting, strategies for collecting principal ICD-10 codes of patients discharged during the study period differed slightly across sites. Principal ICD-10 codes from patients discharged from NYU-BK and NYU-MN were filtered by nursing unit, allowing selection for resident-staffed units. Principal ICD-10 codes from BH were curated by care team, allowing selection for resident-staffed teams. Principal ICD-10 codes from VA were filtered by both hospital unit and provider service to attribute to resident providers. Dates of each discharge were included, and mortalities were included as discharges. All methods yielded a dataset of principal ICD-10 discharge diagnosis codes attributed primarily to IM residents. Given the rapid changes in hospital staffing to care for increasing patient volumes, in rare circumstances residents and other providers (such as advanced practice providers) shared hospital units. While ICD-10 codes mined from each hospital are attributed primarily to residents, this attribution is not entirely exclusive. Data were analyzed both by training site and in aggregate across the four training sites. No individually identifiable data were analyzed, the primary goal of the project was to improve education, and the data were collected as part of a required aspect of training; as a result, this project met criteria for certification as a quality improvement, and not a human subject, research project.

The Crosswalk Tool

We previously developed a crosswalk tool containing 4,854 ICD-10 diagnoses uniquely mapped to 16 broad medical content areas as defined by the American Board of Internal Medicine (ABIM).⁸ Custom programs (MATLAB, MathWorks, Inc) captured and subsequently mapped resident-attributed ICD-10 discharge codes to content areas if the syntax of the ICD-10 code in question exactly matched or was nested within an ICD-10 code in the crosswalk. This tool allowed us to measure the daily discharge frequency of each content area across the sites.

Analysis

The sensitivity of the crosswalk tool was calculated as the number of ICD-10 codes captured divided by the total number of patients. Codes missed by the tool were excluded. The total number, as well as the 7-day running average of discharges per content area, across the sites during the study period were measured. To evaluate for differences in the distribution of content before and after pandemic emergency status, 2 × 16 χ² contingency tables were constructed. To evaluate for changes in the mean relative proportions (%) of each content area, paired t tests were conducted. Confidence intervals were estimated from t distributions.

There were 6,613 patients discharged from all sites (NYU-BK, 2,062; NYU-MN, 2,188; BH, 1,711; VA, 652; Appendix Table). The crosswalk tool captured 6,384 principal discharge ICD-10 codes (96.5%). The five most common content areas during the study period were infectious diseases (ID; n = 2,892), cardiovascular disease (CVD; n = 1,199), gastroenterology (n = 406), pulmonary disease (n = 372), and nephrology and urology (n = 252). These were also the content areas most frequently encountered by residents at baseline (Figure and Table). The distribution of content prior to declaration of pandemic emergency status was significantly different than that after declaration (χ² = 709; df, 15; P <.001). ID diagnoses, driven by COVID-19, rose steeply in the period following declaration, peaked in mid-April, and slowly waned in May (Figure). The mean relative percentage of ID discharges across the sites rose from 26.0% (16.5%-35.4%) at baseline to 58.3% (41.3%-75.3%) in the period after pandemic emergency status was declared (P = .005).

Frequencies of diagnoses mapping to other content areas decreased significantly, reflecting a marked tapering of clinical diversity (Figure and Table). Specifically, decreases were seen in CVD (27.6% [95% CI, 17.9%-37.2%] to 13.9% [95% CI, 5.5%-22.3%]; P = .013); gastroenterology (8.3% [95% CI, 6.2%-10.2%] to 4.6% [95% CI, 2.1%-6.9%]; P = .038); pulmonary disease (8.0% [95% CI, 5.6%-10.2%] to 4.6% [95% CI, 1.6%-7.4%]; P = .040); and nephrology and urology (4.8% [95% CI, 2.6%-6.9%] to 3.1% [95% CI, 1.9%-4.2%]; P = .047) (Table). In late April, diagnoses mapping to these content areas began to repopulate residents’ clinical experiences and by the end of the study period had nearly returned to baseline frequencies. These patterns were similar when discharge diagnoses from each training site were plotted individually (Appendix Figure).

Here, we demonstrate how the clinical educational landscape changed for our residents during the COVID-19 pandemic. We uncover a dramatic deviation in the content to which residents were exposed through patient care activities that disproportionately favored ID at the expense of all other content. We demonstrate that this reduction in clinical diversity persisted for nearly 2 months and was similar at each of our training hospitals, and also provide a trajectory on which other content repopulated residents’ clinical experiences.

These data have served several valuable purposes and support ongoing efforts to map residents’ experiential curriculum at our program and others. Sharing this data with residents, as occurred routinely in town hall forums and noon conferences, has provided them with real-time practice feedback during a time of crisis. This has provided scope for their herculean efforts during the pandemic, served as a blueprint for underrepresented content most ripe for self-study, and offered reassurance of a return to normalcy given the trajectory of clinical content curves. As practice habits feedback is an Accreditation Council for Graduate Medical Education requirement, this strategy has also served as a robust and reproducible means of complying.

Our training program used this characterization of clinical content to help guide teaching in the pandemic era. For example, we preferentially structured case conferences and other didactics around reemerging content areas to capitalize on just-in-time education and harness residents’ eagerness for a respite from COVID-specific education. Residents required to quarantine at home were provided with learning plans centered on content underrepresented in clinical practice.

Given the critical importance of experiential learning in IM residents’ training, our findings quantifying significant changes in clinical exposure could form the basis for predicting poor outcomes in competency-based assessments for residents training in the COVID era, which continues to affect our trainees. For example, our characterization of clinical exposure may predict poor in-training exam or even ABIM certification exam performance in the content areas most drastically affected. Knowledge of this association of clinical exposure and clinical competence could allow training programs like ours to preempt poor performance in competency-based assessments by more aggressively shifting lectures, simulations, and other didactic programs toward content areas underrepresented in the pandemic’s wake.

Limitations of this study include the fact that availability of testing and ICD-10 coding for COVID-19 differed slightly across training sites, potentially contributing to site differences in mapping. Additionally, given our 1:1 mapping of ICD-10 codes to content categories, our strategy attributes COVID-19 to ID alone, and does not capture additional areas germane to this diagnosis, such as pulmonary disease.

We provide a detailed characterization of the evolution of a single IM program’s patient care experiences across four training hospitals during the COVID-19 pandemic. Such characterization can be leveraged to provide effective practice habits feedback and guide teaching efforts, and could form the basis to predict competency-based outcomes for trainees in the COVID era.

The COVID-19 pandemic has disrupted the educational experience of medical trainees around the world, and this has been especially true for those in New York City (NYC), the early epicenter of the global outbreak.¹ The pandemic’s surge required redeployment of trainees away from scheduled rotations, focused didactics around emerging COVID-19 data, and seemingly narrowed trainees’ clinical exposure to a single respiratory infection.

While there is a small body of literature describing the programmatic responses^2,3 and educational adaptations^4-7 that have come about as a result of the pandemic’s disruptive force, a characterization of exactly how trainees’ clinical experiences have been affected is lacking. A detailed understanding of how trainees’ inpatient care activities evolved during the pandemic could provide valuable practice habits feedback, allow for comparisons across training sites, focus content selection for didactic learning and self-study, and potentially help forecast similar clinical changes in the event of a subsequent wave. Perhaps most important, as internal medicine (IM) trainees require broad exposure to diverse clinical conditions to mature toward independent practice, a characterization of exactly how the pandemic has narrowed the diversity of clinical exposure could inform changes in how trainees attain clinical competence.

Profiling IM residents’ clinical experiences in a meaningful way is particularly challenging given the extraordinary breadth of the field. We recently developed a strategy by which resident-attributed International Classification of Diseases, Tenth Revision (ICD-10) principal diagnosis codes are mapped to an educational taxonomy of medical content categories, yielding clinical exposure profiles.⁸ Here, we apply this mapping strategy to all four training hospitals of a large NYC IM residency program to catalogue the evolution of clinical diversity experienced by residents during the COVID-19 pandemic.

Study Population

The NYU IM Residency Program comprises 225 resident physicians rotating at four inpatient training sites: NYU Langone Hospital–Brooklyn (NYU-BK), NYU Langone Hospitals–Manhattan (NYU-MN), Bellevue Hospital (BH), and VA–New York Harbor Healthcare (VA). The study period was defined as February 1, 2020, to May 31, 2020, to capture clinical exposure during baseline, surge, and immediate post-surge periods. The NYU IM residency program declared pandemic emergency status on March 23, 2020, after which all residents were assigned to inpatient acute care and intensive care rotations to augment the inpatient workforce.

Data Source

Clinical data at each training hospital are collected and stored, allowing for asynchronous querying. Given differences in data reporting, strategies for collecting principal ICD-10 codes of patients discharged during the study period differed slightly across sites. Principal ICD-10 codes from patients discharged from NYU-BK and NYU-MN were filtered by nursing unit, allowing selection for resident-staffed units. Principal ICD-10 codes from BH were curated by care team, allowing selection for resident-staffed teams. Principal ICD-10 codes from VA were filtered by both hospital unit and provider service to attribute to resident providers. Dates of each discharge were included, and mortalities were included as discharges. All methods yielded a dataset of principal ICD-10 discharge diagnosis codes attributed primarily to IM residents. Given the rapid changes in hospital staffing to care for increasing patient volumes, in rare circumstances residents and other providers (such as advanced practice providers) shared hospital units. While ICD-10 codes mined from each hospital are attributed primarily to residents, this attribution is not entirely exclusive. Data were analyzed both by training site and in aggregate across the four training sites. No individually identifiable data were analyzed, the primary goal of the project was to improve education, and the data were collected as part of a required aspect of training; as a result, this project met criteria for certification as a quality improvement, and not a human subject, research project.

The Crosswalk Tool

We previously developed a crosswalk tool containing 4,854 ICD-10 diagnoses uniquely mapped to 16 broad medical content areas as defined by the American Board of Internal Medicine (ABIM).⁸ Custom programs (MATLAB, MathWorks, Inc) captured and subsequently mapped resident-attributed ICD-10 discharge codes to content areas if the syntax of the ICD-10 code in question exactly matched or was nested within an ICD-10 code in the crosswalk. This tool allowed us to measure the daily discharge frequency of each content area across the sites.

Analysis

The sensitivity of the crosswalk tool was calculated as the number of ICD-10 codes captured divided by the total number of patients. Codes missed by the tool were excluded. The total number, as well as the 7-day running average of discharges per content area, across the sites during the study period were measured. To evaluate for differences in the distribution of content before and after pandemic emergency status, 2 × 16 χ² contingency tables were constructed. To evaluate for changes in the mean relative proportions (%) of each content area, paired t tests were conducted. Confidence intervals were estimated from t distributions.

There were 6,613 patients discharged from all sites (NYU-BK, 2,062; NYU-MN, 2,188; BH, 1,711; VA, 652; Appendix Table). The crosswalk tool captured 6,384 principal discharge ICD-10 codes (96.5%). The five most common content areas during the study period were infectious diseases (ID; n = 2,892), cardiovascular disease (CVD; n = 1,199), gastroenterology (n = 406), pulmonary disease (n = 372), and nephrology and urology (n = 252). These were also the content areas most frequently encountered by residents at baseline (Figure and Table). The distribution of content prior to declaration of pandemic emergency status was significantly different than that after declaration (χ² = 709; df, 15; P <.001). ID diagnoses, driven by COVID-19, rose steeply in the period following declaration, peaked in mid-April, and slowly waned in May (Figure). The mean relative percentage of ID discharges across the sites rose from 26.0% (16.5%-35.4%) at baseline to 58.3% (41.3%-75.3%) in the period after pandemic emergency status was declared (P = .005).

Frequencies of diagnoses mapping to other content areas decreased significantly, reflecting a marked tapering of clinical diversity (Figure and Table). Specifically, decreases were seen in CVD (27.6% [95% CI, 17.9%-37.2%] to 13.9% [95% CI, 5.5%-22.3%]; P = .013); gastroenterology (8.3% [95% CI, 6.2%-10.2%] to 4.6% [95% CI, 2.1%-6.9%]; P = .038); pulmonary disease (8.0% [95% CI, 5.6%-10.2%] to 4.6% [95% CI, 1.6%-7.4%]; P = .040); and nephrology and urology (4.8% [95% CI, 2.6%-6.9%] to 3.1% [95% CI, 1.9%-4.2%]; P = .047) (Table). In late April, diagnoses mapping to these content areas began to repopulate residents’ clinical experiences and by the end of the study period had nearly returned to baseline frequencies. These patterns were similar when discharge diagnoses from each training site were plotted individually (Appendix Figure).

Here, we demonstrate how the clinical educational landscape changed for our residents during the COVID-19 pandemic. We uncover a dramatic deviation in the content to which residents were exposed through patient care activities that disproportionately favored ID at the expense of all other content. We demonstrate that this reduction in clinical diversity persisted for nearly 2 months and was similar at each of our training hospitals, and also provide a trajectory on which other content repopulated residents’ clinical experiences.

These data have served several valuable purposes and support ongoing efforts to map residents’ experiential curriculum at our program and others. Sharing this data with residents, as occurred routinely in town hall forums and noon conferences, has provided them with real-time practice feedback during a time of crisis. This has provided scope for their herculean efforts during the pandemic, served as a blueprint for underrepresented content most ripe for self-study, and offered reassurance of a return to normalcy given the trajectory of clinical content curves. As practice habits feedback is an Accreditation Council for Graduate Medical Education requirement, this strategy has also served as a robust and reproducible means of complying.

Our training program used this characterization of clinical content to help guide teaching in the pandemic era. For example, we preferentially structured case conferences and other didactics around reemerging content areas to capitalize on just-in-time education and harness residents’ eagerness for a respite from COVID-specific education. Residents required to quarantine at home were provided with learning plans centered on content underrepresented in clinical practice.

Given the critical importance of experiential learning in IM residents’ training, our findings quantifying significant changes in clinical exposure could form the basis for predicting poor outcomes in competency-based assessments for residents training in the COVID era, which continues to affect our trainees. For example, our characterization of clinical exposure may predict poor in-training exam or even ABIM certification exam performance in the content areas most drastically affected. Knowledge of this association of clinical exposure and clinical competence could allow training programs like ours to preempt poor performance in competency-based assessments by more aggressively shifting lectures, simulations, and other didactic programs toward content areas underrepresented in the pandemic’s wake.

Limitations of this study include the fact that availability of testing and ICD-10 coding for COVID-19 differed slightly across training sites, potentially contributing to site differences in mapping. Additionally, given our 1:1 mapping of ICD-10 codes to content categories, our strategy attributes COVID-19 to ID alone, and does not capture additional areas germane to this diagnosis, such as pulmonary disease.

We provide a detailed characterization of the evolution of a single IM program’s patient care experiences across four training hospitals during the COVID-19 pandemic. Such characterization can be leveraged to provide effective practice habits feedback and guide teaching efforts, and could form the basis to predict competency-based outcomes for trainees in the COVID era.

The COVID-19 pandemic has disrupted the educational experience of medical trainees around the world, and this has been especially true for those in New York City (NYC), the early epicenter of the global outbreak.¹ The pandemic’s surge required redeployment of trainees away from scheduled rotations, focused didactics around emerging COVID-19 data, and seemingly narrowed trainees’ clinical exposure to a single respiratory infection.

While there is a small body of literature describing the programmatic responses^2,3 and educational adaptations^4-7 that have come about as a result of the pandemic’s disruptive force, a characterization of exactly how trainees’ clinical experiences have been affected is lacking. A detailed understanding of how trainees’ inpatient care activities evolved during the pandemic could provide valuable practice habits feedback, allow for comparisons across training sites, focus content selection for didactic learning and self-study, and potentially help forecast similar clinical changes in the event of a subsequent wave. Perhaps most important, as internal medicine (IM) trainees require broad exposure to diverse clinical conditions to mature toward independent practice, a characterization of exactly how the pandemic has narrowed the diversity of clinical exposure could inform changes in how trainees attain clinical competence.

Profiling IM residents’ clinical experiences in a meaningful way is particularly challenging given the extraordinary breadth of the field. We recently developed a strategy by which resident-attributed International Classification of Diseases, Tenth Revision (ICD-10) principal diagnosis codes are mapped to an educational taxonomy of medical content categories, yielding clinical exposure profiles.⁸ Here, we apply this mapping strategy to all four training hospitals of a large NYC IM residency program to catalogue the evolution of clinical diversity experienced by residents during the COVID-19 pandemic.

Study Population

The NYU IM Residency Program comprises 225 resident physicians rotating at four inpatient training sites: NYU Langone Hospital–Brooklyn (NYU-BK), NYU Langone Hospitals–Manhattan (NYU-MN), Bellevue Hospital (BH), and VA–New York Harbor Healthcare (VA). The study period was defined as February 1, 2020, to May 31, 2020, to capture clinical exposure during baseline, surge, and immediate post-surge periods. The NYU IM residency program declared pandemic emergency status on March 23, 2020, after which all residents were assigned to inpatient acute care and intensive care rotations to augment the inpatient workforce.

Data Source

Clinical data at each training hospital are collected and stored, allowing for asynchronous querying. Given differences in data reporting, strategies for collecting principal ICD-10 codes of patients discharged during the study period differed slightly across sites. Principal ICD-10 codes from patients discharged from NYU-BK and NYU-MN were filtered by nursing unit, allowing selection for resident-staffed units. Principal ICD-10 codes from BH were curated by care team, allowing selection for resident-staffed teams. Principal ICD-10 codes from VA were filtered by both hospital unit and provider service to attribute to resident providers. Dates of each discharge were included, and mortalities were included as discharges. All methods yielded a dataset of principal ICD-10 discharge diagnosis codes attributed primarily to IM residents. Given the rapid changes in hospital staffing to care for increasing patient volumes, in rare circumstances residents and other providers (such as advanced practice providers) shared hospital units. While ICD-10 codes mined from each hospital are attributed primarily to residents, this attribution is not entirely exclusive. Data were analyzed both by training site and in aggregate across the four training sites. No individually identifiable data were analyzed, the primary goal of the project was to improve education, and the data were collected as part of a required aspect of training; as a result, this project met criteria for certification as a quality improvement, and not a human subject, research project.

The Crosswalk Tool

We previously developed a crosswalk tool containing 4,854 ICD-10 diagnoses uniquely mapped to 16 broad medical content areas as defined by the American Board of Internal Medicine (ABIM).⁸ Custom programs (MATLAB, MathWorks, Inc) captured and subsequently mapped resident-attributed ICD-10 discharge codes to content areas if the syntax of the ICD-10 code in question exactly matched or was nested within an ICD-10 code in the crosswalk. This tool allowed us to measure the daily discharge frequency of each content area across the sites.

Analysis

The sensitivity of the crosswalk tool was calculated as the number of ICD-10 codes captured divided by the total number of patients. Codes missed by the tool were excluded. The total number, as well as the 7-day running average of discharges per content area, across the sites during the study period were measured. To evaluate for differences in the distribution of content before and after pandemic emergency status, 2 × 16 χ² contingency tables were constructed. To evaluate for changes in the mean relative proportions (%) of each content area, paired t tests were conducted. Confidence intervals were estimated from t distributions.

There were 6,613 patients discharged from all sites (NYU-BK, 2,062; NYU-MN, 2,188; BH, 1,711; VA, 652; Appendix Table). The crosswalk tool captured 6,384 principal discharge ICD-10 codes (96.5%). The five most common content areas during the study period were infectious diseases (ID; n = 2,892), cardiovascular disease (CVD; n = 1,199), gastroenterology (n = 406), pulmonary disease (n = 372), and nephrology and urology (n = 252). These were also the content areas most frequently encountered by residents at baseline (Figure and Table). The distribution of content prior to declaration of pandemic emergency status was significantly different than that after declaration (χ² = 709; df, 15; P <.001). ID diagnoses, driven by COVID-19, rose steeply in the period following declaration, peaked in mid-April, and slowly waned in May (Figure). The mean relative percentage of ID discharges across the sites rose from 26.0% (16.5%-35.4%) at baseline to 58.3% (41.3%-75.3%) in the period after pandemic emergency status was declared (P = .005).

Frequencies of diagnoses mapping to other content areas decreased significantly, reflecting a marked tapering of clinical diversity (Figure and Table). Specifically, decreases were seen in CVD (27.6% [95% CI, 17.9%-37.2%] to 13.9% [95% CI, 5.5%-22.3%]; P = .013); gastroenterology (8.3% [95% CI, 6.2%-10.2%] to 4.6% [95% CI, 2.1%-6.9%]; P = .038); pulmonary disease (8.0% [95% CI, 5.6%-10.2%] to 4.6% [95% CI, 1.6%-7.4%]; P = .040); and nephrology and urology (4.8% [95% CI, 2.6%-6.9%] to 3.1% [95% CI, 1.9%-4.2%]; P = .047) (Table). In late April, diagnoses mapping to these content areas began to repopulate residents’ clinical experiences and by the end of the study period had nearly returned to baseline frequencies. These patterns were similar when discharge diagnoses from each training site were plotted individually (Appendix Figure).

Here, we demonstrate how the clinical educational landscape changed for our residents during the COVID-19 pandemic. We uncover a dramatic deviation in the content to which residents were exposed through patient care activities that disproportionately favored ID at the expense of all other content. We demonstrate that this reduction in clinical diversity persisted for nearly 2 months and was similar at each of our training hospitals, and also provide a trajectory on which other content repopulated residents’ clinical experiences.

These data have served several valuable purposes and support ongoing efforts to map residents’ experiential curriculum at our program and others. Sharing this data with residents, as occurred routinely in town hall forums and noon conferences, has provided them with real-time practice feedback during a time of crisis. This has provided scope for their herculean efforts during the pandemic, served as a blueprint for underrepresented content most ripe for self-study, and offered reassurance of a return to normalcy given the trajectory of clinical content curves. As practice habits feedback is an Accreditation Council for Graduate Medical Education requirement, this strategy has also served as a robust and reproducible means of complying.

Our training program used this characterization of clinical content to help guide teaching in the pandemic era. For example, we preferentially structured case conferences and other didactics around reemerging content areas to capitalize on just-in-time education and harness residents’ eagerness for a respite from COVID-specific education. Residents required to quarantine at home were provided with learning plans centered on content underrepresented in clinical practice.

Given the critical importance of experiential learning in IM residents’ training, our findings quantifying significant changes in clinical exposure could form the basis for predicting poor outcomes in competency-based assessments for residents training in the COVID era, which continues to affect our trainees. For example, our characterization of clinical exposure may predict poor in-training exam or even ABIM certification exam performance in the content areas most drastically affected. Knowledge of this association of clinical exposure and clinical competence could allow training programs like ours to preempt poor performance in competency-based assessments by more aggressively shifting lectures, simulations, and other didactic programs toward content areas underrepresented in the pandemic’s wake.

Limitations of this study include the fact that availability of testing and ICD-10 coding for COVID-19 differed slightly across training sites, potentially contributing to site differences in mapping. Additionally, given our 1:1 mapping of ICD-10 codes to content categories, our strategy attributes COVID-19 to ID alone, and does not capture additional areas germane to this diagnosis, such as pulmonary disease.

We provide a detailed characterization of the evolution of a single IM program’s patient care experiences across four training hospitals during the COVID-19 pandemic. Such characterization can be leveraged to provide effective practice habits feedback and guide teaching efforts, and could form the basis to predict competency-based outcomes for trainees in the COVID era.

Peritoneal fluid examination is often recommended for hospitalized patients with ascites.¹ The prevalence of spontaneous bacterial peritonitis (SBP) in these patients ranges from 10% to 30%.^2-6 Bedside paracentesis has clinical outcomes similar to that performed by radiology, with an improved length of stay (LOS) and decreased transfusion requirements.⁷

Internal medicine residency programs are establishing procedure services to address concerns about resident training in procedures and patient safety. Previous studies, which include paracentesis in patients with cirrhosis, have focused on resident comfort with procedures, supervision, procedural complications, and patient satisfaction.^8-12 However, the impact of a procedure service on the time from admission to the procedure has not been studied. In this study, we aimed to examine whether the institution of a hospitalist-run procedure service affected a patient’s LOS in the hospital and the time difference between a patient’s hospital admission and paracentesis (A2P).

An inpatient hospitalist-run procedure service was introduced on July 1, 2016. The service was staffed by a hospitalist and second-year internal medicine residents. The service is available 7:00 am to 5:00 pm all days of the week. To identify patients who underwent paracentesis, we queried our electronic medical records for all peritoneal fluid samples from July 1, 2016, to May 31, 2019. Paracenteses performed in the outpatient clinics, in the radiology suite, or in the emergency department were excluded if the patient was not admitted. We also excluded patients who had paracentesis within 6 hours of presentation, as these patients likely had an urgent clinical indication for paracentesis.

Data on age, gender, race, ethnicity, date and time of hospital admission, and discharge date and time were retrieved. We also retrieved data on the absolute number of polymorphonuclear leukocytes (PMN) in the peritoneal fluid sample; a patient with a count higher than 250/uL was considered to have SBP. The timestamp for the peritoneal fluid results was used to approximate the A2P time. Paracenteses performed by or under direct supervision of procedure service hospitalists were identified through a procedure log maintained by procedure service hospitalists. We generated a binary variable to differentiate patients who were admitted during the day from those admitted during the night, when the procedure service was not available. For all patients, we calculated the model for end-stage liver disease and sodium (MELD-Na) score.¹³ Groups performing paracenteses were categorized into procedure service, residents, and radiology. Primary clinical services were categorized into general medicine, gastroenterology, surgery, and others.

Data were summarized as mean (SD) or median (interquartile range) for continuous variables and as percentages for categorical variables. Patients who had paracenteses by radiology or residents during the study period were considered controls. We used concurrent controls to address secular time trends (eg, measures to decrease LOS or changes in ordering tests in the electronic health record) in outcome measures. Patient characteristics were compared using the Wilcoxon rank-sum test or the χ² test, as appropriate.

Two outcome variables were examined: LOS, and A2P time. Because both outcome variables were right skewed, we used generalized linear models with gamma distribution and log link. The advantage of a generalized linear model approach is that the transformed coefficients are better interpretable than when using the log transformation of the response variable.¹⁴ To account for time trends, we included time in months in the model. Models were adjusted for age, gender, race, whether the admission was during day or night, PMN in peritoneal fluid, MELD-Na score, platelet count on the day of procedure, presence or absence of cirrhosis, diagnosis-related groups weight, primary clinical service, and the group performing paracentesis. To address heterogeneity among patients included in our study and the fact that some patients had multiple paracenteses, we conducted sensitivity analyses by excluding all noncirrhotic patients and including only the first paracentesis. A P value less than .05 was considered significant. All statistical analyses were performed using Stata MP 16.0 for Windows (StataCorp LLC).

Of the 1,321 paracenteses included in our study, 509 (38.5%) were performed by the procedure service, 723 (54.7%) by residents, and 89 (6.7%) by radiology. For comparison, 15.4% of procedures were performed by the radiology service during the 3 years before the start of the procedure service. More than 50% of the first paracenteses were performed within 30 hours of admission. Hospitalists or residents under the direct supervision of a hospitalist performed all paracenteses. Residents performing paracenteses, when not on the procedure service, were on general internal medicine, gastroenterology, hematology and oncology, or surgical services. No failed paracentesis attempts by the procedure service were subsequently performed by radiology. The mean age of the participants was 55.3 (12.2) years, 728 (55%) were White, 502 (38%) were female, and SBP was present in 61 (4.6%) patients. There was no difference by age, gender, time of admission, presence of SBP, or peritoneal fluid PMN in patients who underwent paracentesis by the procedure service versus controls (Table 1). A higher proportion of White patients and patients with cirrhosis underwent paracentesis by the procedure service than by another service. The LOS and A2P time were significantly lower for patients who underwent paracentesis by the procedure service than by another service (Table 1). When examining the adjusted linear secular time trends, LOS decreased by 0.1% per month (95% CI, –0.5% to 0.8%; P = .67) and A2P time by 0.02% per month (95% CI, –1.0% to 1.1%; P = .96).

In unadjusted models but accounting for secular time trends, patients who had paracenteses performed by residents or by radiology had a 50% (95% CI, 22%-83%; P = .002) and 127% (95% CI, 65%-211%; P < .001) longer LOS, respectively, than when paracentesis was performed by the procedure service. After adjusting for potential confounders, the difference in LOS between radiology and the procedure service remained significant; patients who had a paracentesis performed by radiology had a 27% (95% CI, 2%-58%; P = .03) longer LOS than patients who had the procedure performed by the procedure service. This relative LOS translates into 88 (95% CI, 1-174 hours) additional hours in absolute LOS. There was no difference in LOS between the procedure service and residents in the adjusted analysis (Table 2).

Similarly, in unadjusted models for A2P time and accounting for secular time trends, patients who had a paracentesis performed by residents or by radiology had a 52% (95% CI, 23%-88%; P < .001) and 173% (95% CI, 109%-280%; P < .001) longer A2P time, respectively, than patients whose paracentesis was performed by the procedure service. After adjusting for potential confounders, the difference in A2P time between radiology and the procedure service remained significant. Patients who had paracentesis performed by radiology had a 40% (95% CI, 5%-87%; P = .02) longer A2P time than patients who had paracentesis performed by the procedure service. This relative increase translates into 52 (95% CI, 3.3-101 hours) additional hours in absolute A2P time. On the other hand, residents had a significantly shorter A2P time (–19%, 95% CI, –33% to 0.2%; P = .05) (Table 2).

In the sensitivity analysis, excluding noncirrhotic patients and including only the first paracentesis for patients who had multiple procedures performed during admission, the results remained unchanged. In adjusted analysis, patients who had paracentesis performed by radiology had a 47% (95% CI, 3.7%-108%; P = .03) longer LOS and 91% (95% CI, 19%-107%; P = .008) longer A2P time than when paracentesis was performed by the procedure service. There were no differences in LOS or A2P time between the procedure service and residents (Table 2).

In this study, we report that a hospitalist-run procedure service, when compared with a radiology service, is associated with decreased LOS and A2P time independent of studied potential confounders and secular time trends. We also showed that, compared with radiology, the A2P time for nonemergent procedures (those performed 6 hours after admission) was not adversely affected by the procedure service. Residents performing paracenteses independently had shorter A2P time than the procedure service.

Although several institutions have bedside procedure services, data are lacking on benefits. Previously, paracenteses performed by residents have been associated with decreased LOS and need for transfusions when compared with radiology.⁷ Our study extends these findings to show a shortened A2P time. Delays may occur when a patient is referred to radiology because of volume, triaging of higher-acuity procedures, and transportation. Procedure services provide consistent attending supervision, more procedures by upper-level residents, and a lower rate of unsuccessful procedures.^12,15 Current study findings support the importance of continuing bedside procedure training for at least those residents who are interested in hospital medicine.⁷

Our study has several strengths and some potential limitations. The study examined outcomes that are important to patients as well as hospital administrators; it also had a large sample size, spanning 3 years. As it was a retrospective cohort study, there is potential for residual confounding due to unmeasured confounders. We did not examine the potential effect modification of procedure urgency, as such data are difficult to discern. Our method of identification missed patients who received therapeutic paracentesis without laboratory analysis. It is unclear why more White patients were referred to the procedure team; this is an area for further evaluation. Results of this study are likely not generalizable to institutions with a robust radiology service that has built-in redundancy to accommodate urgent procedures and easy availability over the weekends.

We found that a hospitalist-run teaching procedure service is associated with shorter LOS and A2P time. Further research is needed to determine if the benefits of a procedure service extend to lowering morbidity and/or mortality, as well as to determine the cost-effectiveness of a procedure service and whether the significant investment by the institution in establishing a procedure service is mitigated by the gains from better patient outcomes and reduced LOS.

Peritoneal fluid examination is often recommended for hospitalized patients with ascites.¹ The prevalence of spontaneous bacterial peritonitis (SBP) in these patients ranges from 10% to 30%.^2-6 Bedside paracentesis has clinical outcomes similar to that performed by radiology, with an improved length of stay (LOS) and decreased transfusion requirements.⁷

Internal medicine residency programs are establishing procedure services to address concerns about resident training in procedures and patient safety. Previous studies, which include paracentesis in patients with cirrhosis, have focused on resident comfort with procedures, supervision, procedural complications, and patient satisfaction.^8-12 However, the impact of a procedure service on the time from admission to the procedure has not been studied. In this study, we aimed to examine whether the institution of a hospitalist-run procedure service affected a patient’s LOS in the hospital and the time difference between a patient’s hospital admission and paracentesis (A2P).

An inpatient hospitalist-run procedure service was introduced on July 1, 2016. The service was staffed by a hospitalist and second-year internal medicine residents. The service is available 7:00 am to 5:00 pm all days of the week. To identify patients who underwent paracentesis, we queried our electronic medical records for all peritoneal fluid samples from July 1, 2016, to May 31, 2019. Paracenteses performed in the outpatient clinics, in the radiology suite, or in the emergency department were excluded if the patient was not admitted. We also excluded patients who had paracentesis within 6 hours of presentation, as these patients likely had an urgent clinical indication for paracentesis.

Data on age, gender, race, ethnicity, date and time of hospital admission, and discharge date and time were retrieved. We also retrieved data on the absolute number of polymorphonuclear leukocytes (PMN) in the peritoneal fluid sample; a patient with a count higher than 250/uL was considered to have SBP. The timestamp for the peritoneal fluid results was used to approximate the A2P time. Paracenteses performed by or under direct supervision of procedure service hospitalists were identified through a procedure log maintained by procedure service hospitalists. We generated a binary variable to differentiate patients who were admitted during the day from those admitted during the night, when the procedure service was not available. For all patients, we calculated the model for end-stage liver disease and sodium (MELD-Na) score.¹³ Groups performing paracenteses were categorized into procedure service, residents, and radiology. Primary clinical services were categorized into general medicine, gastroenterology, surgery, and others.

Data were summarized as mean (SD) or median (interquartile range) for continuous variables and as percentages for categorical variables. Patients who had paracenteses by radiology or residents during the study period were considered controls. We used concurrent controls to address secular time trends (eg, measures to decrease LOS or changes in ordering tests in the electronic health record) in outcome measures. Patient characteristics were compared using the Wilcoxon rank-sum test or the χ² test, as appropriate.

Two outcome variables were examined: LOS, and A2P time. Because both outcome variables were right skewed, we used generalized linear models with gamma distribution and log link. The advantage of a generalized linear model approach is that the transformed coefficients are better interpretable than when using the log transformation of the response variable.¹⁴ To account for time trends, we included time in months in the model. Models were adjusted for age, gender, race, whether the admission was during day or night, PMN in peritoneal fluid, MELD-Na score, platelet count on the day of procedure, presence or absence of cirrhosis, diagnosis-related groups weight, primary clinical service, and the group performing paracentesis. To address heterogeneity among patients included in our study and the fact that some patients had multiple paracenteses, we conducted sensitivity analyses by excluding all noncirrhotic patients and including only the first paracentesis. A P value less than .05 was considered significant. All statistical analyses were performed using Stata MP 16.0 for Windows (StataCorp LLC).

Of the 1,321 paracenteses included in our study, 509 (38.5%) were performed by the procedure service, 723 (54.7%) by residents, and 89 (6.7%) by radiology. For comparison, 15.4% of procedures were performed by the radiology service during the 3 years before the start of the procedure service. More than 50% of the first paracenteses were performed within 30 hours of admission. Hospitalists or residents under the direct supervision of a hospitalist performed all paracenteses. Residents performing paracenteses, when not on the procedure service, were on general internal medicine, gastroenterology, hematology and oncology, or surgical services. No failed paracentesis attempts by the procedure service were subsequently performed by radiology. The mean age of the participants was 55.3 (12.2) years, 728 (55%) were White, 502 (38%) were female, and SBP was present in 61 (4.6%) patients. There was no difference by age, gender, time of admission, presence of SBP, or peritoneal fluid PMN in patients who underwent paracentesis by the procedure service versus controls (Table 1). A higher proportion of White patients and patients with cirrhosis underwent paracentesis by the procedure service than by another service. The LOS and A2P time were significantly lower for patients who underwent paracentesis by the procedure service than by another service (Table 1). When examining the adjusted linear secular time trends, LOS decreased by 0.1% per month (95% CI, –0.5% to 0.8%; P = .67) and A2P time by 0.02% per month (95% CI, –1.0% to 1.1%; P = .96).

In unadjusted models but accounting for secular time trends, patients who had paracenteses performed by residents or by radiology had a 50% (95% CI, 22%-83%; P = .002) and 127% (95% CI, 65%-211%; P < .001) longer LOS, respectively, than when paracentesis was performed by the procedure service. After adjusting for potential confounders, the difference in LOS between radiology and the procedure service remained significant; patients who had a paracentesis performed by radiology had a 27% (95% CI, 2%-58%; P = .03) longer LOS than patients who had the procedure performed by the procedure service. This relative LOS translates into 88 (95% CI, 1-174 hours) additional hours in absolute LOS. There was no difference in LOS between the procedure service and residents in the adjusted analysis (Table 2).

Similarly, in unadjusted models for A2P time and accounting for secular time trends, patients who had a paracentesis performed by residents or by radiology had a 52% (95% CI, 23%-88%; P < .001) and 173% (95% CI, 109%-280%; P < .001) longer A2P time, respectively, than patients whose paracentesis was performed by the procedure service. After adjusting for potential confounders, the difference in A2P time between radiology and the procedure service remained significant. Patients who had paracentesis performed by radiology had a 40% (95% CI, 5%-87%; P = .02) longer A2P time than patients who had paracentesis performed by the procedure service. This relative increase translates into 52 (95% CI, 3.3-101 hours) additional hours in absolute A2P time. On the other hand, residents had a significantly shorter A2P time (–19%, 95% CI, –33% to 0.2%; P = .05) (Table 2).

In the sensitivity analysis, excluding noncirrhotic patients and including only the first paracentesis for patients who had multiple procedures performed during admission, the results remained unchanged. In adjusted analysis, patients who had paracentesis performed by radiology had a 47% (95% CI, 3.7%-108%; P = .03) longer LOS and 91% (95% CI, 19%-107%; P = .008) longer A2P time than when paracentesis was performed by the procedure service. There were no differences in LOS or A2P time between the procedure service and residents (Table 2).

In this study, we report that a hospitalist-run procedure service, when compared with a radiology service, is associated with decreased LOS and A2P time independent of studied potential confounders and secular time trends. We also showed that, compared with radiology, the A2P time for nonemergent procedures (those performed 6 hours after admission) was not adversely affected by the procedure service. Residents performing paracenteses independently had shorter A2P time than the procedure service.

Although several institutions have bedside procedure services, data are lacking on benefits. Previously, paracenteses performed by residents have been associated with decreased LOS and need for transfusions when compared with radiology.⁷ Our study extends these findings to show a shortened A2P time. Delays may occur when a patient is referred to radiology because of volume, triaging of higher-acuity procedures, and transportation. Procedure services provide consistent attending supervision, more procedures by upper-level residents, and a lower rate of unsuccessful procedures.^12,15 Current study findings support the importance of continuing bedside procedure training for at least those residents who are interested in hospital medicine.⁷

Our study has several strengths and some potential limitations. The study examined outcomes that are important to patients as well as hospital administrators; it also had a large sample size, spanning 3 years. As it was a retrospective cohort study, there is potential for residual confounding due to unmeasured confounders. We did not examine the potential effect modification of procedure urgency, as such data are difficult to discern. Our method of identification missed patients who received therapeutic paracentesis without laboratory analysis. It is unclear why more White patients were referred to the procedure team; this is an area for further evaluation. Results of this study are likely not generalizable to institutions with a robust radiology service that has built-in redundancy to accommodate urgent procedures and easy availability over the weekends.

We found that a hospitalist-run teaching procedure service is associated with shorter LOS and A2P time. Further research is needed to determine if the benefits of a procedure service extend to lowering morbidity and/or mortality, as well as to determine the cost-effectiveness of a procedure service and whether the significant investment by the institution in establishing a procedure service is mitigated by the gains from better patient outcomes and reduced LOS.

Peritoneal fluid examination is often recommended for hospitalized patients with ascites.¹ The prevalence of spontaneous bacterial peritonitis (SBP) in these patients ranges from 10% to 30%.^2-6 Bedside paracentesis has clinical outcomes similar to that performed by radiology, with an improved length of stay (LOS) and decreased transfusion requirements.⁷

Internal medicine residency programs are establishing procedure services to address concerns about resident training in procedures and patient safety. Previous studies, which include paracentesis in patients with cirrhosis, have focused on resident comfort with procedures, supervision, procedural complications, and patient satisfaction.^8-12 However, the impact of a procedure service on the time from admission to the procedure has not been studied. In this study, we aimed to examine whether the institution of a hospitalist-run procedure service affected a patient’s LOS in the hospital and the time difference between a patient’s hospital admission and paracentesis (A2P).

An inpatient hospitalist-run procedure service was introduced on July 1, 2016. The service was staffed by a hospitalist and second-year internal medicine residents. The service is available 7:00 am to 5:00 pm all days of the week. To identify patients who underwent paracentesis, we queried our electronic medical records for all peritoneal fluid samples from July 1, 2016, to May 31, 2019. Paracenteses performed in the outpatient clinics, in the radiology suite, or in the emergency department were excluded if the patient was not admitted. We also excluded patients who had paracentesis within 6 hours of presentation, as these patients likely had an urgent clinical indication for paracentesis.

Data on age, gender, race, ethnicity, date and time of hospital admission, and discharge date and time were retrieved. We also retrieved data on the absolute number of polymorphonuclear leukocytes (PMN) in the peritoneal fluid sample; a patient with a count higher than 250/uL was considered to have SBP. The timestamp for the peritoneal fluid results was used to approximate the A2P time. Paracenteses performed by or under direct supervision of procedure service hospitalists were identified through a procedure log maintained by procedure service hospitalists. We generated a binary variable to differentiate patients who were admitted during the day from those admitted during the night, when the procedure service was not available. For all patients, we calculated the model for end-stage liver disease and sodium (MELD-Na) score.¹³ Groups performing paracenteses were categorized into procedure service, residents, and radiology. Primary clinical services were categorized into general medicine, gastroenterology, surgery, and others.

Data were summarized as mean (SD) or median (interquartile range) for continuous variables and as percentages for categorical variables. Patients who had paracenteses by radiology or residents during the study period were considered controls. We used concurrent controls to address secular time trends (eg, measures to decrease LOS or changes in ordering tests in the electronic health record) in outcome measures. Patient characteristics were compared using the Wilcoxon rank-sum test or the χ² test, as appropriate.

Two outcome variables were examined: LOS, and A2P time. Because both outcome variables were right skewed, we used generalized linear models with gamma distribution and log link. The advantage of a generalized linear model approach is that the transformed coefficients are better interpretable than when using the log transformation of the response variable.¹⁴ To account for time trends, we included time in months in the model. Models were adjusted for age, gender, race, whether the admission was during day or night, PMN in peritoneal fluid, MELD-Na score, platelet count on the day of procedure, presence or absence of cirrhosis, diagnosis-related groups weight, primary clinical service, and the group performing paracentesis. To address heterogeneity among patients included in our study and the fact that some patients had multiple paracenteses, we conducted sensitivity analyses by excluding all noncirrhotic patients and including only the first paracentesis. A P value less than .05 was considered significant. All statistical analyses were performed using Stata MP 16.0 for Windows (StataCorp LLC).

Of the 1,321 paracenteses included in our study, 509 (38.5%) were performed by the procedure service, 723 (54.7%) by residents, and 89 (6.7%) by radiology. For comparison, 15.4% of procedures were performed by the radiology service during the 3 years before the start of the procedure service. More than 50% of the first paracenteses were performed within 30 hours of admission. Hospitalists or residents under the direct supervision of a hospitalist performed all paracenteses. Residents performing paracenteses, when not on the procedure service, were on general internal medicine, gastroenterology, hematology and oncology, or surgical services. No failed paracentesis attempts by the procedure service were subsequently performed by radiology. The mean age of the participants was 55.3 (12.2) years, 728 (55%) were White, 502 (38%) were female, and SBP was present in 61 (4.6%) patients. There was no difference by age, gender, time of admission, presence of SBP, or peritoneal fluid PMN in patients who underwent paracentesis by the procedure service versus controls (Table 1). A higher proportion of White patients and patients with cirrhosis underwent paracentesis by the procedure service than by another service. The LOS and A2P time were significantly lower for patients who underwent paracentesis by the procedure service than by another service (Table 1). When examining the adjusted linear secular time trends, LOS decreased by 0.1% per month (95% CI, –0.5% to 0.8%; P = .67) and A2P time by 0.02% per month (95% CI, –1.0% to 1.1%; P = .96).

In unadjusted models but accounting for secular time trends, patients who had paracenteses performed by residents or by radiology had a 50% (95% CI, 22%-83%; P = .002) and 127% (95% CI, 65%-211%; P < .001) longer LOS, respectively, than when paracentesis was performed by the procedure service. After adjusting for potential confounders, the difference in LOS between radiology and the procedure service remained significant; patients who had a paracentesis performed by radiology had a 27% (95% CI, 2%-58%; P = .03) longer LOS than patients who had the procedure performed by the procedure service. This relative LOS translates into 88 (95% CI, 1-174 hours) additional hours in absolute LOS. There was no difference in LOS between the procedure service and residents in the adjusted analysis (Table 2).

Similarly, in unadjusted models for A2P time and accounting for secular time trends, patients who had a paracentesis performed by residents or by radiology had a 52% (95% CI, 23%-88%; P < .001) and 173% (95% CI, 109%-280%; P < .001) longer A2P time, respectively, than patients whose paracentesis was performed by the procedure service. After adjusting for potential confounders, the difference in A2P time between radiology and the procedure service remained significant. Patients who had paracentesis performed by radiology had a 40% (95% CI, 5%-87%; P = .02) longer A2P time than patients who had paracentesis performed by the procedure service. This relative increase translates into 52 (95% CI, 3.3-101 hours) additional hours in absolute A2P time. On the other hand, residents had a significantly shorter A2P time (–19%, 95% CI, –33% to 0.2%; P = .05) (Table 2).

In the sensitivity analysis, excluding noncirrhotic patients and including only the first paracentesis for patients who had multiple procedures performed during admission, the results remained unchanged. In adjusted analysis, patients who had paracentesis performed by radiology had a 47% (95% CI, 3.7%-108%; P = .03) longer LOS and 91% (95% CI, 19%-107%; P = .008) longer A2P time than when paracentesis was performed by the procedure service. There were no differences in LOS or A2P time between the procedure service and residents (Table 2).

In this study, we report that a hospitalist-run procedure service, when compared with a radiology service, is associated with decreased LOS and A2P time independent of studied potential confounders and secular time trends. We also showed that, compared with radiology, the A2P time for nonemergent procedures (those performed 6 hours after admission) was not adversely affected by the procedure service. Residents performing paracenteses independently had shorter A2P time than the procedure service.

Although several institutions have bedside procedure services, data are lacking on benefits. Previously, paracenteses performed by residents have been associated with decreased LOS and need for transfusions when compared with radiology.⁷ Our study extends these findings to show a shortened A2P time. Delays may occur when a patient is referred to radiology because of volume, triaging of higher-acuity procedures, and transportation. Procedure services provide consistent attending supervision, more procedures by upper-level residents, and a lower rate of unsuccessful procedures.^12,15 Current study findings support the importance of continuing bedside procedure training for at least those residents who are interested in hospital medicine.⁷

Our study has several strengths and some potential limitations. The study examined outcomes that are important to patients as well as hospital administrators; it also had a large sample size, spanning 3 years. As it was a retrospective cohort study, there is potential for residual confounding due to unmeasured confounders. We did not examine the potential effect modification of procedure urgency, as such data are difficult to discern. Our method of identification missed patients who received therapeutic paracentesis without laboratory analysis. It is unclear why more White patients were referred to the procedure team; this is an area for further evaluation. Results of this study are likely not generalizable to institutions with a robust radiology service that has built-in redundancy to accommodate urgent procedures and easy availability over the weekends.

We found that a hospitalist-run teaching procedure service is associated with shorter LOS and A2P time. Further research is needed to determine if the benefits of a procedure service extend to lowering morbidity and/or mortality, as well as to determine the cost-effectiveness of a procedure service and whether the significant investment by the institution in establishing a procedure service is mitigated by the gains from better patient outcomes and reduced LOS.

Hospital medicine research often asks the question whether an intervention, such as a policy or guideline, has improved quality of care and/or whether there were any unintended consequences. Alternatively, investigators may be interested in understanding the impact of an event, such as a natural disaster or a pandemic, on hospital care. The study design that provides the best estimate of the causal effect of the intervention is the randomized controlled trial (RCT). The goal of randomization, which can be implemented at the patient or cluster level (eg, hospitals), is attaining a balance of the known and unknown confounders between study groups.

However, an RCT may not be feasible for several reasons: complexity, insufficient setup time or funding, ethical barriers to randomization, unwillingness of funders or payers to withhold the intervention from patients (ie, the control group), or anticipated contamination of the intervention into the control group (eg, provider practice change interventions). In addition, it may be impossible to conduct an RCT because the investigator does not have control over the design of an intervention or because they are studying an event, such as a pandemic.

In the June 2020 issue of the Journal of Hospital Medicine, Coon et al¹ use a type of quasi-experimental design (QED)—specifically, the interrupted time series (ITS)—to examine the impact of the adoption of ward-based high-flow nasal cannula protocols on intensive care unit (ICU) admission for bronchiolitis at children’s hospitals. In this methodologic progress note, we discuss QEDs for evaluating the impact of healthcare interventions or events and focus on ITS, one of the strongest QEDs.

Quasi-experimental design refers to a broad range of nonrandomized or partially randomized pre- vs postintervention studies.² In order to test a causal hypothesis without randomization, QEDs define a comparison group or a time period in which an intervention has not been implemented, as well as at least one group or time period in which an intervention has been implemented. In a QED, the control may lack similarity with the intervention group or time period because of differences in the patients, sites, or time period (sometimes referred to as having a “nonequivalent control group”). Several design and analytic approaches are available to enhance the extent to which the study is able to make conclusions about the causal impact of the intervention.^2,3 Because randomization is not necessary, QEDs allow for inclusion of a broader population than that which is feasible by RCTs, which increases the applicability and generalizability of the results. Therefore, they are a powerful research design to test the effectiveness of interventions in real-world settings.

The choice of which QED depends on whether the investigators are conducting a prospective evaluation and have control over the study design (ie, the ordering of the intervention, selection of sites or individuals, and/or timing and frequency of the data collection) or whether the investigators do not have control over the intervention, which is also known as a “natural experiment.”^4,5 Some studies may also incorporate two QEDs in tandem.⁶ The Table provides a brief summary of different QEDs, ordered by methodologic strength, and distinguishes those that can be used to study natural experiments. In the study by Coon et al,¹ an ITS is used as opposed to a methodologically stronger QED, such as the stepped-wedge design, because the investigators did not have control over the rollout of heated high-flow nasal canula protocols across hospitals.

Interrupted time series designs use repeated observations of an outcome over time. This method then divides, or “interrupts,” the series of data into two time periods: before the intervention or event and after. Using data from the preintervention period, an underlying trend in the outcome is estimated and assumed to continue forward into the postintervention period to estimate what would have occurred without the intervention. Any significant change in the outcome at the beginning of the postintervention period or change in the trend in the postintervention is then attributed to the intervention.

There are several important methodologic considerations when designing an ITS study, as detailed in other review papers.^2,3,7,8 An ITS design can be retrospective or prospective. It can be of a single center or include multiple sites, as in Coon et al. It can be conducted with or without a control. The inclusion of a control, when appropriately chosen, improves the strength of the study design because it can account for seasonal trends and potential confounders that vary over time. The control can be a different group of hospitals or participants that are similar but did not receive the intervention, or it can be a different outcome in the same group of hospitals or participants that are not expected to be affected by the intervention. The ITS design may also be set up to estimate the individual effects of multicomponent interventions. If the different components are phased in sequentially over time, then it may be possible to interrupt the time series at these points and estimate the impact of each intervention component.

Other examples of ITS studies in hospital medicine include those that evaluated the impact of a readmission-reduction program,⁹ of state sepsis regulations on in-hospital mortality,¹⁰ of resident duty-hour reform on mortality among hospitalized patients,¹¹ of a quality-improvement initiative on early discharge,¹² and of national guidelines on pediatric pneumonia antibiotic selection.¹³ There are several types of ITS analysis, and in this article, we focus on segmented regression without a control group.^7,8

Segmented regression is the statistical model used to measure (a) the immediate change in the outcome (level) at the start of the intervention and (b) the change in the trend of the outcome (slope) in the postintervention period vs that in the preintervention period. Therefore, the intervention effect size is expressed in terms of the level change and the slope change. To function properly, the models require several repeated (eg, monthly) measurements of the outcome before and after the intervention. Some experts suggest a minimum of 4 to 12 observations, depending on a number of factors including the stability of the outcome and seasonal variations.^7,8 If changes before and after more than one intervention are being examined, there should be the minimum number of observations separating them. Unlike typical regression models, time-series models can correct for autocorrelation if it is present in the data. Autocorrelation is the type of correlation that arises when data are collected over time, with those closest in time being more strongly correlated (there are also other types of autocorrelation, such as seasonal patterns). Using available statistical software, autocorrelation can be detected and, if present, it can be controlled for in the segmented regression models.

Coon et al present results of their ITS analysis in a panel of figures detailing each study outcome, ICU admission, ICU length of stay, total length of stay, and rates of mechanical ventilation. Each panel shows the rate of change in the outcome per season across hospitals, before and after adoption of heated high-flow nasal cannula protocols, and the level change at the time of adoption.

To further explain how segmented regression results are presented, in the Figure we detail the structure of a segmented regression figure evaluating the impact of an intervention without a control group. In addition to the regression figure, authors typically provide 95% CIs around the rates, level change, and the difference between the postintervention and preintervention periods, along with P values demonstrating whether the rates, level change, and the differences between period slopes differ significantly from zero.

Segmented regression models assume a linear trend in the outcome. If the outcome follows a nonlinear pattern (eg, exponential spread of a disease during a pandemic), then using different distributions in the modeling or transformations of the data may be necessary. The validity of the comparison between the pre- and postintervention groups relies on the similarity between the populations. When there is imbalance, investigators can consider matching based on important characteristics or applying risk adjustment as necessary. Another important assumption is that the outcome of interest is unchanged in the absence of the intervention. Finally, the analysis assumes that the intervention is fully implemented at the time the postintervention period begins. Often, there is a washout period during which the old approach is stopped and the new approach (the intervention) is being implemented and can easily be taken into account.

There are several strengths of the ITS analysis and segmented regression.^7,8 First, this approach accounts for a possible secular trend in the outcome measure that may have been present prior to the intervention. For example, investigators might conclude that a readmissions program was effective in reducing readmissions if they found that the mean readmission percentage in the period after the intervention was significantly lower than before using a simple pre/post study design. However, what if the readmission rate was already going down prior to the intervention? Using an ITS approach, they may have found that the rate of readmissions simply continued to decrease after the intervention at the same rate that it was decreasing prior to the intervention and, therefore, conclude that the intervention was not effective. Second, because the ITS approach evaluates changes in rates of an outcome at a population level, confounding by individual-level variables will not introduce serious bias unless the confounding occurred at the same time as the intervention. Third, ITS can be used to measure the unintended consequences of interventions or events, and investigators can construct separate time-series analyses for different outcomes. Fourth, ITS can be used to evaluate the impact of the intervention on subpopulations (eg, those grouped by age, sex, race) by conducting stratified analysis. Fifth, ITS provides simple and clear graphical results that can be easily understood by various audiences.

By accounting for preintervention trends, ITS studies permit stronger causal inference than do cross-sectional or simple pre/post QEDs, but they may by prone to confounding by cointerventions or by changes in the population composition. Causal inference based on the ITS analysis is only valid to the extent to which the intervention was the only thing that changed at the point in time between the preintervention and postintervention periods. It is important for investigators to consider this in the design and discuss any coincident interventions. If there are multiple interventions over time, it is possible to account for these changes in the study design by creating multiple points of interruption provided there are sufficient measurements of the outcome between interventions. If the composition of the population changes at the same time as the intervention, this introduces bias. Changes in the ability to measure the outcome or changes to its definition also threaten the validity of the study’s inferences. Finally, it is also important to remember that when the outcome is a population-level measurement, inferences about individual-level outcomes are inappropriate due to ecological fallacies (ie, when inferences about individuals are deduced from inferences about the group to which those individuals belong). For example, Coon et al found that infants with bronchiolitis in the ward-based high-flow nasal cannula protocol group had greater ICU admission rates. It would be inappropriate to conclude that, based on this, an individual infant in a hospital on a ward-based protocol is more likely to be admitted to the ICU.

Studies evaluating interventions and events are important for informing healthcare practice, policy, and public health. While an RCT is the preferred method for such evaluations, investigators must often consider alternative study designs when an RCT is not feasible or when more real-world outcome evaluation is desired. Quasi-experimental designs are employed in studies that do not use randomization to study the impact of interventions in real-world settings, and an interrupted time series is a strong QED for the evaluation of interventions and natural experiments.

Hospital medicine research often asks the question whether an intervention, such as a policy or guideline, has improved quality of care and/or whether there were any unintended consequences. Alternatively, investigators may be interested in understanding the impact of an event, such as a natural disaster or a pandemic, on hospital care. The study design that provides the best estimate of the causal effect of the intervention is the randomized controlled trial (RCT). The goal of randomization, which can be implemented at the patient or cluster level (eg, hospitals), is attaining a balance of the known and unknown confounders between study groups.

However, an RCT may not be feasible for several reasons: complexity, insufficient setup time or funding, ethical barriers to randomization, unwillingness of funders or payers to withhold the intervention from patients (ie, the control group), or anticipated contamination of the intervention into the control group (eg, provider practice change interventions). In addition, it may be impossible to conduct an RCT because the investigator does not have control over the design of an intervention or because they are studying an event, such as a pandemic.

In the June 2020 issue of the Journal of Hospital Medicine, Coon et al¹ use a type of quasi-experimental design (QED)—specifically, the interrupted time series (ITS)—to examine the impact of the adoption of ward-based high-flow nasal cannula protocols on intensive care unit (ICU) admission for bronchiolitis at children’s hospitals. In this methodologic progress note, we discuss QEDs for evaluating the impact of healthcare interventions or events and focus on ITS, one of the strongest QEDs.

Quasi-experimental design refers to a broad range of nonrandomized or partially randomized pre- vs postintervention studies.² In order to test a causal hypothesis without randomization, QEDs define a comparison group or a time period in which an intervention has not been implemented, as well as at least one group or time period in which an intervention has been implemented. In a QED, the control may lack similarity with the intervention group or time period because of differences in the patients, sites, or time period (sometimes referred to as having a “nonequivalent control group”). Several design and analytic approaches are available to enhance the extent to which the study is able to make conclusions about the causal impact of the intervention.^2,3 Because randomization is not necessary, QEDs allow for inclusion of a broader population than that which is feasible by RCTs, which increases the applicability and generalizability of the results. Therefore, they are a powerful research design to test the effectiveness of interventions in real-world settings.

The choice of which QED depends on whether the investigators are conducting a prospective evaluation and have control over the study design (ie, the ordering of the intervention, selection of sites or individuals, and/or timing and frequency of the data collection) or whether the investigators do not have control over the intervention, which is also known as a “natural experiment.”^4,5 Some studies may also incorporate two QEDs in tandem.⁶ The Table provides a brief summary of different QEDs, ordered by methodologic strength, and distinguishes those that can be used to study natural experiments. In the study by Coon et al,¹ an ITS is used as opposed to a methodologically stronger QED, such as the stepped-wedge design, because the investigators did not have control over the rollout of heated high-flow nasal canula protocols across hospitals.

Interrupted time series designs use repeated observations of an outcome over time. This method then divides, or “interrupts,” the series of data into two time periods: before the intervention or event and after. Using data from the preintervention period, an underlying trend in the outcome is estimated and assumed to continue forward into the postintervention period to estimate what would have occurred without the intervention. Any significant change in the outcome at the beginning of the postintervention period or change in the trend in the postintervention is then attributed to the intervention.

There are several important methodologic considerations when designing an ITS study, as detailed in other review papers.^2,3,7,8 An ITS design can be retrospective or prospective. It can be of a single center or include multiple sites, as in Coon et al. It can be conducted with or without a control. The inclusion of a control, when appropriately chosen, improves the strength of the study design because it can account for seasonal trends and potential confounders that vary over time. The control can be a different group of hospitals or participants that are similar but did not receive the intervention, or it can be a different outcome in the same group of hospitals or participants that are not expected to be affected by the intervention. The ITS design may also be set up to estimate the individual effects of multicomponent interventions. If the different components are phased in sequentially over time, then it may be possible to interrupt the time series at these points and estimate the impact of each intervention component.

Other examples of ITS studies in hospital medicine include those that evaluated the impact of a readmission-reduction program,⁹ of state sepsis regulations on in-hospital mortality,¹⁰ of resident duty-hour reform on mortality among hospitalized patients,¹¹ of a quality-improvement initiative on early discharge,¹² and of national guidelines on pediatric pneumonia antibiotic selection.¹³ There are several types of ITS analysis, and in this article, we focus on segmented regression without a control group.^7,8

Segmented regression is the statistical model used to measure (a) the immediate change in the outcome (level) at the start of the intervention and (b) the change in the trend of the outcome (slope) in the postintervention period vs that in the preintervention period. Therefore, the intervention effect size is expressed in terms of the level change and the slope change. To function properly, the models require several repeated (eg, monthly) measurements of the outcome before and after the intervention. Some experts suggest a minimum of 4 to 12 observations, depending on a number of factors including the stability of the outcome and seasonal variations.^7,8 If changes before and after more than one intervention are being examined, there should be the minimum number of observations separating them. Unlike typical regression models, time-series models can correct for autocorrelation if it is present in the data. Autocorrelation is the type of correlation that arises when data are collected over time, with those closest in time being more strongly correlated (there are also other types of autocorrelation, such as seasonal patterns). Using available statistical software, autocorrelation can be detected and, if present, it can be controlled for in the segmented regression models.

Coon et al present results of their ITS analysis in a panel of figures detailing each study outcome, ICU admission, ICU length of stay, total length of stay, and rates of mechanical ventilation. Each panel shows the rate of change in the outcome per season across hospitals, before and after adoption of heated high-flow nasal cannula protocols, and the level change at the time of adoption.

To further explain how segmented regression results are presented, in the Figure we detail the structure of a segmented regression figure evaluating the impact of an intervention without a control group. In addition to the regression figure, authors typically provide 95% CIs around the rates, level change, and the difference between the postintervention and preintervention periods, along with P values demonstrating whether the rates, level change, and the differences between period slopes differ significantly from zero.

Segmented regression models assume a linear trend in the outcome. If the outcome follows a nonlinear pattern (eg, exponential spread of a disease during a pandemic), then using different distributions in the modeling or transformations of the data may be necessary. The validity of the comparison between the pre- and postintervention groups relies on the similarity between the populations. When there is imbalance, investigators can consider matching based on important characteristics or applying risk adjustment as necessary. Another important assumption is that the outcome of interest is unchanged in the absence of the intervention. Finally, the analysis assumes that the intervention is fully implemented at the time the postintervention period begins. Often, there is a washout period during which the old approach is stopped and the new approach (the intervention) is being implemented and can easily be taken into account.

There are several strengths of the ITS analysis and segmented regression.^7,8 First, this approach accounts for a possible secular trend in the outcome measure that may have been present prior to the intervention. For example, investigators might conclude that a readmissions program was effective in reducing readmissions if they found that the mean readmission percentage in the period after the intervention was significantly lower than before using a simple pre/post study design. However, what if the readmission rate was already going down prior to the intervention? Using an ITS approach, they may have found that the rate of readmissions simply continued to decrease after the intervention at the same rate that it was decreasing prior to the intervention and, therefore, conclude that the intervention was not effective. Second, because the ITS approach evaluates changes in rates of an outcome at a population level, confounding by individual-level variables will not introduce serious bias unless the confounding occurred at the same time as the intervention. Third, ITS can be used to measure the unintended consequences of interventions or events, and investigators can construct separate time-series analyses for different outcomes. Fourth, ITS can be used to evaluate the impact of the intervention on subpopulations (eg, those grouped by age, sex, race) by conducting stratified analysis. Fifth, ITS provides simple and clear graphical results that can be easily understood by various audiences.

By accounting for preintervention trends, ITS studies permit stronger causal inference than do cross-sectional or simple pre/post QEDs, but they may by prone to confounding by cointerventions or by changes in the population composition. Causal inference based on the ITS analysis is only valid to the extent to which the intervention was the only thing that changed at the point in time between the preintervention and postintervention periods. It is important for investigators to consider this in the design and discuss any coincident interventions. If there are multiple interventions over time, it is possible to account for these changes in the study design by creating multiple points of interruption provided there are sufficient measurements of the outcome between interventions. If the composition of the population changes at the same time as the intervention, this introduces bias. Changes in the ability to measure the outcome or changes to its definition also threaten the validity of the study’s inferences. Finally, it is also important to remember that when the outcome is a population-level measurement, inferences about individual-level outcomes are inappropriate due to ecological fallacies (ie, when inferences about individuals are deduced from inferences about the group to which those individuals belong). For example, Coon et al found that infants with bronchiolitis in the ward-based high-flow nasal cannula protocol group had greater ICU admission rates. It would be inappropriate to conclude that, based on this, an individual infant in a hospital on a ward-based protocol is more likely to be admitted to the ICU.

Studies evaluating interventions and events are important for informing healthcare practice, policy, and public health. While an RCT is the preferred method for such evaluations, investigators must often consider alternative study designs when an RCT is not feasible or when more real-world outcome evaluation is desired. Quasi-experimental designs are employed in studies that do not use randomization to study the impact of interventions in real-world settings, and an interrupted time series is a strong QED for the evaluation of interventions and natural experiments.

Hospital medicine research often asks the question whether an intervention, such as a policy or guideline, has improved quality of care and/or whether there were any unintended consequences. Alternatively, investigators may be interested in understanding the impact of an event, such as a natural disaster or a pandemic, on hospital care. The study design that provides the best estimate of the causal effect of the intervention is the randomized controlled trial (RCT). The goal of randomization, which can be implemented at the patient or cluster level (eg, hospitals), is attaining a balance of the known and unknown confounders between study groups.

However, an RCT may not be feasible for several reasons: complexity, insufficient setup time or funding, ethical barriers to randomization, unwillingness of funders or payers to withhold the intervention from patients (ie, the control group), or anticipated contamination of the intervention into the control group (eg, provider practice change interventions). In addition, it may be impossible to conduct an RCT because the investigator does not have control over the design of an intervention or because they are studying an event, such as a pandemic.

In the June 2020 issue of the Journal of Hospital Medicine, Coon et al¹ use a type of quasi-experimental design (QED)—specifically, the interrupted time series (ITS)—to examine the impact of the adoption of ward-based high-flow nasal cannula protocols on intensive care unit (ICU) admission for bronchiolitis at children’s hospitals. In this methodologic progress note, we discuss QEDs for evaluating the impact of healthcare interventions or events and focus on ITS, one of the strongest QEDs.

Quasi-experimental design refers to a broad range of nonrandomized or partially randomized pre- vs postintervention studies.² In order to test a causal hypothesis without randomization, QEDs define a comparison group or a time period in which an intervention has not been implemented, as well as at least one group or time period in which an intervention has been implemented. In a QED, the control may lack similarity with the intervention group or time period because of differences in the patients, sites, or time period (sometimes referred to as having a “nonequivalent control group”). Several design and analytic approaches are available to enhance the extent to which the study is able to make conclusions about the causal impact of the intervention.^2,3 Because randomization is not necessary, QEDs allow for inclusion of a broader population than that which is feasible by RCTs, which increases the applicability and generalizability of the results. Therefore, they are a powerful research design to test the effectiveness of interventions in real-world settings.

The choice of which QED depends on whether the investigators are conducting a prospective evaluation and have control over the study design (ie, the ordering of the intervention, selection of sites or individuals, and/or timing and frequency of the data collection) or whether the investigators do not have control over the intervention, which is also known as a “natural experiment.”^4,5 Some studies may also incorporate two QEDs in tandem.⁶ The Table provides a brief summary of different QEDs, ordered by methodologic strength, and distinguishes those that can be used to study natural experiments. In the study by Coon et al,¹ an ITS is used as opposed to a methodologically stronger QED, such as the stepped-wedge design, because the investigators did not have control over the rollout of heated high-flow nasal canula protocols across hospitals.

Interrupted time series designs use repeated observations of an outcome over time. This method then divides, or “interrupts,” the series of data into two time periods: before the intervention or event and after. Using data from the preintervention period, an underlying trend in the outcome is estimated and assumed to continue forward into the postintervention period to estimate what would have occurred without the intervention. Any significant change in the outcome at the beginning of the postintervention period or change in the trend in the postintervention is then attributed to the intervention.

There are several important methodologic considerations when designing an ITS study, as detailed in other review papers.^2,3,7,8 An ITS design can be retrospective or prospective. It can be of a single center or include multiple sites, as in Coon et al. It can be conducted with or without a control. The inclusion of a control, when appropriately chosen, improves the strength of the study design because it can account for seasonal trends and potential confounders that vary over time. The control can be a different group of hospitals or participants that are similar but did not receive the intervention, or it can be a different outcome in the same group of hospitals or participants that are not expected to be affected by the intervention. The ITS design may also be set up to estimate the individual effects of multicomponent interventions. If the different components are phased in sequentially over time, then it may be possible to interrupt the time series at these points and estimate the impact of each intervention component.

Other examples of ITS studies in hospital medicine include those that evaluated the impact of a readmission-reduction program,⁹ of state sepsis regulations on in-hospital mortality,¹⁰ of resident duty-hour reform on mortality among hospitalized patients,¹¹ of a quality-improvement initiative on early discharge,¹² and of national guidelines on pediatric pneumonia antibiotic selection.¹³ There are several types of ITS analysis, and in this article, we focus on segmented regression without a control group.^7,8

Segmented regression is the statistical model used to measure (a) the immediate change in the outcome (level) at the start of the intervention and (b) the change in the trend of the outcome (slope) in the postintervention period vs that in the preintervention period. Therefore, the intervention effect size is expressed in terms of the level change and the slope change. To function properly, the models require several repeated (eg, monthly) measurements of the outcome before and after the intervention. Some experts suggest a minimum of 4 to 12 observations, depending on a number of factors including the stability of the outcome and seasonal variations.^7,8 If changes before and after more than one intervention are being examined, there should be the minimum number of observations separating them. Unlike typical regression models, time-series models can correct for autocorrelation if it is present in the data. Autocorrelation is the type of correlation that arises when data are collected over time, with those closest in time being more strongly correlated (there are also other types of autocorrelation, such as seasonal patterns). Using available statistical software, autocorrelation can be detected and, if present, it can be controlled for in the segmented regression models.

Coon et al present results of their ITS analysis in a panel of figures detailing each study outcome, ICU admission, ICU length of stay, total length of stay, and rates of mechanical ventilation. Each panel shows the rate of change in the outcome per season across hospitals, before and after adoption of heated high-flow nasal cannula protocols, and the level change at the time of adoption.

To further explain how segmented regression results are presented, in the Figure we detail the structure of a segmented regression figure evaluating the impact of an intervention without a control group. In addition to the regression figure, authors typically provide 95% CIs around the rates, level change, and the difference between the postintervention and preintervention periods, along with P values demonstrating whether the rates, level change, and the differences between period slopes differ significantly from zero.

Segmented regression models assume a linear trend in the outcome. If the outcome follows a nonlinear pattern (eg, exponential spread of a disease during a pandemic), then using different distributions in the modeling or transformations of the data may be necessary. The validity of the comparison between the pre- and postintervention groups relies on the similarity between the populations. When there is imbalance, investigators can consider matching based on important characteristics or applying risk adjustment as necessary. Another important assumption is that the outcome of interest is unchanged in the absence of the intervention. Finally, the analysis assumes that the intervention is fully implemented at the time the postintervention period begins. Often, there is a washout period during which the old approach is stopped and the new approach (the intervention) is being implemented and can easily be taken into account.

There are several strengths of the ITS analysis and segmented regression.^7,8 First, this approach accounts for a possible secular trend in the outcome measure that may have been present prior to the intervention. For example, investigators might conclude that a readmissions program was effective in reducing readmissions if they found that the mean readmission percentage in the period after the intervention was significantly lower than before using a simple pre/post study design. However, what if the readmission rate was already going down prior to the intervention? Using an ITS approach, they may have found that the rate of readmissions simply continued to decrease after the intervention at the same rate that it was decreasing prior to the intervention and, therefore, conclude that the intervention was not effective. Second, because the ITS approach evaluates changes in rates of an outcome at a population level, confounding by individual-level variables will not introduce serious bias unless the confounding occurred at the same time as the intervention. Third, ITS can be used to measure the unintended consequences of interventions or events, and investigators can construct separate time-series analyses for different outcomes. Fourth, ITS can be used to evaluate the impact of the intervention on subpopulations (eg, those grouped by age, sex, race) by conducting stratified analysis. Fifth, ITS provides simple and clear graphical results that can be easily understood by various audiences.

By accounting for preintervention trends, ITS studies permit stronger causal inference than do cross-sectional or simple pre/post QEDs, but they may by prone to confounding by cointerventions or by changes in the population composition. Causal inference based on the ITS analysis is only valid to the extent to which the intervention was the only thing that changed at the point in time between the preintervention and postintervention periods. It is important for investigators to consider this in the design and discuss any coincident interventions. If there are multiple interventions over time, it is possible to account for these changes in the study design by creating multiple points of interruption provided there are sufficient measurements of the outcome between interventions. If the composition of the population changes at the same time as the intervention, this introduces bias. Changes in the ability to measure the outcome or changes to its definition also threaten the validity of the study’s inferences. Finally, it is also important to remember that when the outcome is a population-level measurement, inferences about individual-level outcomes are inappropriate due to ecological fallacies (ie, when inferences about individuals are deduced from inferences about the group to which those individuals belong). For example, Coon et al found that infants with bronchiolitis in the ward-based high-flow nasal cannula protocol group had greater ICU admission rates. It would be inappropriate to conclude that, based on this, an individual infant in a hospital on a ward-based protocol is more likely to be admitted to the ICU.

Studies evaluating interventions and events are important for informing healthcare practice, policy, and public health. While an RCT is the preferred method for such evaluations, investigators must often consider alternative study designs when an RCT is not feasible or when more real-world outcome evaluation is desired. Quasi-experimental designs are employed in studies that do not use randomization to study the impact of interventions in real-world settings, and an interrupted time series is a strong QED for the evaluation of interventions and natural experiments.

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

The hospitalist admits an 18-year-old man for newly diagnosed granulomatosis with polyangiitis to receive expedited pulse-dose steroids and plasma exchange. After consulting interventional radiology for catheter placement the following day, the hospitalist places a “strict” nil per os (nothing by mouth, NPO) after midnight order. During rounds the following morning, the patient reports that he wants to eat. At 9 am, interventional radiology informs the nurse that the line placement will take place at 3 pm. Due to emergencies and other unplanned delays, the catheter placement occurs at 5 pm. The patient and family express their displeasure about the prolonged fasting and ask why this happened.

Hospitalists commonly order “NPO after midnight” diets in anticipation of procedures requiring sedation or general anesthesia. Typically, NPO refers to no food or drink, but in some instances, NPO includes no oral medications. Up to half of medical patients experience some time of fasting while hospitalized.¹ However, NPO practices vary widely across institutions.^2,3 A study from 2014 notes that, on average, patients fast preprocedure for approximately 13.5 hours for solids and 9.6 hours for liquids.² Prolonged fasting times offer little benefit to patients and may lead to frequent patient dissatisfaction and complaints.

In 1883, Sir Joseph Lister described 19th century NPO practices distinguishing solids from liquids, allowing patients “tea or beef tea” until 2 to 3 hours prior to surgery.⁴ However, in 1946, Mendelson published an influential account of 66 pregnant women who aspirated during delivery under general anesthesia.⁵ Two of the 66 patients, both of whom had eaten a full meal 6 to 8 hours prior to general anesthesia, died. The study not only increased awareness of the risk of aspiration with general anesthesia in pregnancy, but it influenced the care for the nonpregnant population of patients as well. By the 1960s, anesthesia texts recommended “NPO after midnight” for both liquids and solids in all patients, regardless of pregnancy status.⁴ To minimize the risk to patients, we have continued to pass down the practice of NPO after midnight to subsequent generations.

Additionally, medical centers and hospitals feel pressure to provide efficient, patient-centered, high-value care. Given the complexity of procedural scheduling and the penalties associated with delays, keeping patients NPO ensures their availability for the next open procedural slot. NPO after midnight orders aim to prevent potential delays in treatment that occur when inadvertent ingestion of food and drink leads to cancellation of procedures.

Recent studies have led to a more sophisticated understanding of gastric emptying and the risks of aspiration during sedation and intubation. Gastric emptying studies routinely show that transit of clear liquids out of the stomach is virtually complete within two hours of drinking.⁶ Age, body mass index, and alcohol have no effect on gastric emptying time, and almost all patients return to preingestion gastric residual volumes within 2 hours of clear liquid consumption.^6,7 While morbidly obese patients tend to have higher gastric fluid volumes after 9 hours of fasting, their stomachs empty at rates similar to nonobese individuals.⁶ Note that, regardless of fasting times, morbid obesity predisposes patients to a higher overall gastric volume and lower pH of gastric contents, which may increase risk of aspiration.⁸ A Cochrane review found no statistical difference in gastric volumes or stomach pH in patients on a standard fast vs shortened (<180 minutes) liquid fast.⁹ The review included nine studies that found patients who consumed a clear liquid beverage had reduced gastric volumes, compared with patients in a fasting state (P < .001).⁹

In a pediatric retrospective study of pulmonary aspiration events, the researchers demonstrated that clinically significant aspiration (presence of bilious secretions in the tracheobronchial airways) occurred at a rate of 0.04% with emergency surgery.¹⁰ Bowel obstruction or ileus accounted for approximately 54% of those cases. Importantly, the reported aspiration rate approximates the rate of pregnant patients from the 1946 Mendelson study of 0.14% (66 out of 44,016), which originally prompted the use of the prolonged NPO status. Based on the Cochrane review of perioperative fasting recommendations for those older than 18 years, consuming fluids more than 90 minutes preoperatively confers a negligible (0 adverse events reported in 9 studies) risk for aspiration or regurgitation events.⁹

In 1998, as a result of these and other similar studies, the American Society of Anesthesiologists (ASA) along with global anesthesia partners adopted guidelines that allowed clear liquids up until 2 hours prior to anesthesia or sedation in low-aspiration-risk patients undergoing elective cases.¹¹ The guidelines allowed for other beverages and food based on their standard transit times (Table). The ASA guidelines do not define low-aspiration-risk patients. Anesthesiologists generally exclude from the low-risk category patients who may have delayed gastric emptying from medical or iatrogenic causes. The updated 2017 ASA guidelines remain unchanged regarding fasting guidelines.¹² Studies suggest that approximately 10% to 20% of NPO after midnight orders are avoidable.^1,3 For those instances, procedures are often deemed not necessary or do not require NPO status.¹

In a study evaluating the reasons that necessary procedures are canceled, only 0.5% of inpatient procedures are cancelled due to the inappropriate ingestion of food or drink.³ In addition, NPO status creates risk. Patients with prolonged NPO status report greater hunger, thirst, tiredness, and weakness prior to surgery when compared with patients receiving a carbohydrate-rich drink 2 hours prior to procedures.^9,13,14 In fact, multiple studies have suggested that preoperative carbohydrate-rich drinks 2 hours before surgery can be associated with decreased insulin resistance in the perioperative period, decreased length of stay, and improvement in perioperative metabolic, cardiac, and psychosomatic status.^9,13-15 These types of studies have informed the enhanced recovery after surgery program, which recommends a carbohydrate beverage 2 to 3 hours prior to surgery.

Prescribe the minimum recommended fasting times only for low-aspiration-risk patients undergoing elective procedures. Risk for regurgitation or aspiration increases for patients with conditions resulting in decreased gastric emptying, gastric or bowel obstruction, or lower esophageal sphincter incompetence. Those patients may require longer NPO time periods.⁸ Higher-risk diagnoses and clinical conditions include gastroparesis, trauma, and pregnancy.^5,8,16 Specific risk factors for aspiration in children may include trauma, bowel obstruction, depressed consciousness, shock, or ileus.¹⁰ For surgical emergencies, balance the risk of surgical delay vs perceived aspiration risk.

Use evidence-based guidelines to assess periprocedural aspiration risk. The ASA guidelines suggest that healthy, nonpregnant patients should fast for 8 hours after heavy meals, 6 hours after a light, nonfatty meal, and 2 hours after clear liquids (eg, water, fruit juices without pulp, carbonated beverages, black coffee).¹² Focus on the type of food or drink rather than the volume ingested.¹² Additionally, patients should ingest, with small amounts of clear fluids, appropriate home medications for acute and chronic conditions regardless of NPO status.

While procedure delays or cancellations for any reason upset patients and families and can disrupt the flow of the operating room and procedural suite, we can achieve the delicate balance between efficiency and patient safety and comfort. Since complex inpatient procedural scheduling may not allow for liberalization of solids requiring 6 to 8 hours of fasting time, focus on liberalizing liquids 2 hours prior to anesthesia. This allows staff to minimize the time low-risk patients fast while still maintaining flexibility for operating room case scheduling. We must promote communication between operating room and floor staff to anticipate timing of procedures each day. Healthcare facilities should aim to achieve time-based preprocedural NPO status as opposed to an arbitrary starting time like midnight.⁴

• Risk stratify patients for anesthesia-related aspiration with the aim of identifying those at low aspiration risk.
• For low-risk patients, adhere to recommended fasting times: 2 hours for a clear carbohydrate beverage, 4 hours for breast milk, 6 hours for a light meal or formula, and 8 hours for a fatty meal.
• For patients not deemed low risk, determine the appropriate length of preprocedural fasting by consulting with the anesthesia and surgical teams.

NPO after midnight represents a low-value and arbitrary practice that leaves patients fasting longer than necessary.^2,3,12 In addition to the 2017 ASA guidelines, newer studies and protocols are improving patient satisfaction, minimizing patient dehydration and electrolyte disturbances, and incorporating enhanced recovery after surgery factors into a better patient experience. Returning to the clinical scenario, the hospitalist team can increase patient satisfaction by focusing on liberalizing clear fluids with a carbohydrate beverage up to 2 hours prior to elective surgery while still allowing for schedule flexibility. For this patient, a 3 pm procedure time would have allowed him to have a light breakfast and carbohydrate beverages until 2 hours prior to anesthesia. Dispose of the antiquated practice of NPO after midnight by maximizing clear fluid intake in accordance with current guidelines prior to sedation and general anesthesia. This change in practice will help to achieve normophysiology and increase patient satisfaction.

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

Disclaimer: The opinions expressed in this article are those of the authors alone and do not reflect the views of the Department of Veterans Affairs. The Veterans Affairs Quality Scholars Program is supported by the Veterans Affairs Office of Academic Affiliations, Washington, DC.

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

The hospitalist admits an 18-year-old man for newly diagnosed granulomatosis with polyangiitis to receive expedited pulse-dose steroids and plasma exchange. After consulting interventional radiology for catheter placement the following day, the hospitalist places a “strict” nil per os (nothing by mouth, NPO) after midnight order. During rounds the following morning, the patient reports that he wants to eat. At 9 am, interventional radiology informs the nurse that the line placement will take place at 3 pm. Due to emergencies and other unplanned delays, the catheter placement occurs at 5 pm. The patient and family express their displeasure about the prolonged fasting and ask why this happened.

Hospitalists commonly order “NPO after midnight” diets in anticipation of procedures requiring sedation or general anesthesia. Typically, NPO refers to no food or drink, but in some instances, NPO includes no oral medications. Up to half of medical patients experience some time of fasting while hospitalized.¹ However, NPO practices vary widely across institutions.^2,3 A study from 2014 notes that, on average, patients fast preprocedure for approximately 13.5 hours for solids and 9.6 hours for liquids.² Prolonged fasting times offer little benefit to patients and may lead to frequent patient dissatisfaction and complaints.

In 1883, Sir Joseph Lister described 19th century NPO practices distinguishing solids from liquids, allowing patients “tea or beef tea” until 2 to 3 hours prior to surgery.⁴ However, in 1946, Mendelson published an influential account of 66 pregnant women who aspirated during delivery under general anesthesia.⁵ Two of the 66 patients, both of whom had eaten a full meal 6 to 8 hours prior to general anesthesia, died. The study not only increased awareness of the risk of aspiration with general anesthesia in pregnancy, but it influenced the care for the nonpregnant population of patients as well. By the 1960s, anesthesia texts recommended “NPO after midnight” for both liquids and solids in all patients, regardless of pregnancy status.⁴ To minimize the risk to patients, we have continued to pass down the practice of NPO after midnight to subsequent generations.

Additionally, medical centers and hospitals feel pressure to provide efficient, patient-centered, high-value care. Given the complexity of procedural scheduling and the penalties associated with delays, keeping patients NPO ensures their availability for the next open procedural slot. NPO after midnight orders aim to prevent potential delays in treatment that occur when inadvertent ingestion of food and drink leads to cancellation of procedures.

Recent studies have led to a more sophisticated understanding of gastric emptying and the risks of aspiration during sedation and intubation. Gastric emptying studies routinely show that transit of clear liquids out of the stomach is virtually complete within two hours of drinking.⁶ Age, body mass index, and alcohol have no effect on gastric emptying time, and almost all patients return to preingestion gastric residual volumes within 2 hours of clear liquid consumption.^6,7 While morbidly obese patients tend to have higher gastric fluid volumes after 9 hours of fasting, their stomachs empty at rates similar to nonobese individuals.⁶ Note that, regardless of fasting times, morbid obesity predisposes patients to a higher overall gastric volume and lower pH of gastric contents, which may increase risk of aspiration.⁸ A Cochrane review found no statistical difference in gastric volumes or stomach pH in patients on a standard fast vs shortened (<180 minutes) liquid fast.⁹ The review included nine studies that found patients who consumed a clear liquid beverage had reduced gastric volumes, compared with patients in a fasting state (P < .001).⁹

In a pediatric retrospective study of pulmonary aspiration events, the researchers demonstrated that clinically significant aspiration (presence of bilious secretions in the tracheobronchial airways) occurred at a rate of 0.04% with emergency surgery.¹⁰ Bowel obstruction or ileus accounted for approximately 54% of those cases. Importantly, the reported aspiration rate approximates the rate of pregnant patients from the 1946 Mendelson study of 0.14% (66 out of 44,016), which originally prompted the use of the prolonged NPO status. Based on the Cochrane review of perioperative fasting recommendations for those older than 18 years, consuming fluids more than 90 minutes preoperatively confers a negligible (0 adverse events reported in 9 studies) risk for aspiration or regurgitation events.⁹

In 1998, as a result of these and other similar studies, the American Society of Anesthesiologists (ASA) along with global anesthesia partners adopted guidelines that allowed clear liquids up until 2 hours prior to anesthesia or sedation in low-aspiration-risk patients undergoing elective cases.¹¹ The guidelines allowed for other beverages and food based on their standard transit times (Table). The ASA guidelines do not define low-aspiration-risk patients. Anesthesiologists generally exclude from the low-risk category patients who may have delayed gastric emptying from medical or iatrogenic causes. The updated 2017 ASA guidelines remain unchanged regarding fasting guidelines.¹² Studies suggest that approximately 10% to 20% of NPO after midnight orders are avoidable.^1,3 For those instances, procedures are often deemed not necessary or do not require NPO status.¹

In a study evaluating the reasons that necessary procedures are canceled, only 0.5% of inpatient procedures are cancelled due to the inappropriate ingestion of food or drink.³ In addition, NPO status creates risk. Patients with prolonged NPO status report greater hunger, thirst, tiredness, and weakness prior to surgery when compared with patients receiving a carbohydrate-rich drink 2 hours prior to procedures.^9,13,14 In fact, multiple studies have suggested that preoperative carbohydrate-rich drinks 2 hours before surgery can be associated with decreased insulin resistance in the perioperative period, decreased length of stay, and improvement in perioperative metabolic, cardiac, and psychosomatic status.^9,13-15 These types of studies have informed the enhanced recovery after surgery program, which recommends a carbohydrate beverage 2 to 3 hours prior to surgery.

Prescribe the minimum recommended fasting times only for low-aspiration-risk patients undergoing elective procedures. Risk for regurgitation or aspiration increases for patients with conditions resulting in decreased gastric emptying, gastric or bowel obstruction, or lower esophageal sphincter incompetence. Those patients may require longer NPO time periods.⁸ Higher-risk diagnoses and clinical conditions include gastroparesis, trauma, and pregnancy.^5,8,16 Specific risk factors for aspiration in children may include trauma, bowel obstruction, depressed consciousness, shock, or ileus.¹⁰ For surgical emergencies, balance the risk of surgical delay vs perceived aspiration risk.

Use evidence-based guidelines to assess periprocedural aspiration risk. The ASA guidelines suggest that healthy, nonpregnant patients should fast for 8 hours after heavy meals, 6 hours after a light, nonfatty meal, and 2 hours after clear liquids (eg, water, fruit juices without pulp, carbonated beverages, black coffee).¹² Focus on the type of food or drink rather than the volume ingested.¹² Additionally, patients should ingest, with small amounts of clear fluids, appropriate home medications for acute and chronic conditions regardless of NPO status.

While procedure delays or cancellations for any reason upset patients and families and can disrupt the flow of the operating room and procedural suite, we can achieve the delicate balance between efficiency and patient safety and comfort. Since complex inpatient procedural scheduling may not allow for liberalization of solids requiring 6 to 8 hours of fasting time, focus on liberalizing liquids 2 hours prior to anesthesia. This allows staff to minimize the time low-risk patients fast while still maintaining flexibility for operating room case scheduling. We must promote communication between operating room and floor staff to anticipate timing of procedures each day. Healthcare facilities should aim to achieve time-based preprocedural NPO status as opposed to an arbitrary starting time like midnight.⁴

• Risk stratify patients for anesthesia-related aspiration with the aim of identifying those at low aspiration risk.
• For low-risk patients, adhere to recommended fasting times: 2 hours for a clear carbohydrate beverage, 4 hours for breast milk, 6 hours for a light meal or formula, and 8 hours for a fatty meal.
• For patients not deemed low risk, determine the appropriate length of preprocedural fasting by consulting with the anesthesia and surgical teams.

NPO after midnight represents a low-value and arbitrary practice that leaves patients fasting longer than necessary.^2,3,12 In addition to the 2017 ASA guidelines, newer studies and protocols are improving patient satisfaction, minimizing patient dehydration and electrolyte disturbances, and incorporating enhanced recovery after surgery factors into a better patient experience. Returning to the clinical scenario, the hospitalist team can increase patient satisfaction by focusing on liberalizing clear fluids with a carbohydrate beverage up to 2 hours prior to elective surgery while still allowing for schedule flexibility. For this patient, a 3 pm procedure time would have allowed him to have a light breakfast and carbohydrate beverages until 2 hours prior to anesthesia. Dispose of the antiquated practice of NPO after midnight by maximizing clear fluid intake in accordance with current guidelines prior to sedation and general anesthesia. This change in practice will help to achieve normophysiology and increase patient satisfaction.

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

Disclaimer: The opinions expressed in this article are those of the authors alone and do not reflect the views of the Department of Veterans Affairs. The Veterans Affairs Quality Scholars Program is supported by the Veterans Affairs Office of Academic Affiliations, Washington, DC.

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

The hospitalist admits an 18-year-old man for newly diagnosed granulomatosis with polyangiitis to receive expedited pulse-dose steroids and plasma exchange. After consulting interventional radiology for catheter placement the following day, the hospitalist places a “strict” nil per os (nothing by mouth, NPO) after midnight order. During rounds the following morning, the patient reports that he wants to eat. At 9 am, interventional radiology informs the nurse that the line placement will take place at 3 pm. Due to emergencies and other unplanned delays, the catheter placement occurs at 5 pm. The patient and family express their displeasure about the prolonged fasting and ask why this happened.

Hospitalists commonly order “NPO after midnight” diets in anticipation of procedures requiring sedation or general anesthesia. Typically, NPO refers to no food or drink, but in some instances, NPO includes no oral medications. Up to half of medical patients experience some time of fasting while hospitalized.¹ However, NPO practices vary widely across institutions.^2,3 A study from 2014 notes that, on average, patients fast preprocedure for approximately 13.5 hours for solids and 9.6 hours for liquids.² Prolonged fasting times offer little benefit to patients and may lead to frequent patient dissatisfaction and complaints.

In 1883, Sir Joseph Lister described 19th century NPO practices distinguishing solids from liquids, allowing patients “tea or beef tea” until 2 to 3 hours prior to surgery.⁴ However, in 1946, Mendelson published an influential account of 66 pregnant women who aspirated during delivery under general anesthesia.⁵ Two of the 66 patients, both of whom had eaten a full meal 6 to 8 hours prior to general anesthesia, died. The study not only increased awareness of the risk of aspiration with general anesthesia in pregnancy, but it influenced the care for the nonpregnant population of patients as well. By the 1960s, anesthesia texts recommended “NPO after midnight” for both liquids and solids in all patients, regardless of pregnancy status.⁴ To minimize the risk to patients, we have continued to pass down the practice of NPO after midnight to subsequent generations.

Additionally, medical centers and hospitals feel pressure to provide efficient, patient-centered, high-value care. Given the complexity of procedural scheduling and the penalties associated with delays, keeping patients NPO ensures their availability for the next open procedural slot. NPO after midnight orders aim to prevent potential delays in treatment that occur when inadvertent ingestion of food and drink leads to cancellation of procedures.

Recent studies have led to a more sophisticated understanding of gastric emptying and the risks of aspiration during sedation and intubation. Gastric emptying studies routinely show that transit of clear liquids out of the stomach is virtually complete within two hours of drinking.⁶ Age, body mass index, and alcohol have no effect on gastric emptying time, and almost all patients return to preingestion gastric residual volumes within 2 hours of clear liquid consumption.^6,7 While morbidly obese patients tend to have higher gastric fluid volumes after 9 hours of fasting, their stomachs empty at rates similar to nonobese individuals.⁶ Note that, regardless of fasting times, morbid obesity predisposes patients to a higher overall gastric volume and lower pH of gastric contents, which may increase risk of aspiration.⁸ A Cochrane review found no statistical difference in gastric volumes or stomach pH in patients on a standard fast vs shortened (<180 minutes) liquid fast.⁹ The review included nine studies that found patients who consumed a clear liquid beverage had reduced gastric volumes, compared with patients in a fasting state (P < .001).⁹

In a pediatric retrospective study of pulmonary aspiration events, the researchers demonstrated that clinically significant aspiration (presence of bilious secretions in the tracheobronchial airways) occurred at a rate of 0.04% with emergency surgery.¹⁰ Bowel obstruction or ileus accounted for approximately 54% of those cases. Importantly, the reported aspiration rate approximates the rate of pregnant patients from the 1946 Mendelson study of 0.14% (66 out of 44,016), which originally prompted the use of the prolonged NPO status. Based on the Cochrane review of perioperative fasting recommendations for those older than 18 years, consuming fluids more than 90 minutes preoperatively confers a negligible (0 adverse events reported in 9 studies) risk for aspiration or regurgitation events.⁹

In 1998, as a result of these and other similar studies, the American Society of Anesthesiologists (ASA) along with global anesthesia partners adopted guidelines that allowed clear liquids up until 2 hours prior to anesthesia or sedation in low-aspiration-risk patients undergoing elective cases.¹¹ The guidelines allowed for other beverages and food based on their standard transit times (Table). The ASA guidelines do not define low-aspiration-risk patients. Anesthesiologists generally exclude from the low-risk category patients who may have delayed gastric emptying from medical or iatrogenic causes. The updated 2017 ASA guidelines remain unchanged regarding fasting guidelines.¹² Studies suggest that approximately 10% to 20% of NPO after midnight orders are avoidable.^1,3 For those instances, procedures are often deemed not necessary or do not require NPO status.¹

In a study evaluating the reasons that necessary procedures are canceled, only 0.5% of inpatient procedures are cancelled due to the inappropriate ingestion of food or drink.³ In addition, NPO status creates risk. Patients with prolonged NPO status report greater hunger, thirst, tiredness, and weakness prior to surgery when compared with patients receiving a carbohydrate-rich drink 2 hours prior to procedures.^9,13,14 In fact, multiple studies have suggested that preoperative carbohydrate-rich drinks 2 hours before surgery can be associated with decreased insulin resistance in the perioperative period, decreased length of stay, and improvement in perioperative metabolic, cardiac, and psychosomatic status.^9,13-15 These types of studies have informed the enhanced recovery after surgery program, which recommends a carbohydrate beverage 2 to 3 hours prior to surgery.

Prescribe the minimum recommended fasting times only for low-aspiration-risk patients undergoing elective procedures. Risk for regurgitation or aspiration increases for patients with conditions resulting in decreased gastric emptying, gastric or bowel obstruction, or lower esophageal sphincter incompetence. Those patients may require longer NPO time periods.⁸ Higher-risk diagnoses and clinical conditions include gastroparesis, trauma, and pregnancy.^5,8,16 Specific risk factors for aspiration in children may include trauma, bowel obstruction, depressed consciousness, shock, or ileus.¹⁰ For surgical emergencies, balance the risk of surgical delay vs perceived aspiration risk.

Use evidence-based guidelines to assess periprocedural aspiration risk. The ASA guidelines suggest that healthy, nonpregnant patients should fast for 8 hours after heavy meals, 6 hours after a light, nonfatty meal, and 2 hours after clear liquids (eg, water, fruit juices without pulp, carbonated beverages, black coffee).¹² Focus on the type of food or drink rather than the volume ingested.¹² Additionally, patients should ingest, with small amounts of clear fluids, appropriate home medications for acute and chronic conditions regardless of NPO status.

While procedure delays or cancellations for any reason upset patients and families and can disrupt the flow of the operating room and procedural suite, we can achieve the delicate balance between efficiency and patient safety and comfort. Since complex inpatient procedural scheduling may not allow for liberalization of solids requiring 6 to 8 hours of fasting time, focus on liberalizing liquids 2 hours prior to anesthesia. This allows staff to minimize the time low-risk patients fast while still maintaining flexibility for operating room case scheduling. We must promote communication between operating room and floor staff to anticipate timing of procedures each day. Healthcare facilities should aim to achieve time-based preprocedural NPO status as opposed to an arbitrary starting time like midnight.⁴

• Risk stratify patients for anesthesia-related aspiration with the aim of identifying those at low aspiration risk.
• For low-risk patients, adhere to recommended fasting times: 2 hours for a clear carbohydrate beverage, 4 hours for breast milk, 6 hours for a light meal or formula, and 8 hours for a fatty meal.
• For patients not deemed low risk, determine the appropriate length of preprocedural fasting by consulting with the anesthesia and surgical teams.

NPO after midnight represents a low-value and arbitrary practice that leaves patients fasting longer than necessary.^2,3,12 In addition to the 2017 ASA guidelines, newer studies and protocols are improving patient satisfaction, minimizing patient dehydration and electrolyte disturbances, and incorporating enhanced recovery after surgery factors into a better patient experience. Returning to the clinical scenario, the hospitalist team can increase patient satisfaction by focusing on liberalizing clear fluids with a carbohydrate beverage up to 2 hours prior to elective surgery while still allowing for schedule flexibility. For this patient, a 3 pm procedure time would have allowed him to have a light breakfast and carbohydrate beverages until 2 hours prior to anesthesia. Dispose of the antiquated practice of NPO after midnight by maximizing clear fluid intake in accordance with current guidelines prior to sedation and general anesthesia. This change in practice will help to achieve normophysiology and increase patient satisfaction.

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

Disclaimer: The opinions expressed in this article are those of the authors alone and do not reflect the views of the Department of Veterans Affairs. The Veterans Affairs Quality Scholars Program is supported by the Veterans Affairs Office of Academic Affiliations, Washington, DC.

This icon represents the patient’s case. Each paragraph that follows represents the discussant’s thoughts.

An 81-year-old woman with a remote history of left proximal femoral fracture (status post–open reduction and internal fixation) acutely developed severe pain in her left lateral thigh while at her home. A few days prior to her left thigh pain, the patient had routine blood work done. Her lab results (prior to the onset of her symptoms) revealed that her hemoglobin decreased from 10 g/dL, noted 9 months earlier, to 6.6 g/dL. Her primary care physician, who was planning to see the patient for her next regularly scheduled follow-up, was made aware of the patient’s decline in hemoglobin prior to the planned visit. The primary care physician called the patient to inform her about her concerning lab findings and coincidentally became aware of the acute, new-onset left thigh pain. The primary care physician requested that the patient be taken by her daughter to the emergency department (ED) for further evaluation.

The acute decrease in hemoglobin carries a broad differential and may or may not be related to the subsequent development of thigh pain. The presentation of an acute onset of pain in the thigh within the context of this patient’s age and gender suggests a femur fracture; this can be osteoporosis-related or a pathologic fracture associated with malignancy. Several malignancies are plausible, including multiple myeloma (given the anemia) or breast cancer. The proximal part of long bones is the most common site of pathologic fractures, and the femur accounts for half of these cases. Plain radiographs would be appropriate initial imaging and may be followed by either a computed tomography (CT) scan or magnetic resonance imaging (MRI).

In the ED, she denied any recent trauma, hemoptysis, recent dark or bloody stools, vaginal bleeding, abdominal pain, or history of gastric ulcers. She had not experienced any similar episodes of thigh pain in the past. She had a history of atrial fibrillation, hypertension, diabetes mellitus type 2 with diabetic retinopathy and peripheral neuropathy, osteoporosis, nonalcoholic fatty liver disease (NAFLD), and internal hemorrhoids. Her medications included apixaban, metoprolol succinate, metformin, losartan, sitagliptin, calcium, vitamin D, alendronate, and fish oil. She had mild tenderness to palpation of her thigh, but her exam was otherwise normal. Radiography of the left hip and pelvis showed no acute fracture (Figure 1). An upper and lower endoscopy 3 years prior to her presentation revealed internal hemorrhoids.

The patient is taking apixaban, a direct factor Xa inhibitor. The absence of other obvious sources of bleeding suggests that the cause of anemia and pain is most likely bleeding into the anterior thigh compartment, exacerbated by the underlying anticoagulation. Since there was no trauma preceding this episode, the differential diagnosis must be expanded to include other, less common sources of bleeding, including a vascular anomaly such as a pseudoaneurysm or arteriovenous malformation. While the radiographs were normal, a CT scan or MRI may allow for identification of a fracture, other bone lesion, and/or hematoma.

A complete blood count revealed a hemoglobin of 6.6 g/dL (normal, 11.5-14.1 g/dL) with a mean corpuscular volume of 62 fL (normal, 79-96 fL). A CT scan of the abdomen and pelvis with intravenous contrast (Figure 2) was obtained to evaluate for intra-abdominal hemorrhage and retroperitoneal hematoma; it showed mild abdominal and pelvic ascites, a small right pleural effusion with compressive atelectasis, and generalized anasarca, but no evidence of bleeding. She was administered 2 units of packed red blood cells. Apixaban was held and 40 mg intravenous pantoprazole twice daily was started. Her iron level was 12 µg/dL (normal, 50-170 µg/dL); total iron-binding capacity (TIBC) was 431 µg/dL (normal, 179-378 µg/dL); and ferritin level was 19 ng/mL (normal, 10-204 ng/mL). Her basic metabolic panel, liver enzymes, international normalized ratio, partial thromboplastin time, and folate were normal. Serum vitamin B₁₂ level was 277 pg/mL (normal, 213-816 pg/mL), and the reticulocyte count was 1.7%.

Myopathies can be hereditary or acquired. Hereditary myopathies include congenital myopathies, muscular dystrophies, channelopathies, primary metabolic myopathies, and mitochondrial myopathies. Acquired myopathies include infectious myopathies, inflammatory myopathies, endocrine myopathies, secondary metabolic myopathies, and drug-induced and toxic myopathies. The findings of hemorrhagic myositis and skin edema are very intriguing, especially given their localized features. An overt femur fracture was previously ruled out, and an anterior thigh compartment syndrome was considered less likely after orthopedic surgery consultation. There is no description of the patient taking medications that could cause myopathy (such as statins), and there are also no clinical features suggestive of primary inflammatory myopathy, such as dermatomyositis. Increased suspicion of a focal inflammatory process such as localized scleroderma with regional inflammatory myopathy or another focal myopathy must be considered. The next diagnostic steps would include measuring the creatine kinase level, as well as obtaining an MRI of the leg to assess the nature and extent of the myopathy.

Multidisciplinary involvement, including hematology, rheumatology, and surgery, aided in narrowing the differential diagnosis. On hospital day 10, an MRI of the left thigh was performed for suspicion of diabetic myonecrosis (Figure 4). The MRI revealed a 10 cm × 3.6 cm × 22 cm intramuscular hematoma in the belly of the vastus lateralis muscle with associated soft tissue swelling, overlying subcutaneous edema, and skin thickening that was suggestive of hemorrhagic diabetic myonecrosis with some atypical features. A rheumatology consult was requested to evaluate for possible vasculitis in the left lower extremity, and vasculitis was not considered likely. The diagnosis of diabetic myonecrosis with associated intramuscular hemorrhage secondary to apixaban was made after careful reconsideration of the clinical presentation, imaging and laboratory data, and overall picture. Based on the clinical findings, imaging results, and exclusion of alternative causative pathologies of thigh swelling, no biopsy was performed, as it was not considered necessary to make the diagnosis of diabetic myonecrosis. The patient was discharged on hospital day 11 and was doing well. She followed up with her primary care doctor and has regained normal function of her leg.

Diabetic myonecrosis, or diabetic muscle infarction, is an uncommon nontraumatic myopathy that occurs in patients with diabetes who develop acute, focal muscle pain without recent trauma. In this case, the muscle infarction was further complicated by hemorrhagic transformation. Diabetic myonecrosis is relatively uncommon and a diagnosis made by combining history, examination, and laboratory findings and excluding other alternative conditions.

A clear schema for approaching the patient with acute, nontraumatic myopathies is important in avoiding diagnostic error. One effective schema is to divide myopathy into infectious and noninfectious categories. Causes of infectious myopathy include bacterial infections (eg, pyomyositis), inflammatory damage to muscles associated with viruses (eg, influenza), as well as rarer causes. Bacterial processes tend to be relatively focal and affect a specific muscle group or anatomic compartment, while viral causes are often more diffuse and occur in the context of a systemic viral syndrome. Bacterial causes range in severity, and life-threatening conditions, such as necrotizing soft tissue infection, must be considered. In this case, bacterial causes were less likely given the patient’s lack of fever, leukocytosis, and systemic signs of infection.^1,2 However, these findings are not uniformly sensitive, and clinicians should not exclude potentially life- or limb-threatening infections without thorough evaluation. For example, pyomyositis may present without fever in the subacute stage, without leukocytosis if the patient is immunocompromised, and without overt pus if the infection is not in the suppurative stage.³ Viral causes were made less likely in this patient given the lack of a current or recent systemic viral syndrome.

Once infectious etiologies are deemed unlikely, noninfectious etiologies for nontraumatic myopathies should be considered. Some causes of noninfectious myopathy present with the muscle symptoms as a predominant feature, while others present in the context of another illness such as cancer, metabolic disorders, or other systemic disorders. Many noninfectious causes of myopathy associated with systemic illnesses have diffuse or relatively diffuse symptoms, with pain and/or weakness in multiple muscle groups, often in a bilateral distribution. Such examples include dermatomyositis and polymyositis as well as myositis associated with other rheumatologic conditions. Nontraumatic rhabdomyolysis is diffuse and can occur in association with medications and/or genetic conditions.

Angervall and Stener⁴ first described diabetic myonecrosis in 1965 as tumoriform focal muscular degeneration due to diabetic microangiopathy. The most commonly affected muscle groups in diabetic myonecrosis are the anterior thigh, calf, and posterior thigh, followed by muscles in the upper extremities.⁵ Patients with diabetic myonecrosis have an overall mean age at presentation of 44.6 years; affected patients with type 1 diabetes mellitus present at a mean age nearly 20 years younger than those with type 2 diabetes mellitus (35.9 years vs 52.2 years, respectively).⁶ Patients tend to have a long (often >15 years) history of diabetes with microvascular complications such as retinopathy (reported in 71%), nephropathy (reported in 57%), and/or neuropathy (reported in 55%).⁷

The mainstay of the diagnosis of diabetic myonecrosis is a thorough history and physical examination and imaging. Routine laboratory evaluation is relatively unhelpful in diagnosing diabetic myonecrosis, but appropriate imaging can provide valuable supportive information. A CT scan and MRI are both helpful in excluding other etiologies as well as identifying features consistent with diabetic myonecrosis. A CT scan can help exclude a localized abscess, tumor, or bone destruction and, in affected patients, may show increased subcutaneous attenuation and increased muscle size with decreased attenuation secondary to edema.² However, a CT scan may not give optimal assessment of muscle tissue, and therefore MRI may need to be considered. MRI T2 images have a sensitivity nearing 90% for detecting myonecrosis.¹ The diagnostic value of MRI often obviates the need for muscle biopsy.

Spontaneous infarction with hemorrhagic features seen on imaging can be explained by a combination of damage from atherosclerotic or microvascular disease, an activated coagulation cascade, and an impaired fibrinolytic pathway.⁸ Hemorrhagic conversion in diabetic myonecrosis appears to be uncommon.⁹ In our case, we suspect that it developed because of the combination of bleeding risk from apixaban and the underlying mechanisms of diabetic myonecrosis.

The treatment of diabetic myonecrosis is mainly supportive, with an emphasis on rest, nonsteroidal anti-inflammatory agents, antiplatelet agents, and strict glycemic control.¹⁰ There is conflicting information about the value of limb immobilization versus active physical therapy as appropriate treatment modalities.¹¹ Patients who present with clinical concern for sepsis or compartment syndrome require consultation for consideration of acute surgical intervention.¹⁰ The short-term prognosis is promising with supportive therapy, but the condition may recur.¹² The recurrence rate may be as high as 40%, with a 2-year mortality of 10%.¹³ Ultimately, patients need to be followed closely in the outpatient setting to reduce the risk of recurrence.

In this patient, the simultaneous occurrence of focal pain and acute blood loss anemia led to a diagnosis of diabetic myonecrosis that was complicated by hemorrhagic conversion, a truly painful coincidence. The patient underwent a thorough evaluation for acute blood loss before the diagnosis was ultimately made. Clinicians should consider diabetic myonecrosis in patients with diabetes who present with acute muscle pain but no evidence of infection.

• Diabetic myonecrosis is an underrecognized entity and should be included in the differential diagnosis for patients with diabetes who present with acute muscle pain and no history of trauma.
• Imaging with CT and/or MRI of the affected region is the mainstay of diagnosis; treatment is predicated on severity and risk factors and can range from conservative therapy to operative intervention.
• Although the prognosis is good in these patients, careful outpatient follow-up is necessary to oversee their recovery to help reduce the risk of recurrence.

The authors thank Dr Vijay Singh for his radiology input on image selection for this manuscript.

This icon represents the patient’s case. Each paragraph that follows represents the discussant’s thoughts.

An 81-year-old woman with a remote history of left proximal femoral fracture (status post–open reduction and internal fixation) acutely developed severe pain in her left lateral thigh while at her home. A few days prior to her left thigh pain, the patient had routine blood work done. Her lab results (prior to the onset of her symptoms) revealed that her hemoglobin decreased from 10 g/dL, noted 9 months earlier, to 6.6 g/dL. Her primary care physician, who was planning to see the patient for her next regularly scheduled follow-up, was made aware of the patient’s decline in hemoglobin prior to the planned visit. The primary care physician called the patient to inform her about her concerning lab findings and coincidentally became aware of the acute, new-onset left thigh pain. The primary care physician requested that the patient be taken by her daughter to the emergency department (ED) for further evaluation.

The acute decrease in hemoglobin carries a broad differential and may or may not be related to the subsequent development of thigh pain. The presentation of an acute onset of pain in the thigh within the context of this patient’s age and gender suggests a femur fracture; this can be osteoporosis-related or a pathologic fracture associated with malignancy. Several malignancies are plausible, including multiple myeloma (given the anemia) or breast cancer. The proximal part of long bones is the most common site of pathologic fractures, and the femur accounts for half of these cases. Plain radiographs would be appropriate initial imaging and may be followed by either a computed tomography (CT) scan or magnetic resonance imaging (MRI).

In the ED, she denied any recent trauma, hemoptysis, recent dark or bloody stools, vaginal bleeding, abdominal pain, or history of gastric ulcers. She had not experienced any similar episodes of thigh pain in the past. She had a history of atrial fibrillation, hypertension, diabetes mellitus type 2 with diabetic retinopathy and peripheral neuropathy, osteoporosis, nonalcoholic fatty liver disease (NAFLD), and internal hemorrhoids. Her medications included apixaban, metoprolol succinate, metformin, losartan, sitagliptin, calcium, vitamin D, alendronate, and fish oil. She had mild tenderness to palpation of her thigh, but her exam was otherwise normal. Radiography of the left hip and pelvis showed no acute fracture (Figure 1). An upper and lower endoscopy 3 years prior to her presentation revealed internal hemorrhoids.

The patient is taking apixaban, a direct factor Xa inhibitor. The absence of other obvious sources of bleeding suggests that the cause of anemia and pain is most likely bleeding into the anterior thigh compartment, exacerbated by the underlying anticoagulation. Since there was no trauma preceding this episode, the differential diagnosis must be expanded to include other, less common sources of bleeding, including a vascular anomaly such as a pseudoaneurysm or arteriovenous malformation. While the radiographs were normal, a CT scan or MRI may allow for identification of a fracture, other bone lesion, and/or hematoma.

A complete blood count revealed a hemoglobin of 6.6 g/dL (normal, 11.5-14.1 g/dL) with a mean corpuscular volume of 62 fL (normal, 79-96 fL). A CT scan of the abdomen and pelvis with intravenous contrast (Figure 2) was obtained to evaluate for intra-abdominal hemorrhage and retroperitoneal hematoma; it showed mild abdominal and pelvic ascites, a small right pleural effusion with compressive atelectasis, and generalized anasarca, but no evidence of bleeding. She was administered 2 units of packed red blood cells. Apixaban was held and 40 mg intravenous pantoprazole twice daily was started. Her iron level was 12 µg/dL (normal, 50-170 µg/dL); total iron-binding capacity (TIBC) was 431 µg/dL (normal, 179-378 µg/dL); and ferritin level was 19 ng/mL (normal, 10-204 ng/mL). Her basic metabolic panel, liver enzymes, international normalized ratio, partial thromboplastin time, and folate were normal. Serum vitamin B₁₂ level was 277 pg/mL (normal, 213-816 pg/mL), and the reticulocyte count was 1.7%.

Myopathies can be hereditary or acquired. Hereditary myopathies include congenital myopathies, muscular dystrophies, channelopathies, primary metabolic myopathies, and mitochondrial myopathies. Acquired myopathies include infectious myopathies, inflammatory myopathies, endocrine myopathies, secondary metabolic myopathies, and drug-induced and toxic myopathies. The findings of hemorrhagic myositis and skin edema are very intriguing, especially given their localized features. An overt femur fracture was previously ruled out, and an anterior thigh compartment syndrome was considered less likely after orthopedic surgery consultation. There is no description of the patient taking medications that could cause myopathy (such as statins), and there are also no clinical features suggestive of primary inflammatory myopathy, such as dermatomyositis. Increased suspicion of a focal inflammatory process such as localized scleroderma with regional inflammatory myopathy or another focal myopathy must be considered. The next diagnostic steps would include measuring the creatine kinase level, as well as obtaining an MRI of the leg to assess the nature and extent of the myopathy.

Multidisciplinary involvement, including hematology, rheumatology, and surgery, aided in narrowing the differential diagnosis. On hospital day 10, an MRI of the left thigh was performed for suspicion of diabetic myonecrosis (Figure 4). The MRI revealed a 10 cm × 3.6 cm × 22 cm intramuscular hematoma in the belly of the vastus lateralis muscle with associated soft tissue swelling, overlying subcutaneous edema, and skin thickening that was suggestive of hemorrhagic diabetic myonecrosis with some atypical features. A rheumatology consult was requested to evaluate for possible vasculitis in the left lower extremity, and vasculitis was not considered likely. The diagnosis of diabetic myonecrosis with associated intramuscular hemorrhage secondary to apixaban was made after careful reconsideration of the clinical presentation, imaging and laboratory data, and overall picture. Based on the clinical findings, imaging results, and exclusion of alternative causative pathologies of thigh swelling, no biopsy was performed, as it was not considered necessary to make the diagnosis of diabetic myonecrosis. The patient was discharged on hospital day 11 and was doing well. She followed up with her primary care doctor and has regained normal function of her leg.

Diabetic myonecrosis, or diabetic muscle infarction, is an uncommon nontraumatic myopathy that occurs in patients with diabetes who develop acute, focal muscle pain without recent trauma. In this case, the muscle infarction was further complicated by hemorrhagic transformation. Diabetic myonecrosis is relatively uncommon and a diagnosis made by combining history, examination, and laboratory findings and excluding other alternative conditions.

A clear schema for approaching the patient with acute, nontraumatic myopathies is important in avoiding diagnostic error. One effective schema is to divide myopathy into infectious and noninfectious categories. Causes of infectious myopathy include bacterial infections (eg, pyomyositis), inflammatory damage to muscles associated with viruses (eg, influenza), as well as rarer causes. Bacterial processes tend to be relatively focal and affect a specific muscle group or anatomic compartment, while viral causes are often more diffuse and occur in the context of a systemic viral syndrome. Bacterial causes range in severity, and life-threatening conditions, such as necrotizing soft tissue infection, must be considered. In this case, bacterial causes were less likely given the patient’s lack of fever, leukocytosis, and systemic signs of infection.^1,2 However, these findings are not uniformly sensitive, and clinicians should not exclude potentially life- or limb-threatening infections without thorough evaluation. For example, pyomyositis may present without fever in the subacute stage, without leukocytosis if the patient is immunocompromised, and without overt pus if the infection is not in the suppurative stage.³ Viral causes were made less likely in this patient given the lack of a current or recent systemic viral syndrome.

Once infectious etiologies are deemed unlikely, noninfectious etiologies for nontraumatic myopathies should be considered. Some causes of noninfectious myopathy present with the muscle symptoms as a predominant feature, while others present in the context of another illness such as cancer, metabolic disorders, or other systemic disorders. Many noninfectious causes of myopathy associated with systemic illnesses have diffuse or relatively diffuse symptoms, with pain and/or weakness in multiple muscle groups, often in a bilateral distribution. Such examples include dermatomyositis and polymyositis as well as myositis associated with other rheumatologic conditions. Nontraumatic rhabdomyolysis is diffuse and can occur in association with medications and/or genetic conditions.

Angervall and Stener⁴ first described diabetic myonecrosis in 1965 as tumoriform focal muscular degeneration due to diabetic microangiopathy. The most commonly affected muscle groups in diabetic myonecrosis are the anterior thigh, calf, and posterior thigh, followed by muscles in the upper extremities.⁵ Patients with diabetic myonecrosis have an overall mean age at presentation of 44.6 years; affected patients with type 1 diabetes mellitus present at a mean age nearly 20 years younger than those with type 2 diabetes mellitus (35.9 years vs 52.2 years, respectively).⁶ Patients tend to have a long (often >15 years) history of diabetes with microvascular complications such as retinopathy (reported in 71%), nephropathy (reported in 57%), and/or neuropathy (reported in 55%).⁷

The mainstay of the diagnosis of diabetic myonecrosis is a thorough history and physical examination and imaging. Routine laboratory evaluation is relatively unhelpful in diagnosing diabetic myonecrosis, but appropriate imaging can provide valuable supportive information. A CT scan and MRI are both helpful in excluding other etiologies as well as identifying features consistent with diabetic myonecrosis. A CT scan can help exclude a localized abscess, tumor, or bone destruction and, in affected patients, may show increased subcutaneous attenuation and increased muscle size with decreased attenuation secondary to edema.² However, a CT scan may not give optimal assessment of muscle tissue, and therefore MRI may need to be considered. MRI T2 images have a sensitivity nearing 90% for detecting myonecrosis.¹ The diagnostic value of MRI often obviates the need for muscle biopsy.

Spontaneous infarction with hemorrhagic features seen on imaging can be explained by a combination of damage from atherosclerotic or microvascular disease, an activated coagulation cascade, and an impaired fibrinolytic pathway.⁸ Hemorrhagic conversion in diabetic myonecrosis appears to be uncommon.⁹ In our case, we suspect that it developed because of the combination of bleeding risk from apixaban and the underlying mechanisms of diabetic myonecrosis.

The treatment of diabetic myonecrosis is mainly supportive, with an emphasis on rest, nonsteroidal anti-inflammatory agents, antiplatelet agents, and strict glycemic control.¹⁰ There is conflicting information about the value of limb immobilization versus active physical therapy as appropriate treatment modalities.¹¹ Patients who present with clinical concern for sepsis or compartment syndrome require consultation for consideration of acute surgical intervention.¹⁰ The short-term prognosis is promising with supportive therapy, but the condition may recur.¹² The recurrence rate may be as high as 40%, with a 2-year mortality of 10%.¹³ Ultimately, patients need to be followed closely in the outpatient setting to reduce the risk of recurrence.

In this patient, the simultaneous occurrence of focal pain and acute blood loss anemia led to a diagnosis of diabetic myonecrosis that was complicated by hemorrhagic conversion, a truly painful coincidence. The patient underwent a thorough evaluation for acute blood loss before the diagnosis was ultimately made. Clinicians should consider diabetic myonecrosis in patients with diabetes who present with acute muscle pain but no evidence of infection.

• Diabetic myonecrosis is an underrecognized entity and should be included in the differential diagnosis for patients with diabetes who present with acute muscle pain and no history of trauma.
• Imaging with CT and/or MRI of the affected region is the mainstay of diagnosis; treatment is predicated on severity and risk factors and can range from conservative therapy to operative intervention.
• Although the prognosis is good in these patients, careful outpatient follow-up is necessary to oversee their recovery to help reduce the risk of recurrence.

The authors thank Dr Vijay Singh for his radiology input on image selection for this manuscript.

This icon represents the patient’s case. Each paragraph that follows represents the discussant’s thoughts.

An 81-year-old woman with a remote history of left proximal femoral fracture (status post–open reduction and internal fixation) acutely developed severe pain in her left lateral thigh while at her home. A few days prior to her left thigh pain, the patient had routine blood work done. Her lab results (prior to the onset of her symptoms) revealed that her hemoglobin decreased from 10 g/dL, noted 9 months earlier, to 6.6 g/dL. Her primary care physician, who was planning to see the patient for her next regularly scheduled follow-up, was made aware of the patient’s decline in hemoglobin prior to the planned visit. The primary care physician called the patient to inform her about her concerning lab findings and coincidentally became aware of the acute, new-onset left thigh pain. The primary care physician requested that the patient be taken by her daughter to the emergency department (ED) for further evaluation.

The acute decrease in hemoglobin carries a broad differential and may or may not be related to the subsequent development of thigh pain. The presentation of an acute onset of pain in the thigh within the context of this patient’s age and gender suggests a femur fracture; this can be osteoporosis-related or a pathologic fracture associated with malignancy. Several malignancies are plausible, including multiple myeloma (given the anemia) or breast cancer. The proximal part of long bones is the most common site of pathologic fractures, and the femur accounts for half of these cases. Plain radiographs would be appropriate initial imaging and may be followed by either a computed tomography (CT) scan or magnetic resonance imaging (MRI).

In the ED, she denied any recent trauma, hemoptysis, recent dark or bloody stools, vaginal bleeding, abdominal pain, or history of gastric ulcers. She had not experienced any similar episodes of thigh pain in the past. She had a history of atrial fibrillation, hypertension, diabetes mellitus type 2 with diabetic retinopathy and peripheral neuropathy, osteoporosis, nonalcoholic fatty liver disease (NAFLD), and internal hemorrhoids. Her medications included apixaban, metoprolol succinate, metformin, losartan, sitagliptin, calcium, vitamin D, alendronate, and fish oil. She had mild tenderness to palpation of her thigh, but her exam was otherwise normal. Radiography of the left hip and pelvis showed no acute fracture (Figure 1). An upper and lower endoscopy 3 years prior to her presentation revealed internal hemorrhoids.

The patient is taking apixaban, a direct factor Xa inhibitor. The absence of other obvious sources of bleeding suggests that the cause of anemia and pain is most likely bleeding into the anterior thigh compartment, exacerbated by the underlying anticoagulation. Since there was no trauma preceding this episode, the differential diagnosis must be expanded to include other, less common sources of bleeding, including a vascular anomaly such as a pseudoaneurysm or arteriovenous malformation. While the radiographs were normal, a CT scan or MRI may allow for identification of a fracture, other bone lesion, and/or hematoma.

A complete blood count revealed a hemoglobin of 6.6 g/dL (normal, 11.5-14.1 g/dL) with a mean corpuscular volume of 62 fL (normal, 79-96 fL). A CT scan of the abdomen and pelvis with intravenous contrast (Figure 2) was obtained to evaluate for intra-abdominal hemorrhage and retroperitoneal hematoma; it showed mild abdominal and pelvic ascites, a small right pleural effusion with compressive atelectasis, and generalized anasarca, but no evidence of bleeding. She was administered 2 units of packed red blood cells. Apixaban was held and 40 mg intravenous pantoprazole twice daily was started. Her iron level was 12 µg/dL (normal, 50-170 µg/dL); total iron-binding capacity (TIBC) was 431 µg/dL (normal, 179-378 µg/dL); and ferritin level was 19 ng/mL (normal, 10-204 ng/mL). Her basic metabolic panel, liver enzymes, international normalized ratio, partial thromboplastin time, and folate were normal. Serum vitamin B₁₂ level was 277 pg/mL (normal, 213-816 pg/mL), and the reticulocyte count was 1.7%.

Myopathies can be hereditary or acquired. Hereditary myopathies include congenital myopathies, muscular dystrophies, channelopathies, primary metabolic myopathies, and mitochondrial myopathies. Acquired myopathies include infectious myopathies, inflammatory myopathies, endocrine myopathies, secondary metabolic myopathies, and drug-induced and toxic myopathies. The findings of hemorrhagic myositis and skin edema are very intriguing, especially given their localized features. An overt femur fracture was previously ruled out, and an anterior thigh compartment syndrome was considered less likely after orthopedic surgery consultation. There is no description of the patient taking medications that could cause myopathy (such as statins), and there are also no clinical features suggestive of primary inflammatory myopathy, such as dermatomyositis. Increased suspicion of a focal inflammatory process such as localized scleroderma with regional inflammatory myopathy or another focal myopathy must be considered. The next diagnostic steps would include measuring the creatine kinase level, as well as obtaining an MRI of the leg to assess the nature and extent of the myopathy.

Multidisciplinary involvement, including hematology, rheumatology, and surgery, aided in narrowing the differential diagnosis. On hospital day 10, an MRI of the left thigh was performed for suspicion of diabetic myonecrosis (Figure 4). The MRI revealed a 10 cm × 3.6 cm × 22 cm intramuscular hematoma in the belly of the vastus lateralis muscle with associated soft tissue swelling, overlying subcutaneous edema, and skin thickening that was suggestive of hemorrhagic diabetic myonecrosis with some atypical features. A rheumatology consult was requested to evaluate for possible vasculitis in the left lower extremity, and vasculitis was not considered likely. The diagnosis of diabetic myonecrosis with associated intramuscular hemorrhage secondary to apixaban was made after careful reconsideration of the clinical presentation, imaging and laboratory data, and overall picture. Based on the clinical findings, imaging results, and exclusion of alternative causative pathologies of thigh swelling, no biopsy was performed, as it was not considered necessary to make the diagnosis of diabetic myonecrosis. The patient was discharged on hospital day 11 and was doing well. She followed up with her primary care doctor and has regained normal function of her leg.

Diabetic myonecrosis, or diabetic muscle infarction, is an uncommon nontraumatic myopathy that occurs in patients with diabetes who develop acute, focal muscle pain without recent trauma. In this case, the muscle infarction was further complicated by hemorrhagic transformation. Diabetic myonecrosis is relatively uncommon and a diagnosis made by combining history, examination, and laboratory findings and excluding other alternative conditions.

A clear schema for approaching the patient with acute, nontraumatic myopathies is important in avoiding diagnostic error. One effective schema is to divide myopathy into infectious and noninfectious categories. Causes of infectious myopathy include bacterial infections (eg, pyomyositis), inflammatory damage to muscles associated with viruses (eg, influenza), as well as rarer causes. Bacterial processes tend to be relatively focal and affect a specific muscle group or anatomic compartment, while viral causes are often more diffuse and occur in the context of a systemic viral syndrome. Bacterial causes range in severity, and life-threatening conditions, such as necrotizing soft tissue infection, must be considered. In this case, bacterial causes were less likely given the patient’s lack of fever, leukocytosis, and systemic signs of infection.^1,2 However, these findings are not uniformly sensitive, and clinicians should not exclude potentially life- or limb-threatening infections without thorough evaluation. For example, pyomyositis may present without fever in the subacute stage, without leukocytosis if the patient is immunocompromised, and without overt pus if the infection is not in the suppurative stage.³ Viral causes were made less likely in this patient given the lack of a current or recent systemic viral syndrome.

Once infectious etiologies are deemed unlikely, noninfectious etiologies for nontraumatic myopathies should be considered. Some causes of noninfectious myopathy present with the muscle symptoms as a predominant feature, while others present in the context of another illness such as cancer, metabolic disorders, or other systemic disorders. Many noninfectious causes of myopathy associated with systemic illnesses have diffuse or relatively diffuse symptoms, with pain and/or weakness in multiple muscle groups, often in a bilateral distribution. Such examples include dermatomyositis and polymyositis as well as myositis associated with other rheumatologic conditions. Nontraumatic rhabdomyolysis is diffuse and can occur in association with medications and/or genetic conditions.

Angervall and Stener⁴ first described diabetic myonecrosis in 1965 as tumoriform focal muscular degeneration due to diabetic microangiopathy. The most commonly affected muscle groups in diabetic myonecrosis are the anterior thigh, calf, and posterior thigh, followed by muscles in the upper extremities.⁵ Patients with diabetic myonecrosis have an overall mean age at presentation of 44.6 years; affected patients with type 1 diabetes mellitus present at a mean age nearly 20 years younger than those with type 2 diabetes mellitus (35.9 years vs 52.2 years, respectively).⁶ Patients tend to have a long (often >15 years) history of diabetes with microvascular complications such as retinopathy (reported in 71%), nephropathy (reported in 57%), and/or neuropathy (reported in 55%).⁷

The mainstay of the diagnosis of diabetic myonecrosis is a thorough history and physical examination and imaging. Routine laboratory evaluation is relatively unhelpful in diagnosing diabetic myonecrosis, but appropriate imaging can provide valuable supportive information. A CT scan and MRI are both helpful in excluding other etiologies as well as identifying features consistent with diabetic myonecrosis. A CT scan can help exclude a localized abscess, tumor, or bone destruction and, in affected patients, may show increased subcutaneous attenuation and increased muscle size with decreased attenuation secondary to edema.² However, a CT scan may not give optimal assessment of muscle tissue, and therefore MRI may need to be considered. MRI T2 images have a sensitivity nearing 90% for detecting myonecrosis.¹ The diagnostic value of MRI often obviates the need for muscle biopsy.

Spontaneous infarction with hemorrhagic features seen on imaging can be explained by a combination of damage from atherosclerotic or microvascular disease, an activated coagulation cascade, and an impaired fibrinolytic pathway.⁸ Hemorrhagic conversion in diabetic myonecrosis appears to be uncommon.⁹ In our case, we suspect that it developed because of the combination of bleeding risk from apixaban and the underlying mechanisms of diabetic myonecrosis.

The treatment of diabetic myonecrosis is mainly supportive, with an emphasis on rest, nonsteroidal anti-inflammatory agents, antiplatelet agents, and strict glycemic control.¹⁰ There is conflicting information about the value of limb immobilization versus active physical therapy as appropriate treatment modalities.¹¹ Patients who present with clinical concern for sepsis or compartment syndrome require consultation for consideration of acute surgical intervention.¹⁰ The short-term prognosis is promising with supportive therapy, but the condition may recur.¹² The recurrence rate may be as high as 40%, with a 2-year mortality of 10%.¹³ Ultimately, patients need to be followed closely in the outpatient setting to reduce the risk of recurrence.

In this patient, the simultaneous occurrence of focal pain and acute blood loss anemia led to a diagnosis of diabetic myonecrosis that was complicated by hemorrhagic conversion, a truly painful coincidence. The patient underwent a thorough evaluation for acute blood loss before the diagnosis was ultimately made. Clinicians should consider diabetic myonecrosis in patients with diabetes who present with acute muscle pain but no evidence of infection.

• Diabetic myonecrosis is an underrecognized entity and should be included in the differential diagnosis for patients with diabetes who present with acute muscle pain and no history of trauma.
• Imaging with CT and/or MRI of the affected region is the mainstay of diagnosis; treatment is predicated on severity and risk factors and can range from conservative therapy to operative intervention.
• Although the prognosis is good in these patients, careful outpatient follow-up is necessary to oversee their recovery to help reduce the risk of recurrence.

The authors thank Dr Vijay Singh for his radiology input on image selection for this manuscript.

The police shooting of Jacob Blake, an unarmed Wisconsin man, during an arrest in August 2020, led to more protests in a summer filled with calls against the unequal application of police force. Outrage grew as it was revealed that Blake, paralyzed from his waist down and not yet convicted of a crime, was still handcuffed to his hospital bed while receiving treatment.¹ To many this seemed unusually cruel, but to those tasked with caring for incarcerated patients, it is all too familiar. Given the high rates of incarceration in the United States and the increased medical needs of this population, caring for those in custody is unavoidable for many physicians and hospitals. Though safety should be paramount, the universal application of metal handcuffs or leg cuffs by law enforcement officials, a process known as shackling, can lead to a variety of harms and should be abandoned.

The United States incarcerates more individuals both in total numbers and per capita than any other country in the world. This is currently believed to be more than two million people on any given day or more than 650 persons per 100,000 population.² Incarceration occurs in jails, which are locally run facilities holding individuals on short sentences or those not yet convicted who are unable to afford bail before their trials (pretrial), or prisons, which are state and federally run facilities that house those with long sentences. When an incarcerated person experiences a medical emergency requiring hospitalization, they are either treated in the correctional facility or transferred to a local hospital for a higher level of care. Some hospitals are equipped with security measures similar to those of a correctional facility, with secure floors or wings dedicated solely to the care of the incarcerated. Secure units are more commonly seen in hospitals associated with prisons rather than local jails. Other hospitals house incarcerated patients in the same rooms as the public population, and thus movement is restricted by other means.³ Most commonly, this is done with a hard metal shackle resembling a handcuff with one end attached to the leg or wrist and the other end attached to the bed. Some agencies require more restraints, often requiring the use of wrist cuffs and leg cuffs concurrently for the entire duration of a patient’s hospitalization.⁴ In our experience, agencies apply these restraints universally, regardless of age, illness, mobility, or pretrial status.

Restraint practices are rooted in a concern for practitioner and public safety and bear merit. A patient from a correctional facility is usually guarded by just one officer in lieu of the multiple security measures at a jail or prison facility. Nonsecured hospitals have become sites of multiple escapes by incarcerated inpatients, given the lack of secured doors and the multiple movements during the admission and discharge processes.⁵ Furthermore, violence against hospital staff is now a focus issue in many hospitals and is no longer accepted as just “part of the job.” In several high-profile incidents, incarcerated inpatients have harmed staff, including one at our own institution, when an incarcerated patient held a makeshift weapon to a student’s throat.⁶

The use of shackles during hospital visits has been challenged in US courts and routinely upheld. In one case, an incarcerated patient with renal failure received injuries after his leg edema was so severe that “at one point the shackles themselves were barely visible.”⁷ Though he was injured, the shackles were determined to have served a penological purpose outside of punishment, such as preventing escape, and the injuries were the result of the patient’s guards not following protocol. British courts have taken a different stance, ruling for an incarcerated patient who challenged the use of cuffs during three outpatient appointments and one inpatient admission.⁸ While the cuffs in the outpatient setting were deemed acceptable (as they were removed during the medical visit itself), they remained during the duration of the inpatient stay. This was deemed in violation of Title I/Article 3 of the Charter of Fundamental Rights of the European Union, Dignity/The right to integrity of the person. One area in US healthcare where shackling has been roundly condemned is the peripartum shackling of pregnant women. Though courts have had a mixed record to challenges, activism and advocacy have led to the banning of the practice in 23 states, though in most states significant exemptions exist.⁹ Through the First Step Act of 2018, the federal government banned peripartum shackling for all federal prisoners, but as most incarcerations are under state or local control, a considerable number of incarcerated pregnant women can legally be shackled during their deliveries.

Legal and safety concerns aside, the shackling of incarcerated patients carries enormous risk. The use of medical restraints in hospitals has decreased over the past few decades, given their proven harms in increasing falls, exacerbating delirium, and increasing the risk of in-hospital death.¹⁰ There is no reason to believe that trading a soft medical restraint for a metal leg or wrist cuff would not confer the same risk. Additionally, metal law enforcement cuffs are not designed with patient safety in mind and have been known to cause specific nerve injuries, or handcuff neuropathy. This can occur when placement is too tight or when a patient struggles against them, as could happen with an agitated or delirious patient. The bar for removal, even briefly for an exam, is also much higher than that of a medical restraint, leading to a greater likelihood that certain aspects of the physical exam, such as gait or strength assessment, may not be adequately performed. In one small survey, British physicians reported often performing an exam while the patient was cuffed and with a guard in the room, despite country guidelines against both practices.¹¹

Additionally, marginalized communities are disproportionately incarcerated and have a fraught and tenuous relationship with the healthcare system. Black patients routinely report greater mistrust than White patients in the outcomes of care and the motivations of physicians, in large part due to past and current discrimination and the medical community’s history of experimentation.¹² A shackled patient may view a treating physician and hospital as complicit with the practice, rather than seeing the practice as something outside of their control. If a patient’s sole interaction with inpatient medicine involves shackling, it risks damaging whatever fragile physician-patient relationship may exist and could delay or limit care even further.

While the universal application of metal handcuffs or leg cuffs ensures low rates of escape or attacks on workers, it does so at the expense of vulnerable individuals. We have cared for an incarcerated elderly woman arrested for multiple traffic violations, a man with severe autism who slipped through the cracks of mental health diversion protocols and ended up in jail, and an arrested delirious man with severe alcohol withdrawal, all shackled with hard shackles on the wrists, legs, or in the final case, both. Safety and the rights of the vulnerable are not mutually exclusive, and we feel the following measures can protect both.

First, the universal application of shackles in the hospitalized incarcerated patient should end. If no alternative security measures are available for high-risk patients, correctional facilities must document their necessity as physicians and nurses are required to do for medical restraints. Hospitals should have processes in place for providers who feel unsafe with an unshackled patient or think a patient is unnecessarily shackled, and collegial discussions about shackling with law enforcement should be the norm. If safe to do so, shackles should routinely be removed for physical exams without question. Since law enforcement officials, rather than the hospitals, make the rules for shackling, this will take some degree of physician and administrative advocacy at the hospital level and legislative advocacy at the local and state levels.

Second, vulnerable populations, such as the elderly, those experiencing a mental health crisis, or others at risk for in-hospital delirium, should never be restrained with hard law enforcement cuffs. Restraint procedures should follow standard medical restraint procedures, and soft restraints should be used if at all possible. Given the high rates of psychiatric illness amongst the incarcerated and the role jails play in filling gaps in psychiatric care, medical admissions for those with mental illness are not rare occasions.

Finally, hospitals routinely taking care of an incarcerated population should seek to build secure units, a move that would dramatically reduce the need for shackling. In several cities, the primary referral hospitals for some of the largest jails in the country do not have units with the proper security to allow for freedom of movement, and thus, shackling persists. Creating secure units will take significant investment on the part of hospital and local authorities, but there is potential for decreasing costs due to consolidating supervision, which would lead to better patient outcomes given the above risks.

Advocating for the health of the incarcerated, even those who have not yet been convicted, is typically not a high priority for the general public. As inpatient physicians, we see the impact universal shackling has on some of our most vulnerable patients and should be their voice where they have none. Advocating for and implementing the above procedures will be a step toward improving patient care while maintaining safety.

The police shooting of Jacob Blake, an unarmed Wisconsin man, during an arrest in August 2020, led to more protests in a summer filled with calls against the unequal application of police force. Outrage grew as it was revealed that Blake, paralyzed from his waist down and not yet convicted of a crime, was still handcuffed to his hospital bed while receiving treatment.¹ To many this seemed unusually cruel, but to those tasked with caring for incarcerated patients, it is all too familiar. Given the high rates of incarceration in the United States and the increased medical needs of this population, caring for those in custody is unavoidable for many physicians and hospitals. Though safety should be paramount, the universal application of metal handcuffs or leg cuffs by law enforcement officials, a process known as shackling, can lead to a variety of harms and should be abandoned.

The United States incarcerates more individuals both in total numbers and per capita than any other country in the world. This is currently believed to be more than two million people on any given day or more than 650 persons per 100,000 population.² Incarceration occurs in jails, which are locally run facilities holding individuals on short sentences or those not yet convicted who are unable to afford bail before their trials (pretrial), or prisons, which are state and federally run facilities that house those with long sentences. When an incarcerated person experiences a medical emergency requiring hospitalization, they are either treated in the correctional facility or transferred to a local hospital for a higher level of care. Some hospitals are equipped with security measures similar to those of a correctional facility, with secure floors or wings dedicated solely to the care of the incarcerated. Secure units are more commonly seen in hospitals associated with prisons rather than local jails. Other hospitals house incarcerated patients in the same rooms as the public population, and thus movement is restricted by other means.³ Most commonly, this is done with a hard metal shackle resembling a handcuff with one end attached to the leg or wrist and the other end attached to the bed. Some agencies require more restraints, often requiring the use of wrist cuffs and leg cuffs concurrently for the entire duration of a patient’s hospitalization.⁴ In our experience, agencies apply these restraints universally, regardless of age, illness, mobility, or pretrial status.

Restraint practices are rooted in a concern for practitioner and public safety and bear merit. A patient from a correctional facility is usually guarded by just one officer in lieu of the multiple security measures at a jail or prison facility. Nonsecured hospitals have become sites of multiple escapes by incarcerated inpatients, given the lack of secured doors and the multiple movements during the admission and discharge processes.⁵ Furthermore, violence against hospital staff is now a focus issue in many hospitals and is no longer accepted as just “part of the job.” In several high-profile incidents, incarcerated inpatients have harmed staff, including one at our own institution, when an incarcerated patient held a makeshift weapon to a student’s throat.⁶

The use of shackles during hospital visits has been challenged in US courts and routinely upheld. In one case, an incarcerated patient with renal failure received injuries after his leg edema was so severe that “at one point the shackles themselves were barely visible.”⁷ Though he was injured, the shackles were determined to have served a penological purpose outside of punishment, such as preventing escape, and the injuries were the result of the patient’s guards not following protocol. British courts have taken a different stance, ruling for an incarcerated patient who challenged the use of cuffs during three outpatient appointments and one inpatient admission.⁸ While the cuffs in the outpatient setting were deemed acceptable (as they were removed during the medical visit itself), they remained during the duration of the inpatient stay. This was deemed in violation of Title I/Article 3 of the Charter of Fundamental Rights of the European Union, Dignity/The right to integrity of the person. One area in US healthcare where shackling has been roundly condemned is the peripartum shackling of pregnant women. Though courts have had a mixed record to challenges, activism and advocacy have led to the banning of the practice in 23 states, though in most states significant exemptions exist.⁹ Through the First Step Act of 2018, the federal government banned peripartum shackling for all federal prisoners, but as most incarcerations are under state or local control, a considerable number of incarcerated pregnant women can legally be shackled during their deliveries.

Legal and safety concerns aside, the shackling of incarcerated patients carries enormous risk. The use of medical restraints in hospitals has decreased over the past few decades, given their proven harms in increasing falls, exacerbating delirium, and increasing the risk of in-hospital death.¹⁰ There is no reason to believe that trading a soft medical restraint for a metal leg or wrist cuff would not confer the same risk. Additionally, metal law enforcement cuffs are not designed with patient safety in mind and have been known to cause specific nerve injuries, or handcuff neuropathy. This can occur when placement is too tight or when a patient struggles against them, as could happen with an agitated or delirious patient. The bar for removal, even briefly for an exam, is also much higher than that of a medical restraint, leading to a greater likelihood that certain aspects of the physical exam, such as gait or strength assessment, may not be adequately performed. In one small survey, British physicians reported often performing an exam while the patient was cuffed and with a guard in the room, despite country guidelines against both practices.¹¹

Additionally, marginalized communities are disproportionately incarcerated and have a fraught and tenuous relationship with the healthcare system. Black patients routinely report greater mistrust than White patients in the outcomes of care and the motivations of physicians, in large part due to past and current discrimination and the medical community’s history of experimentation.¹² A shackled patient may view a treating physician and hospital as complicit with the practice, rather than seeing the practice as something outside of their control. If a patient’s sole interaction with inpatient medicine involves shackling, it risks damaging whatever fragile physician-patient relationship may exist and could delay or limit care even further.

While the universal application of metal handcuffs or leg cuffs ensures low rates of escape or attacks on workers, it does so at the expense of vulnerable individuals. We have cared for an incarcerated elderly woman arrested for multiple traffic violations, a man with severe autism who slipped through the cracks of mental health diversion protocols and ended up in jail, and an arrested delirious man with severe alcohol withdrawal, all shackled with hard shackles on the wrists, legs, or in the final case, both. Safety and the rights of the vulnerable are not mutually exclusive, and we feel the following measures can protect both.

First, the universal application of shackles in the hospitalized incarcerated patient should end. If no alternative security measures are available for high-risk patients, correctional facilities must document their necessity as physicians and nurses are required to do for medical restraints. Hospitals should have processes in place for providers who feel unsafe with an unshackled patient or think a patient is unnecessarily shackled, and collegial discussions about shackling with law enforcement should be the norm. If safe to do so, shackles should routinely be removed for physical exams without question. Since law enforcement officials, rather than the hospitals, make the rules for shackling, this will take some degree of physician and administrative advocacy at the hospital level and legislative advocacy at the local and state levels.

Second, vulnerable populations, such as the elderly, those experiencing a mental health crisis, or others at risk for in-hospital delirium, should never be restrained with hard law enforcement cuffs. Restraint procedures should follow standard medical restraint procedures, and soft restraints should be used if at all possible. Given the high rates of psychiatric illness amongst the incarcerated and the role jails play in filling gaps in psychiatric care, medical admissions for those with mental illness are not rare occasions.

Finally, hospitals routinely taking care of an incarcerated population should seek to build secure units, a move that would dramatically reduce the need for shackling. In several cities, the primary referral hospitals for some of the largest jails in the country do not have units with the proper security to allow for freedom of movement, and thus, shackling persists. Creating secure units will take significant investment on the part of hospital and local authorities, but there is potential for decreasing costs due to consolidating supervision, which would lead to better patient outcomes given the above risks.

Advocating for the health of the incarcerated, even those who have not yet been convicted, is typically not a high priority for the general public. As inpatient physicians, we see the impact universal shackling has on some of our most vulnerable patients and should be their voice where they have none. Advocating for and implementing the above procedures will be a step toward improving patient care while maintaining safety.

The police shooting of Jacob Blake, an unarmed Wisconsin man, during an arrest in August 2020, led to more protests in a summer filled with calls against the unequal application of police force. Outrage grew as it was revealed that Blake, paralyzed from his waist down and not yet convicted of a crime, was still handcuffed to his hospital bed while receiving treatment.¹ To many this seemed unusually cruel, but to those tasked with caring for incarcerated patients, it is all too familiar. Given the high rates of incarceration in the United States and the increased medical needs of this population, caring for those in custody is unavoidable for many physicians and hospitals. Though safety should be paramount, the universal application of metal handcuffs or leg cuffs by law enforcement officials, a process known as shackling, can lead to a variety of harms and should be abandoned.

The United States incarcerates more individuals both in total numbers and per capita than any other country in the world. This is currently believed to be more than two million people on any given day or more than 650 persons per 100,000 population.² Incarceration occurs in jails, which are locally run facilities holding individuals on short sentences or those not yet convicted who are unable to afford bail before their trials (pretrial), or prisons, which are state and federally run facilities that house those with long sentences. When an incarcerated person experiences a medical emergency requiring hospitalization, they are either treated in the correctional facility or transferred to a local hospital for a higher level of care. Some hospitals are equipped with security measures similar to those of a correctional facility, with secure floors or wings dedicated solely to the care of the incarcerated. Secure units are more commonly seen in hospitals associated with prisons rather than local jails. Other hospitals house incarcerated patients in the same rooms as the public population, and thus movement is restricted by other means.³ Most commonly, this is done with a hard metal shackle resembling a handcuff with one end attached to the leg or wrist and the other end attached to the bed. Some agencies require more restraints, often requiring the use of wrist cuffs and leg cuffs concurrently for the entire duration of a patient’s hospitalization.⁴ In our experience, agencies apply these restraints universally, regardless of age, illness, mobility, or pretrial status.

Restraint practices are rooted in a concern for practitioner and public safety and bear merit. A patient from a correctional facility is usually guarded by just one officer in lieu of the multiple security measures at a jail or prison facility. Nonsecured hospitals have become sites of multiple escapes by incarcerated inpatients, given the lack of secured doors and the multiple movements during the admission and discharge processes.⁵ Furthermore, violence against hospital staff is now a focus issue in many hospitals and is no longer accepted as just “part of the job.” In several high-profile incidents, incarcerated inpatients have harmed staff, including one at our own institution, when an incarcerated patient held a makeshift weapon to a student’s throat.⁶

The use of shackles during hospital visits has been challenged in US courts and routinely upheld. In one case, an incarcerated patient with renal failure received injuries after his leg edema was so severe that “at one point the shackles themselves were barely visible.”⁷ Though he was injured, the shackles were determined to have served a penological purpose outside of punishment, such as preventing escape, and the injuries were the result of the patient’s guards not following protocol. British courts have taken a different stance, ruling for an incarcerated patient who challenged the use of cuffs during three outpatient appointments and one inpatient admission.⁸ While the cuffs in the outpatient setting were deemed acceptable (as they were removed during the medical visit itself), they remained during the duration of the inpatient stay. This was deemed in violation of Title I/Article 3 of the Charter of Fundamental Rights of the European Union, Dignity/The right to integrity of the person. One area in US healthcare where shackling has been roundly condemned is the peripartum shackling of pregnant women. Though courts have had a mixed record to challenges, activism and advocacy have led to the banning of the practice in 23 states, though in most states significant exemptions exist.⁹ Through the First Step Act of 2018, the federal government banned peripartum shackling for all federal prisoners, but as most incarcerations are under state or local control, a considerable number of incarcerated pregnant women can legally be shackled during their deliveries.

Legal and safety concerns aside, the shackling of incarcerated patients carries enormous risk. The use of medical restraints in hospitals has decreased over the past few decades, given their proven harms in increasing falls, exacerbating delirium, and increasing the risk of in-hospital death.¹⁰ There is no reason to believe that trading a soft medical restraint for a metal leg or wrist cuff would not confer the same risk. Additionally, metal law enforcement cuffs are not designed with patient safety in mind and have been known to cause specific nerve injuries, or handcuff neuropathy. This can occur when placement is too tight or when a patient struggles against them, as could happen with an agitated or delirious patient. The bar for removal, even briefly for an exam, is also much higher than that of a medical restraint, leading to a greater likelihood that certain aspects of the physical exam, such as gait or strength assessment, may not be adequately performed. In one small survey, British physicians reported often performing an exam while the patient was cuffed and with a guard in the room, despite country guidelines against both practices.¹¹

Additionally, marginalized communities are disproportionately incarcerated and have a fraught and tenuous relationship with the healthcare system. Black patients routinely report greater mistrust than White patients in the outcomes of care and the motivations of physicians, in large part due to past and current discrimination and the medical community’s history of experimentation.¹² A shackled patient may view a treating physician and hospital as complicit with the practice, rather than seeing the practice as something outside of their control. If a patient’s sole interaction with inpatient medicine involves shackling, it risks damaging whatever fragile physician-patient relationship may exist and could delay or limit care even further.

While the universal application of metal handcuffs or leg cuffs ensures low rates of escape or attacks on workers, it does so at the expense of vulnerable individuals. We have cared for an incarcerated elderly woman arrested for multiple traffic violations, a man with severe autism who slipped through the cracks of mental health diversion protocols and ended up in jail, and an arrested delirious man with severe alcohol withdrawal, all shackled with hard shackles on the wrists, legs, or in the final case, both. Safety and the rights of the vulnerable are not mutually exclusive, and we feel the following measures can protect both.

First, the universal application of shackles in the hospitalized incarcerated patient should end. If no alternative security measures are available for high-risk patients, correctional facilities must document their necessity as physicians and nurses are required to do for medical restraints. Hospitals should have processes in place for providers who feel unsafe with an unshackled patient or think a patient is unnecessarily shackled, and collegial discussions about shackling with law enforcement should be the norm. If safe to do so, shackles should routinely be removed for physical exams without question. Since law enforcement officials, rather than the hospitals, make the rules for shackling, this will take some degree of physician and administrative advocacy at the hospital level and legislative advocacy at the local and state levels.

Second, vulnerable populations, such as the elderly, those experiencing a mental health crisis, or others at risk for in-hospital delirium, should never be restrained with hard law enforcement cuffs. Restraint procedures should follow standard medical restraint procedures, and soft restraints should be used if at all possible. Given the high rates of psychiatric illness amongst the incarcerated and the role jails play in filling gaps in psychiatric care, medical admissions for those with mental illness are not rare occasions.

Finally, hospitals routinely taking care of an incarcerated population should seek to build secure units, a move that would dramatically reduce the need for shackling. In several cities, the primary referral hospitals for some of the largest jails in the country do not have units with the proper security to allow for freedom of movement, and thus, shackling persists. Creating secure units will take significant investment on the part of hospital and local authorities, but there is potential for decreasing costs due to consolidating supervision, which would lead to better patient outcomes given the above risks.

Advocating for the health of the incarcerated, even those who have not yet been convicted, is typically not a high priority for the general public. As inpatient physicians, we see the impact universal shackling has on some of our most vulnerable patients and should be their voice where they have none. Advocating for and implementing the above procedures will be a step toward improving patient care while maintaining safety.

An 88-year-old male veteran with a medical history of chronic obstructive pulmonary disease (COPD) on home oxygen, chronic alcohol use, squamous cell carcinoma of the lung status after left upper lobectomy, and a 5.7 cm thoracic aortic aneurysm was admitted to the inpatient medical service for progressive dyspnea and productive cough. The patient was in his usual state of health until 2 days before presentation. A chest computed tomography scan showed a right lower lobe infiltrate, concerning for pneumonia, and stable thoracic aortic aneurysm (Figure). On admission, the patient was started on IV ceftriaxone 2 g daily for pneumonia and nebulizer therapy of combined albuterol 15 mg and ipratropium 1,500 mg every 6 hours for symptomatic treatment of his dyspnea.

The patient responded well to therapy, and his cough and dyspnea improved. However, 72 hours after admission, he developed an asymptomatic acute kidney injury (AKI) and anion-gap metabolic acidosis. His serum creatinine increased from baseline 0.6 mg/dL to 1.2 mg/dL. He also had an anion gap of 21 mmol/L and a decrease in bicarbonate from 23 mmol/L to 17 mmol/L. His condition was further complicated by new-onset hypertension (153/111 mm Hg). His calculated fractional excretion of sodium (FENa) was 0.5%, and his lactate level returned elevated at 3.6 mmol/L. On further investigation, he reported alcohol use the night prior; however, his β-hydroxybutyrate was negative, and serum alcohol level was undetectable. Meanwhile, the patient continued to receive antibiotics and scheduled nebulizer treatments. Although his AKI resolved with initial fluid resuscitation, his repeat lactate levels continued to trend upward to a peak of 4.0 mmol/L.

• What is your diagnosis?
• How would you treat this patient?

Although IV fluids resolved his AKI, prerenal in etiology given the calculated FENa at 0.5%, his lactate levels continued to uptrend to a peak of 4.0 mmol/L complicated by elevated blood pressure (BP) > 150/100 mm Hg. Given his thoracic aneurysm, his BP was treated with metoprolol tartrate and amlodipine 10 mg daily. The patient remained asymptomatic with no evidence of ischemia or sepsis.

We suspected the nebulizer treatments to be the etiology of the patient’s hyperlactatemia and subsequent anion-gap metabolic acidosis. His scheduled albuterol and ipratropium nebulizer treatments were discontinued, and the patient experienced rapid resolution of his anion gap and hyperlactatemia to 1.2 mmol/L over 24 hours. On discontinuation of the nebulization therapy, mild wheezing was noted on physical examination. The patient reported no symptoms and was at his baseline. The patient finished his antibiotic course for his community-acquired pneumonia and was discharged in stable condition with instructions to continue his previously established home COPD medication regimen of umeclidinium/vilanterol 62.5/25 mcg daily and albuterol metered-dose inhaler as needed.

Discussion

Short-acting β-agonists, such as albuterol, are widely used in COPD and are a guideline-recommended treatment in maintenance and exacerbation of asthma and COPD.¹ Short-acting β-agonist adverse effects (AEs) include nausea, vomiting, tremors, headache, and tachycardia; abnormal laboratory results include hypocalcemia, hypokalemia, hypophosphatemia, hypomagnesemia, and hyperglycemia.^2,3 Albuterol-induced hyperlactatemia and lactic acidosis also are known but often overlooked and underreported AEs.

In a randomized control trial, researchers identified a positive correlation between nebulized albuterol use and hyperlactatemia in asthmatics with asthma exacerbation.⁴ One systematic review identified ≤ 20% of patients on either IV or nebulized high-dose treatments with selective β2-agonists may experience hyperlactatemia.⁵ However, aerosolized administration of albuterol as opposed to IV administration is less likely to result in AEs and abnormal laboratory results given decreased systemic absorption.³

Hyperlactatemia and lactic acidosis are associated with increased morbidity and mortality.⁶ Lactic acidosis is classified as either type A or type B. Type A lactic acidosis is characterized by hypoperfusion as subsequent ischemic injuries lead to anaerobic metabolism and elevated lactate. Diseases such as septic, cardiogenic, and hypovolemic shock are often associated with type A lactic acidosis. Type B lactic acidosis, however, encapsulates all nonhypoperfusion-related elevations in lactate, including malignancy, ethanol intoxication, and medication-induced lactic acidosis.^7,8

In this case, the diagnosis was elusive as the patient had multiple comorbidities. His history included COPD, which is associated with elevated lactate levels.⁵ However, his initial laboratory workup did not show an anion gap, confirming a lack of an underlying acidotic process on admission. Because the patient was admitted for pneumonia, a known infectious source, complicated by an acute elevation in lactate, sepsis must be and was effectively ruled out. The patient also reported alcohol use during his admission, which confounded his presentation but was unlikely to impact the etiology of his lactic acidosis, given the unremarkable β-hydroxybutyrate and serum alcohol levels.

Conclusions

We encourage heightened clinical suspicion of albuterol-induced lactic acidosis in acutely ill patients with COPD on albuterol therapy on rule out of life-threatening etiologies and suggest transitioning patients from scheduled to as-needed albuterol treatments on symptomatic improvement in the clinical course. With such, we hope for improved patient outcomes and the prudent use of health care resources.

An 88-year-old male veteran with a medical history of chronic obstructive pulmonary disease (COPD) on home oxygen, chronic alcohol use, squamous cell carcinoma of the lung status after left upper lobectomy, and a 5.7 cm thoracic aortic aneurysm was admitted to the inpatient medical service for progressive dyspnea and productive cough. The patient was in his usual state of health until 2 days before presentation. A chest computed tomography scan showed a right lower lobe infiltrate, concerning for pneumonia, and stable thoracic aortic aneurysm (Figure). On admission, the patient was started on IV ceftriaxone 2 g daily for pneumonia and nebulizer therapy of combined albuterol 15 mg and ipratropium 1,500 mg every 6 hours for symptomatic treatment of his dyspnea.

The patient responded well to therapy, and his cough and dyspnea improved. However, 72 hours after admission, he developed an asymptomatic acute kidney injury (AKI) and anion-gap metabolic acidosis. His serum creatinine increased from baseline 0.6 mg/dL to 1.2 mg/dL. He also had an anion gap of 21 mmol/L and a decrease in bicarbonate from 23 mmol/L to 17 mmol/L. His condition was further complicated by new-onset hypertension (153/111 mm Hg). His calculated fractional excretion of sodium (FENa) was 0.5%, and his lactate level returned elevated at 3.6 mmol/L. On further investigation, he reported alcohol use the night prior; however, his β-hydroxybutyrate was negative, and serum alcohol level was undetectable. Meanwhile, the patient continued to receive antibiotics and scheduled nebulizer treatments. Although his AKI resolved with initial fluid resuscitation, his repeat lactate levels continued to trend upward to a peak of 4.0 mmol/L.

• What is your diagnosis?
• How would you treat this patient?

Although IV fluids resolved his AKI, prerenal in etiology given the calculated FENa at 0.5%, his lactate levels continued to uptrend to a peak of 4.0 mmol/L complicated by elevated blood pressure (BP) > 150/100 mm Hg. Given his thoracic aneurysm, his BP was treated with metoprolol tartrate and amlodipine 10 mg daily. The patient remained asymptomatic with no evidence of ischemia or sepsis.

We suspected the nebulizer treatments to be the etiology of the patient’s hyperlactatemia and subsequent anion-gap metabolic acidosis. His scheduled albuterol and ipratropium nebulizer treatments were discontinued, and the patient experienced rapid resolution of his anion gap and hyperlactatemia to 1.2 mmol/L over 24 hours. On discontinuation of the nebulization therapy, mild wheezing was noted on physical examination. The patient reported no symptoms and was at his baseline. The patient finished his antibiotic course for his community-acquired pneumonia and was discharged in stable condition with instructions to continue his previously established home COPD medication regimen of umeclidinium/vilanterol 62.5/25 mcg daily and albuterol metered-dose inhaler as needed.

Discussion

Short-acting β-agonists, such as albuterol, are widely used in COPD and are a guideline-recommended treatment in maintenance and exacerbation of asthma and COPD.¹ Short-acting β-agonist adverse effects (AEs) include nausea, vomiting, tremors, headache, and tachycardia; abnormal laboratory results include hypocalcemia, hypokalemia, hypophosphatemia, hypomagnesemia, and hyperglycemia.^2,3 Albuterol-induced hyperlactatemia and lactic acidosis also are known but often overlooked and underreported AEs.

In a randomized control trial, researchers identified a positive correlation between nebulized albuterol use and hyperlactatemia in asthmatics with asthma exacerbation.⁴ One systematic review identified ≤ 20% of patients on either IV or nebulized high-dose treatments with selective β2-agonists may experience hyperlactatemia.⁵ However, aerosolized administration of albuterol as opposed to IV administration is less likely to result in AEs and abnormal laboratory results given decreased systemic absorption.³

Hyperlactatemia and lactic acidosis are associated with increased morbidity and mortality.⁶ Lactic acidosis is classified as either type A or type B. Type A lactic acidosis is characterized by hypoperfusion as subsequent ischemic injuries lead to anaerobic metabolism and elevated lactate. Diseases such as septic, cardiogenic, and hypovolemic shock are often associated with type A lactic acidosis. Type B lactic acidosis, however, encapsulates all nonhypoperfusion-related elevations in lactate, including malignancy, ethanol intoxication, and medication-induced lactic acidosis.^7,8

In this case, the diagnosis was elusive as the patient had multiple comorbidities. His history included COPD, which is associated with elevated lactate levels.⁵ However, his initial laboratory workup did not show an anion gap, confirming a lack of an underlying acidotic process on admission. Because the patient was admitted for pneumonia, a known infectious source, complicated by an acute elevation in lactate, sepsis must be and was effectively ruled out. The patient also reported alcohol use during his admission, which confounded his presentation but was unlikely to impact the etiology of his lactic acidosis, given the unremarkable β-hydroxybutyrate and serum alcohol levels.

Conclusions

We encourage heightened clinical suspicion of albuterol-induced lactic acidosis in acutely ill patients with COPD on albuterol therapy on rule out of life-threatening etiologies and suggest transitioning patients from scheduled to as-needed albuterol treatments on symptomatic improvement in the clinical course. With such, we hope for improved patient outcomes and the prudent use of health care resources.

An 88-year-old male veteran with a medical history of chronic obstructive pulmonary disease (COPD) on home oxygen, chronic alcohol use, squamous cell carcinoma of the lung status after left upper lobectomy, and a 5.7 cm thoracic aortic aneurysm was admitted to the inpatient medical service for progressive dyspnea and productive cough. The patient was in his usual state of health until 2 days before presentation. A chest computed tomography scan showed a right lower lobe infiltrate, concerning for pneumonia, and stable thoracic aortic aneurysm (Figure). On admission, the patient was started on IV ceftriaxone 2 g daily for pneumonia and nebulizer therapy of combined albuterol 15 mg and ipratropium 1,500 mg every 6 hours for symptomatic treatment of his dyspnea.

The patient responded well to therapy, and his cough and dyspnea improved. However, 72 hours after admission, he developed an asymptomatic acute kidney injury (AKI) and anion-gap metabolic acidosis. His serum creatinine increased from baseline 0.6 mg/dL to 1.2 mg/dL. He also had an anion gap of 21 mmol/L and a decrease in bicarbonate from 23 mmol/L to 17 mmol/L. His condition was further complicated by new-onset hypertension (153/111 mm Hg). His calculated fractional excretion of sodium (FENa) was 0.5%, and his lactate level returned elevated at 3.6 mmol/L. On further investigation, he reported alcohol use the night prior; however, his β-hydroxybutyrate was negative, and serum alcohol level was undetectable. Meanwhile, the patient continued to receive antibiotics and scheduled nebulizer treatments. Although his AKI resolved with initial fluid resuscitation, his repeat lactate levels continued to trend upward to a peak of 4.0 mmol/L.

• What is your diagnosis?
• How would you treat this patient?

Although IV fluids resolved his AKI, prerenal in etiology given the calculated FENa at 0.5%, his lactate levels continued to uptrend to a peak of 4.0 mmol/L complicated by elevated blood pressure (BP) > 150/100 mm Hg. Given his thoracic aneurysm, his BP was treated with metoprolol tartrate and amlodipine 10 mg daily. The patient remained asymptomatic with no evidence of ischemia or sepsis.

We suspected the nebulizer treatments to be the etiology of the patient’s hyperlactatemia and subsequent anion-gap metabolic acidosis. His scheduled albuterol and ipratropium nebulizer treatments were discontinued, and the patient experienced rapid resolution of his anion gap and hyperlactatemia to 1.2 mmol/L over 24 hours. On discontinuation of the nebulization therapy, mild wheezing was noted on physical examination. The patient reported no symptoms and was at his baseline. The patient finished his antibiotic course for his community-acquired pneumonia and was discharged in stable condition with instructions to continue his previously established home COPD medication regimen of umeclidinium/vilanterol 62.5/25 mcg daily and albuterol metered-dose inhaler as needed.

Discussion

Short-acting β-agonists, such as albuterol, are widely used in COPD and are a guideline-recommended treatment in maintenance and exacerbation of asthma and COPD.¹ Short-acting β-agonist adverse effects (AEs) include nausea, vomiting, tremors, headache, and tachycardia; abnormal laboratory results include hypocalcemia, hypokalemia, hypophosphatemia, hypomagnesemia, and hyperglycemia.^2,3 Albuterol-induced hyperlactatemia and lactic acidosis also are known but often overlooked and underreported AEs.

In a randomized control trial, researchers identified a positive correlation between nebulized albuterol use and hyperlactatemia in asthmatics with asthma exacerbation.⁴ One systematic review identified ≤ 20% of patients on either IV or nebulized high-dose treatments with selective β2-agonists may experience hyperlactatemia.⁵ However, aerosolized administration of albuterol as opposed to IV administration is less likely to result in AEs and abnormal laboratory results given decreased systemic absorption.³

Hyperlactatemia and lactic acidosis are associated with increased morbidity and mortality.⁶ Lactic acidosis is classified as either type A or type B. Type A lactic acidosis is characterized by hypoperfusion as subsequent ischemic injuries lead to anaerobic metabolism and elevated lactate. Diseases such as septic, cardiogenic, and hypovolemic shock are often associated with type A lactic acidosis. Type B lactic acidosis, however, encapsulates all nonhypoperfusion-related elevations in lactate, including malignancy, ethanol intoxication, and medication-induced lactic acidosis.^7,8

In this case, the diagnosis was elusive as the patient had multiple comorbidities. His history included COPD, which is associated with elevated lactate levels.⁵ However, his initial laboratory workup did not show an anion gap, confirming a lack of an underlying acidotic process on admission. Because the patient was admitted for pneumonia, a known infectious source, complicated by an acute elevation in lactate, sepsis must be and was effectively ruled out. The patient also reported alcohol use during his admission, which confounded his presentation but was unlikely to impact the etiology of his lactic acidosis, given the unremarkable β-hydroxybutyrate and serum alcohol levels.

Conclusions

We encourage heightened clinical suspicion of albuterol-induced lactic acidosis in acutely ill patients with COPD on albuterol therapy on rule out of life-threatening etiologies and suggest transitioning patients from scheduled to as-needed albuterol treatments on symptomatic improvement in the clinical course. With such, we hope for improved patient outcomes and the prudent use of health care resources.

Delirium is a condition commonly exhibited by hospitalized patients and by those who are approaching the end of life.¹ Patients who experience a disturbance in attention that develops over a relatively short period and represents an acute change may have delirium.² Furthermore, there is often an additional cognitive disturbance, such as disorientation, memory deficit, language deficits, visuospatial deficit, or perception. Terminal delirium is defined as delirium that occurs in the dying process and implies that reversal is less likely.³ When death is anticipated, diagnostic workups are not recommended, and treatment of the physiologic abnormalities that contribute to delirium is generally ineffective.⁴

Background

Delirium is often underdiagnosed and undetected by the clinician. Some studies have shown that delirium is not detected in 22 to 50% of cases.⁵ Factors that contribute to the underdetection of delirium include preexisting dementia, older age, presence of visual or hearing impairment, and hypoactive presentation of delirium. Other possible reasons for nondetection of delirium are its fluctuating nature and lack of formal cognitive assessment as part of a routine screening across care settings.⁵ Another study found that 41% of health care providers (HCPs) felt that screening for delirium was burdensome.⁶

To date, there are no veteran-focused studies that investigate prevalence or risk factors for terminal delirium in US Department of Veterans Affairs (VA) long-term care hospice units. Most long-term care hospice units in the VA are in community living centers (CLCs) that follow regulatory guidelines for using antipsychotic medications. The Centers for Medicare and Medicaid Services state that if antipsychotics are prescribed, documentation must clearly show the indication for the antipsychotic medication, the multiple attempts to implement planned care, nonpharmacologic approaches, and ongoing evaluation of the effectiveness of these interventions.⁷ The symptoms of terminal delirium cause significant distress to patients, family and caregivers, and nursing staff. Literature suggests that delirium poses significant relational challenges for patients, families, and HCPs in end-of-life situations.^8,9 We hypothesize that the early identification of risk factors for the development of terminal delirium in this population may lead to increased use of nonpharmacologic measures to prevent terminal delirium, increase nursing vigilance for development of symptoms, and reduce symptom burden should terminal delirium develop.

Prevalence of delirium in the long-term care setting has ranged between 1.4 and 70.3%.¹⁰ The rate was found to be much higher in institutionalized populations compared with that of patients classified as at-home. In a study of the prevalence, severity, and natural history of neuropsychiatric syndromes in terminally ill veterans enrolled in community hospice, delirium was found to be present in only 4.1% on the initial visit and 42.5% during last visit. Also, more than half had at least 1 episode of delirium during the 90-day study period.¹¹ In a study of the prevalence of delirium in terminal cancer patients admitted to hospice, 80% experienced delirium in their final days.¹²

Risk factors for the development of delirium that have been identified in actively dying patients include bowel or bladder obstruction, fluid and electrolyte imbalances, suboptimal pain management, medication adverse effects and toxicity (eg, benzodiazepines, opioids, anticholinergics, and steroids), the addition of ≥ 3 medications, infection, hepatic and renal failure, poor glycemic control, hypoxia, and hematologic disturbances.^4,5,13 A high percentage of patients with a previous diagnosis of dementia were found to exhibit terminal delirium.¹⁴

There are 2 major subtypes of delirium: hyperactive and hypoactive.⁴ Patients with hypoactive delirium exhibit lethargy, reduced motor activity, lack of interest, and/or incoherent speech. There is currently little evidence to guide the treatment of hypoactive delirium. By contrast, hyperactive delirium is associated with hallucinations, agitation, heightened arousal, and inappropriate behavior. Many studies suggest both nonpharmacologic and pharmacologic treatment modalities for the treatment of hyperactive delirium.^4,13 Nonpharmacologic interventions may minimize the risk and severity of symptoms associated with delirium. Current guidelines recommend these interventions before pharmacologic treatment.⁴ Nonpharmacologic interventions include but are not limited to the following: engaging the patient in mentally stimulating activities; surrounding the patient with familiar materials (eg, photos); ensuring that all individuals identify themselves when they encounter a patient; minimizing the intensity of stimulation, providing family or volunteer presence, soft lighting and warm blankets; and ensuring the patient uses hearing aids and glasses if needed.^4,14

Although there are no US Food and Drug Administration-approved medications to treat hyperactive delirium, first-generation antipsychotics (eg, haloperidol, chlorpromazine) are considered the first-line treatment for patients exhibiting psychosis and psychomotor agitation.^3,4,14-16 In terminally ill patients, there is limited evidence from clinical trials to support the efficacy of drug therapy.¹⁴ One study showed lack of efficacy with hydration and opioid rotation.¹⁷ In terminally ill patients experiencing hyperactive delirium, there is a significant increased risk of muscle tension, myoclonic seizures, and distress to the patient, family, and caregiver.¹ Benzodiazepines can be considered first-line treatment for dying patients with terminal delirium in which the goals of treatment are to relieve muscle tension, ensure amnesia, reduce the risk of seizures, and decrease psychosis and agitation.^18,19 Furthermore, in patients with history of alcohol misuse who are experiencing terminal delirium, benzodiazepines also may be the preferred pharmacologic treatment.²⁰ Caution must be exercised with the use of benzodiazepines because they can also cause oversedation, increased confusion, and/or a paradoxical worsening of delirium.^3,4,14

Methods

This was a retrospective case-control study of patients who died in the Edward Hines Jr. Veterans Affairs Hospital CLC in Hines, Illinois, under the treating specialty nursing home hospice from October 1, 2013 to September 30, 2015. Due to the retrospective nature of this trial, the use of antipsychotics within the last 2 weeks of life was a surrogate marker for development of terminal delirium. Cases were defined as patients who were treated with antipsychotics for terminal delirium within the last 2 weeks of their lives. Controls were defined as patients who were not treated with antipsychotics for terminal delirium within the last 2 weeks of their lives. Living hospice patients and patients who were discharged from the CLC before death were excluded.

The goals of this study were to (1) determine risk factors in the VA CLC hospice veteran population for the development of terminal delirium; (2) evaluate documentation by the nursing staff of nonpharmacologic interventions and indications for antipsychotic use in the treatment of terminal delirium; and (3) examine the current usage patterns of antipsychotics for the treatment of terminal delirium.

Veterans’ medical records were reviewed from 2 weeks before death until the recorded death date. Factors that were assessed included age, war era of service, date of death, terminal diagnosis, time interval from cancer diagnosis to death, comorbid conditions, prescribed antipsychotic medications, and other medications potentially contributing to delirium. Nursing documentation was reviewed for indications for administration of antipsychotic medications and nonpharmacologic interventions used to mitigate the symptoms of terminal delirium.

Statistical analysis was conducted in SAS Version 9.3. Cases were compared with controls using univariate and multivariate statistics as appropriate. Comparisons for continuous variables (eg, age) were conducted with Student t tests. Categorical variables (eg, PTSD diagnosis) were compared using χ² analysis or Fisher exact test as appropriate. Variables with a P value < .1 in the univariate analysis were included in logistic regression models. Independent variables were removed from the models, using a backward selection process. Interaction terms were tested based on significance and clinical relevance. A P value < .05 was considered statistically significant.

Results

From October 1, 2013 to September 30, 2015, 307 patients were analyzed for inclusion in this study. Within this population, 186 received antipsychotic medications for the treatment of terminal delirium (cases), while 90 did not receive antipsychotics (controls). Of the 31 excluded patients, 13 were discharged to receive home hospice care, 11 were discharged to community nursing homes, 5 died in acute care units of Edward Hines, Jr. VA Hospital, and 2 died outside of the study period.

The mean age of all included patients was 75.5 years, and the most common terminal diagnosis was cancer, which occurred in 156 patients (56.5%) (Table 1). The baseline characteristics were similar between the cases and controls, including war era of veteran, terminal diagnosis, and comorbid conditions. The mean time between cancer diagnosis and death was not notably longer in the control group compared with that of the case group (25 vs 16 mo, respectively). There was no statistically significant difference in terminal diagnoses between cases and controls. Veterans in the control group spent more days (mean [SD]) in the hospice unit compared with veterans who experienced terminal delirium (48.5 [168.4] vs 28.2 [46.9]; P = .01). Patients with suspected infections were more likely found in the control group (P = .04; odds ratio [OR] = 1.70; 95% CI, 1.02-2.82).

Several risk factors for terminal delirium were identified in this veteran population. Veterans with a history of drug or alcohol abuse were found to be at a significantly higher risk for terminal delirium (P = .04; OR, 1.87; 95% CI, 1.03-3.37). As noted in previous studies, steroid use (P = .01; OR, 2.57; 95% CI, 1.26-5.22); opioids (P = .007; OR, 5.94; 95% CI, 1.54-22.99), and anticholinergic medications (P = .01; OR, 2.06; 95% CI, 1.21-3.52) also increased the risk of delirium (Table 2).

Discussion

Terminal delirium is experienced by many individuals in their last days to weeks of life. Symptoms can present as hyperactive (eg, agitation, hallucinations, heightened arousal) or hypoactive (lethargy, reduced motor activity, incoherent speech). Hyperactive terminal delirium is particularly problematic because it causes increased distress to the patient, family, and caregivers. Delirium can lead to safety concerns, such as fall risk, due to patients’ decreased insight into functional decline.

Many studies suggest both nonpharmacologic and pharmacologic treatments for nonterminal delirium that may also apply to terminal delirium. Nonpharmacologic methods, such as providing a quiet and familiar environment, relieving urinary retention or constipation, and attending to sensory deficits may help prevent or minimize delirium. Pharmacologic interventions, such as antipsychotics or benzodiazepines, may benefit when other modalities have failed to assuage distressing symptoms of delirium. Because hypoactive delirium is usually accompanied by somnolence and reduced motor activity, medication is most often administered to individuals with hyperactive delirium.

The VA provides long-term care hospice beds in their CLCs for veterans who are nearing end of life and have inadequate caregiver support for comprehensive end-of-life care in the home (Case Presentation). Because of their military service and other factors common in their life histories, they may have a unique set of characteristics that are predictive of developing terminal delirium. Awareness of the propensity for terminal delirium will allow for early identification of symptoms, timely initiation of nonpharmacologic interventions, and potentially a decreased need for use of antipsychotic medications.

Limitations

Limitations to the current study include hyperactive delirium that was misinterpreted and treated as pain; the probable underreporting of hypoactive delirium and associated symptoms; the use of antipsychotics as a surrogate marker for the development of terminal delirium; and lack of nursing documentation of assessment and interventions of terminal delirium. In addition, the total milligrams of antipsychotics administered per patient were not collected. Finally, there was the potential that other risk factors were not identified due to low numbers of veterans with certain diagnoses (eg, dementia).

Conclusions

Based on the findings in this study, several steps have been implemented to enhance the care of veterans under hospice care in this CLC: (1) Nurses providing direct patient care have been educated on the assessment by use of the mRASS and treatment of terminal delirium;²² (2) A hospice delirium note template has been created that details symptoms of terminal delirium, nonpharmacologic interventions, the use of antipsychotic medications if indicated, and the outcome of interventions; (3) Providers (eg, physician, advanced practice nurses) review each veteran’s medical history for the risk factors noted above; (4) Any risk factor(s) identified by this study will lead to a nursing order for delirium precautions, which requires completion of the delirium note template by nurses each shift.

The goal for this enhanced process is to identify veterans at risk for terminal delirium, observe changes that may indicate the onset of delirium, and intervene promptly to decrease symptom burden and improve quality of life and safety. Potentially, there will be less requirement for the use of antipsychotic medications to control the more severe symptoms of terminal delirium. A future study will evaluate the outcome of this enhanced process for the assessment and treatment of terminal delirium in this veteran population.

Acknowledgment

We thank Martin J. Gorbien, MD, associate chief of staff of Geriatrics and Extended Care, for his continued support throughout this project.

Delirium is a condition commonly exhibited by hospitalized patients and by those who are approaching the end of life.¹ Patients who experience a disturbance in attention that develops over a relatively short period and represents an acute change may have delirium.² Furthermore, there is often an additional cognitive disturbance, such as disorientation, memory deficit, language deficits, visuospatial deficit, or perception. Terminal delirium is defined as delirium that occurs in the dying process and implies that reversal is less likely.³ When death is anticipated, diagnostic workups are not recommended, and treatment of the physiologic abnormalities that contribute to delirium is generally ineffective.⁴

Background

Delirium is often underdiagnosed and undetected by the clinician. Some studies have shown that delirium is not detected in 22 to 50% of cases.⁵ Factors that contribute to the underdetection of delirium include preexisting dementia, older age, presence of visual or hearing impairment, and hypoactive presentation of delirium. Other possible reasons for nondetection of delirium are its fluctuating nature and lack of formal cognitive assessment as part of a routine screening across care settings.⁵ Another study found that 41% of health care providers (HCPs) felt that screening for delirium was burdensome.⁶

To date, there are no veteran-focused studies that investigate prevalence or risk factors for terminal delirium in US Department of Veterans Affairs (VA) long-term care hospice units. Most long-term care hospice units in the VA are in community living centers (CLCs) that follow regulatory guidelines for using antipsychotic medications. The Centers for Medicare and Medicaid Services state that if antipsychotics are prescribed, documentation must clearly show the indication for the antipsychotic medication, the multiple attempts to implement planned care, nonpharmacologic approaches, and ongoing evaluation of the effectiveness of these interventions.⁷ The symptoms of terminal delirium cause significant distress to patients, family and caregivers, and nursing staff. Literature suggests that delirium poses significant relational challenges for patients, families, and HCPs in end-of-life situations.^8,9 We hypothesize that the early identification of risk factors for the development of terminal delirium in this population may lead to increased use of nonpharmacologic measures to prevent terminal delirium, increase nursing vigilance for development of symptoms, and reduce symptom burden should terminal delirium develop.

Prevalence of delirium in the long-term care setting has ranged between 1.4 and 70.3%.¹⁰ The rate was found to be much higher in institutionalized populations compared with that of patients classified as at-home. In a study of the prevalence, severity, and natural history of neuropsychiatric syndromes in terminally ill veterans enrolled in community hospice, delirium was found to be present in only 4.1% on the initial visit and 42.5% during last visit. Also, more than half had at least 1 episode of delirium during the 90-day study period.¹¹ In a study of the prevalence of delirium in terminal cancer patients admitted to hospice, 80% experienced delirium in their final days.¹²

Risk factors for the development of delirium that have been identified in actively dying patients include bowel or bladder obstruction, fluid and electrolyte imbalances, suboptimal pain management, medication adverse effects and toxicity (eg, benzodiazepines, opioids, anticholinergics, and steroids), the addition of ≥ 3 medications, infection, hepatic and renal failure, poor glycemic control, hypoxia, and hematologic disturbances.^4,5,13 A high percentage of patients with a previous diagnosis of dementia were found to exhibit terminal delirium.¹⁴

There are 2 major subtypes of delirium: hyperactive and hypoactive.⁴ Patients with hypoactive delirium exhibit lethargy, reduced motor activity, lack of interest, and/or incoherent speech. There is currently little evidence to guide the treatment of hypoactive delirium. By contrast, hyperactive delirium is associated with hallucinations, agitation, heightened arousal, and inappropriate behavior. Many studies suggest both nonpharmacologic and pharmacologic treatment modalities for the treatment of hyperactive delirium.^4,13 Nonpharmacologic interventions may minimize the risk and severity of symptoms associated with delirium. Current guidelines recommend these interventions before pharmacologic treatment.⁴ Nonpharmacologic interventions include but are not limited to the following: engaging the patient in mentally stimulating activities; surrounding the patient with familiar materials (eg, photos); ensuring that all individuals identify themselves when they encounter a patient; minimizing the intensity of stimulation, providing family or volunteer presence, soft lighting and warm blankets; and ensuring the patient uses hearing aids and glasses if needed.^4,14

Although there are no US Food and Drug Administration-approved medications to treat hyperactive delirium, first-generation antipsychotics (eg, haloperidol, chlorpromazine) are considered the first-line treatment for patients exhibiting psychosis and psychomotor agitation.^3,4,14-16 In terminally ill patients, there is limited evidence from clinical trials to support the efficacy of drug therapy.¹⁴ One study showed lack of efficacy with hydration and opioid rotation.¹⁷ In terminally ill patients experiencing hyperactive delirium, there is a significant increased risk of muscle tension, myoclonic seizures, and distress to the patient, family, and caregiver.¹ Benzodiazepines can be considered first-line treatment for dying patients with terminal delirium in which the goals of treatment are to relieve muscle tension, ensure amnesia, reduce the risk of seizures, and decrease psychosis and agitation.^18,19 Furthermore, in patients with history of alcohol misuse who are experiencing terminal delirium, benzodiazepines also may be the preferred pharmacologic treatment.²⁰ Caution must be exercised with the use of benzodiazepines because they can also cause oversedation, increased confusion, and/or a paradoxical worsening of delirium.^3,4,14

Methods

This was a retrospective case-control study of patients who died in the Edward Hines Jr. Veterans Affairs Hospital CLC in Hines, Illinois, under the treating specialty nursing home hospice from October 1, 2013 to September 30, 2015. Due to the retrospective nature of this trial, the use of antipsychotics within the last 2 weeks of life was a surrogate marker for development of terminal delirium. Cases were defined as patients who were treated with antipsychotics for terminal delirium within the last 2 weeks of their lives. Controls were defined as patients who were not treated with antipsychotics for terminal delirium within the last 2 weeks of their lives. Living hospice patients and patients who were discharged from the CLC before death were excluded.

The goals of this study were to (1) determine risk factors in the VA CLC hospice veteran population for the development of terminal delirium; (2) evaluate documentation by the nursing staff of nonpharmacologic interventions and indications for antipsychotic use in the treatment of terminal delirium; and (3) examine the current usage patterns of antipsychotics for the treatment of terminal delirium.

Veterans’ medical records were reviewed from 2 weeks before death until the recorded death date. Factors that were assessed included age, war era of service, date of death, terminal diagnosis, time interval from cancer diagnosis to death, comorbid conditions, prescribed antipsychotic medications, and other medications potentially contributing to delirium. Nursing documentation was reviewed for indications for administration of antipsychotic medications and nonpharmacologic interventions used to mitigate the symptoms of terminal delirium.

Statistical analysis was conducted in SAS Version 9.3. Cases were compared with controls using univariate and multivariate statistics as appropriate. Comparisons for continuous variables (eg, age) were conducted with Student t tests. Categorical variables (eg, PTSD diagnosis) were compared using χ² analysis or Fisher exact test as appropriate. Variables with a P value < .1 in the univariate analysis were included in logistic regression models. Independent variables were removed from the models, using a backward selection process. Interaction terms were tested based on significance and clinical relevance. A P value < .05 was considered statistically significant.

Results

From October 1, 2013 to September 30, 2015, 307 patients were analyzed for inclusion in this study. Within this population, 186 received antipsychotic medications for the treatment of terminal delirium (cases), while 90 did not receive antipsychotics (controls). Of the 31 excluded patients, 13 were discharged to receive home hospice care, 11 were discharged to community nursing homes, 5 died in acute care units of Edward Hines, Jr. VA Hospital, and 2 died outside of the study period.

The mean age of all included patients was 75.5 years, and the most common terminal diagnosis was cancer, which occurred in 156 patients (56.5%) (Table 1). The baseline characteristics were similar between the cases and controls, including war era of veteran, terminal diagnosis, and comorbid conditions. The mean time between cancer diagnosis and death was not notably longer in the control group compared with that of the case group (25 vs 16 mo, respectively). There was no statistically significant difference in terminal diagnoses between cases and controls. Veterans in the control group spent more days (mean [SD]) in the hospice unit compared with veterans who experienced terminal delirium (48.5 [168.4] vs 28.2 [46.9]; P = .01). Patients with suspected infections were more likely found in the control group (P = .04; odds ratio [OR] = 1.70; 95% CI, 1.02-2.82).

Several risk factors for terminal delirium were identified in this veteran population. Veterans with a history of drug or alcohol abuse were found to be at a significantly higher risk for terminal delirium (P = .04; OR, 1.87; 95% CI, 1.03-3.37). As noted in previous studies, steroid use (P = .01; OR, 2.57; 95% CI, 1.26-5.22); opioids (P = .007; OR, 5.94; 95% CI, 1.54-22.99), and anticholinergic medications (P = .01; OR, 2.06; 95% CI, 1.21-3.52) also increased the risk of delirium (Table 2).

Discussion

Terminal delirium is experienced by many individuals in their last days to weeks of life. Symptoms can present as hyperactive (eg, agitation, hallucinations, heightened arousal) or hypoactive (lethargy, reduced motor activity, incoherent speech). Hyperactive terminal delirium is particularly problematic because it causes increased distress to the patient, family, and caregivers. Delirium can lead to safety concerns, such as fall risk, due to patients’ decreased insight into functional decline.

Many studies suggest both nonpharmacologic and pharmacologic treatments for nonterminal delirium that may also apply to terminal delirium. Nonpharmacologic methods, such as providing a quiet and familiar environment, relieving urinary retention or constipation, and attending to sensory deficits may help prevent or minimize delirium. Pharmacologic interventions, such as antipsychotics or benzodiazepines, may benefit when other modalities have failed to assuage distressing symptoms of delirium. Because hypoactive delirium is usually accompanied by somnolence and reduced motor activity, medication is most often administered to individuals with hyperactive delirium.

The VA provides long-term care hospice beds in their CLCs for veterans who are nearing end of life and have inadequate caregiver support for comprehensive end-of-life care in the home (Case Presentation). Because of their military service and other factors common in their life histories, they may have a unique set of characteristics that are predictive of developing terminal delirium. Awareness of the propensity for terminal delirium will allow for early identification of symptoms, timely initiation of nonpharmacologic interventions, and potentially a decreased need for use of antipsychotic medications.

Limitations

Limitations to the current study include hyperactive delirium that was misinterpreted and treated as pain; the probable underreporting of hypoactive delirium and associated symptoms; the use of antipsychotics as a surrogate marker for the development of terminal delirium; and lack of nursing documentation of assessment and interventions of terminal delirium. In addition, the total milligrams of antipsychotics administered per patient were not collected. Finally, there was the potential that other risk factors were not identified due to low numbers of veterans with certain diagnoses (eg, dementia).

Conclusions

Based on the findings in this study, several steps have been implemented to enhance the care of veterans under hospice care in this CLC: (1) Nurses providing direct patient care have been educated on the assessment by use of the mRASS and treatment of terminal delirium;²² (2) A hospice delirium note template has been created that details symptoms of terminal delirium, nonpharmacologic interventions, the use of antipsychotic medications if indicated, and the outcome of interventions; (3) Providers (eg, physician, advanced practice nurses) review each veteran’s medical history for the risk factors noted above; (4) Any risk factor(s) identified by this study will lead to a nursing order for delirium precautions, which requires completion of the delirium note template by nurses each shift.

The goal for this enhanced process is to identify veterans at risk for terminal delirium, observe changes that may indicate the onset of delirium, and intervene promptly to decrease symptom burden and improve quality of life and safety. Potentially, there will be less requirement for the use of antipsychotic medications to control the more severe symptoms of terminal delirium. A future study will evaluate the outcome of this enhanced process for the assessment and treatment of terminal delirium in this veteran population.

Acknowledgment

We thank Martin J. Gorbien, MD, associate chief of staff of Geriatrics and Extended Care, for his continued support throughout this project.

Delirium is a condition commonly exhibited by hospitalized patients and by those who are approaching the end of life.¹ Patients who experience a disturbance in attention that develops over a relatively short period and represents an acute change may have delirium.² Furthermore, there is often an additional cognitive disturbance, such as disorientation, memory deficit, language deficits, visuospatial deficit, or perception. Terminal delirium is defined as delirium that occurs in the dying process and implies that reversal is less likely.³ When death is anticipated, diagnostic workups are not recommended, and treatment of the physiologic abnormalities that contribute to delirium is generally ineffective.⁴

Background

Delirium is often underdiagnosed and undetected by the clinician. Some studies have shown that delirium is not detected in 22 to 50% of cases.⁵ Factors that contribute to the underdetection of delirium include preexisting dementia, older age, presence of visual or hearing impairment, and hypoactive presentation of delirium. Other possible reasons for nondetection of delirium are its fluctuating nature and lack of formal cognitive assessment as part of a routine screening across care settings.⁵ Another study found that 41% of health care providers (HCPs) felt that screening for delirium was burdensome.⁶

To date, there are no veteran-focused studies that investigate prevalence or risk factors for terminal delirium in US Department of Veterans Affairs (VA) long-term care hospice units. Most long-term care hospice units in the VA are in community living centers (CLCs) that follow regulatory guidelines for using antipsychotic medications. The Centers for Medicare and Medicaid Services state that if antipsychotics are prescribed, documentation must clearly show the indication for the antipsychotic medication, the multiple attempts to implement planned care, nonpharmacologic approaches, and ongoing evaluation of the effectiveness of these interventions.⁷ The symptoms of terminal delirium cause significant distress to patients, family and caregivers, and nursing staff. Literature suggests that delirium poses significant relational challenges for patients, families, and HCPs in end-of-life situations.^8,9 We hypothesize that the early identification of risk factors for the development of terminal delirium in this population may lead to increased use of nonpharmacologic measures to prevent terminal delirium, increase nursing vigilance for development of symptoms, and reduce symptom burden should terminal delirium develop.

Prevalence of delirium in the long-term care setting has ranged between 1.4 and 70.3%.¹⁰ The rate was found to be much higher in institutionalized populations compared with that of patients classified as at-home. In a study of the prevalence, severity, and natural history of neuropsychiatric syndromes in terminally ill veterans enrolled in community hospice, delirium was found to be present in only 4.1% on the initial visit and 42.5% during last visit. Also, more than half had at least 1 episode of delirium during the 90-day study period.¹¹ In a study of the prevalence of delirium in terminal cancer patients admitted to hospice, 80% experienced delirium in their final days.¹²

Risk factors for the development of delirium that have been identified in actively dying patients include bowel or bladder obstruction, fluid and electrolyte imbalances, suboptimal pain management, medication adverse effects and toxicity (eg, benzodiazepines, opioids, anticholinergics, and steroids), the addition of ≥ 3 medications, infection, hepatic and renal failure, poor glycemic control, hypoxia, and hematologic disturbances.^4,5,13 A high percentage of patients with a previous diagnosis of dementia were found to exhibit terminal delirium.¹⁴

There are 2 major subtypes of delirium: hyperactive and hypoactive.⁴ Patients with hypoactive delirium exhibit lethargy, reduced motor activity, lack of interest, and/or incoherent speech. There is currently little evidence to guide the treatment of hypoactive delirium. By contrast, hyperactive delirium is associated with hallucinations, agitation, heightened arousal, and inappropriate behavior. Many studies suggest both nonpharmacologic and pharmacologic treatment modalities for the treatment of hyperactive delirium.^4,13 Nonpharmacologic interventions may minimize the risk and severity of symptoms associated with delirium. Current guidelines recommend these interventions before pharmacologic treatment.⁴ Nonpharmacologic interventions include but are not limited to the following: engaging the patient in mentally stimulating activities; surrounding the patient with familiar materials (eg, photos); ensuring that all individuals identify themselves when they encounter a patient; minimizing the intensity of stimulation, providing family or volunteer presence, soft lighting and warm blankets; and ensuring the patient uses hearing aids and glasses if needed.^4,14

Although there are no US Food and Drug Administration-approved medications to treat hyperactive delirium, first-generation antipsychotics (eg, haloperidol, chlorpromazine) are considered the first-line treatment for patients exhibiting psychosis and psychomotor agitation.^3,4,14-16 In terminally ill patients, there is limited evidence from clinical trials to support the efficacy of drug therapy.¹⁴ One study showed lack of efficacy with hydration and opioid rotation.¹⁷ In terminally ill patients experiencing hyperactive delirium, there is a significant increased risk of muscle tension, myoclonic seizures, and distress to the patient, family, and caregiver.¹ Benzodiazepines can be considered first-line treatment for dying patients with terminal delirium in which the goals of treatment are to relieve muscle tension, ensure amnesia, reduce the risk of seizures, and decrease psychosis and agitation.^18,19 Furthermore, in patients with history of alcohol misuse who are experiencing terminal delirium, benzodiazepines also may be the preferred pharmacologic treatment.²⁰ Caution must be exercised with the use of benzodiazepines because they can also cause oversedation, increased confusion, and/or a paradoxical worsening of delirium.^3,4,14

Methods

This was a retrospective case-control study of patients who died in the Edward Hines Jr. Veterans Affairs Hospital CLC in Hines, Illinois, under the treating specialty nursing home hospice from October 1, 2013 to September 30, 2015. Due to the retrospective nature of this trial, the use of antipsychotics within the last 2 weeks of life was a surrogate marker for development of terminal delirium. Cases were defined as patients who were treated with antipsychotics for terminal delirium within the last 2 weeks of their lives. Controls were defined as patients who were not treated with antipsychotics for terminal delirium within the last 2 weeks of their lives. Living hospice patients and patients who were discharged from the CLC before death were excluded.

The goals of this study were to (1) determine risk factors in the VA CLC hospice veteran population for the development of terminal delirium; (2) evaluate documentation by the nursing staff of nonpharmacologic interventions and indications for antipsychotic use in the treatment of terminal delirium; and (3) examine the current usage patterns of antipsychotics for the treatment of terminal delirium.

Veterans’ medical records were reviewed from 2 weeks before death until the recorded death date. Factors that were assessed included age, war era of service, date of death, terminal diagnosis, time interval from cancer diagnosis to death, comorbid conditions, prescribed antipsychotic medications, and other medications potentially contributing to delirium. Nursing documentation was reviewed for indications for administration of antipsychotic medications and nonpharmacologic interventions used to mitigate the symptoms of terminal delirium.

Statistical analysis was conducted in SAS Version 9.3. Cases were compared with controls using univariate and multivariate statistics as appropriate. Comparisons for continuous variables (eg, age) were conducted with Student t tests. Categorical variables (eg, PTSD diagnosis) were compared using χ² analysis or Fisher exact test as appropriate. Variables with a P value < .1 in the univariate analysis were included in logistic regression models. Independent variables were removed from the models, using a backward selection process. Interaction terms were tested based on significance and clinical relevance. A P value < .05 was considered statistically significant.

Results

From October 1, 2013 to September 30, 2015, 307 patients were analyzed for inclusion in this study. Within this population, 186 received antipsychotic medications for the treatment of terminal delirium (cases), while 90 did not receive antipsychotics (controls). Of the 31 excluded patients, 13 were discharged to receive home hospice care, 11 were discharged to community nursing homes, 5 died in acute care units of Edward Hines, Jr. VA Hospital, and 2 died outside of the study period.

The mean age of all included patients was 75.5 years, and the most common terminal diagnosis was cancer, which occurred in 156 patients (56.5%) (Table 1). The baseline characteristics were similar between the cases and controls, including war era of veteran, terminal diagnosis, and comorbid conditions. The mean time between cancer diagnosis and death was not notably longer in the control group compared with that of the case group (25 vs 16 mo, respectively). There was no statistically significant difference in terminal diagnoses between cases and controls. Veterans in the control group spent more days (mean [SD]) in the hospice unit compared with veterans who experienced terminal delirium (48.5 [168.4] vs 28.2 [46.9]; P = .01). Patients with suspected infections were more likely found in the control group (P = .04; odds ratio [OR] = 1.70; 95% CI, 1.02-2.82).

Several risk factors for terminal delirium were identified in this veteran population. Veterans with a history of drug or alcohol abuse were found to be at a significantly higher risk for terminal delirium (P = .04; OR, 1.87; 95% CI, 1.03-3.37). As noted in previous studies, steroid use (P = .01; OR, 2.57; 95% CI, 1.26-5.22); opioids (P = .007; OR, 5.94; 95% CI, 1.54-22.99), and anticholinergic medications (P = .01; OR, 2.06; 95% CI, 1.21-3.52) also increased the risk of delirium (Table 2).

Discussion

Terminal delirium is experienced by many individuals in their last days to weeks of life. Symptoms can present as hyperactive (eg, agitation, hallucinations, heightened arousal) or hypoactive (lethargy, reduced motor activity, incoherent speech). Hyperactive terminal delirium is particularly problematic because it causes increased distress to the patient, family, and caregivers. Delirium can lead to safety concerns, such as fall risk, due to patients’ decreased insight into functional decline.

Many studies suggest both nonpharmacologic and pharmacologic treatments for nonterminal delirium that may also apply to terminal delirium. Nonpharmacologic methods, such as providing a quiet and familiar environment, relieving urinary retention or constipation, and attending to sensory deficits may help prevent or minimize delirium. Pharmacologic interventions, such as antipsychotics or benzodiazepines, may benefit when other modalities have failed to assuage distressing symptoms of delirium. Because hypoactive delirium is usually accompanied by somnolence and reduced motor activity, medication is most often administered to individuals with hyperactive delirium.

The VA provides long-term care hospice beds in their CLCs for veterans who are nearing end of life and have inadequate caregiver support for comprehensive end-of-life care in the home (Case Presentation). Because of their military service and other factors common in their life histories, they may have a unique set of characteristics that are predictive of developing terminal delirium. Awareness of the propensity for terminal delirium will allow for early identification of symptoms, timely initiation of nonpharmacologic interventions, and potentially a decreased need for use of antipsychotic medications.

Limitations

Limitations to the current study include hyperactive delirium that was misinterpreted and treated as pain; the probable underreporting of hypoactive delirium and associated symptoms; the use of antipsychotics as a surrogate marker for the development of terminal delirium; and lack of nursing documentation of assessment and interventions of terminal delirium. In addition, the total milligrams of antipsychotics administered per patient were not collected. Finally, there was the potential that other risk factors were not identified due to low numbers of veterans with certain diagnoses (eg, dementia).

Conclusions

Based on the findings in this study, several steps have been implemented to enhance the care of veterans under hospice care in this CLC: (1) Nurses providing direct patient care have been educated on the assessment by use of the mRASS and treatment of terminal delirium;²² (2) A hospice delirium note template has been created that details symptoms of terminal delirium, nonpharmacologic interventions, the use of antipsychotic medications if indicated, and the outcome of interventions; (3) Providers (eg, physician, advanced practice nurses) review each veteran’s medical history for the risk factors noted above; (4) Any risk factor(s) identified by this study will lead to a nursing order for delirium precautions, which requires completion of the delirium note template by nurses each shift.

The goal for this enhanced process is to identify veterans at risk for terminal delirium, observe changes that may indicate the onset of delirium, and intervene promptly to decrease symptom burden and improve quality of life and safety. Potentially, there will be less requirement for the use of antipsychotic medications to control the more severe symptoms of terminal delirium. A future study will evaluate the outcome of this enhanced process for the assessment and treatment of terminal delirium in this veteran population.

Acknowledgment

We thank Martin J. Gorbien, MD, associate chief of staff of Geriatrics and Extended Care, for his continued support throughout this project.

Preventable errors by health care workers are widespread and cause significant morbidity and mortality. Wrong site surgery (WSS) is a preventable error that causes harm through both the direct insult of surgery and propagation of the untreated initial problem. WSS also can cause poor patient outcomes, low morale, malpractice claims, and increased costs to the health care system. The estimated median prevalence of WSS across all specialties is 9 events per 1,000,000 surgical procedures, and an institutional study of 112,500 surgical procedures reported 1 wrong-site event, which involved removing the incorrect skin lesion and not removing the intended lesion.^1,2

Though the prevalence is low when examining all specialties together, dermatology is also susceptible to WSS.³ Watson and colleagues demonstrated that 31% of intervention errors were due to WSS and suggested that prebiopsy photography helps decrease errors.⁴ Thus, the American Academy of Dermatology has emphasized the importance of reducing WSS.⁵ A study by Nijhawan and colleagues found that 25% of patients receiving Mohs surgery at a private single cancer center could not identify their biopsy location because the duration between biopsy and surgery allowed biopsy sites to heal well, which made finding the lesion difficult.⁶

Risk factors for WSS include having multiple health care providers (HCPs) living remote from the surgery location involved in the case, being a traveling veteran, receiving care at multiple facilities inside and outside the US Department of Veterans Affairs (VA) system, mislabeling photographs or specimens, and photographs not taken at time of biopsy and too close with no frame of reference to assist in finding the correct site. The VA electronic health record (EHR) is not integrated with outside facility EHRs, and the Office of Community Care (OCC) at the VA is responsible for obtaining copies of outside records. If unsuccessful, the HCP and/or patient must provide the records. Frequently, records are not received or require multiple attempts to be obtained. This mostly affects veterans receiving care at multiple facilities inside and outside the VA system as the lack of or timely receipt of past health records could increase the risk for WSS.

To combat WSS, some institutions have implemented standardized protocols requiring photographic documentation of lesions before biopsy so that the surgeon can properly identify the correct site prior to operating.⁷ Fortunately, recent advances in technology have made it easier to provide photographic documentation of skin lesions. Highsmith and colleagues highlighted use of smartphones to avoid WSS in dermatology.⁷ Despite these advances, photographic documentation of lesions is not universal. A study by Rossy and colleagues found that less than half of patients referred for Mohs surgery had clear documentation of the biopsy site with photography, diagram, or measurements, and of those documented, only a small fraction used photographs.⁸

Photographic documentation is not currently required by the VA, increasing the risk of WSS. About 20% of the ~150 VA dermatology departments nationwide are associated with a dermatology residency program and have implemented photographic documentation of lesions before biopsy. The other 80% of departments may not be using photographic documentation. The following 3 cases experienced by the authors highlight instances of how quality photographic documentation of lesions prior to biopsy can improve patient care and save lives. Then, we propose a photographic documentation protocol for VA dermatology departments to follow based on the photographic standards outlined by the American Society for Dermatologic Surgery.⁹

Case 1 Presentation

A 36-year-old traveling veteran who relocates frequently and receives care at multiple VA medical centers (VAMCs) presented for excision of a melanoma. The patient had been managed at another VAMC where the lesion was biopsied in September 2016. He presented to the Orlando, Florida, VAMC dermatology clinic 5 months later with the photographs of his biopsy sites along with the biopsy reports. The patient had 6 biopsies labeled A through F. Lesion A at the right mid back was positive for melanoma (Figure 1), whereas lesion C on the mid lower back was not cancerous (Figure 2). On examination of the patient’s back, he had numerous moles and scars. The initial receiving HCP circled and photographed the scar presumed to be the melanoma on the mid lower back (Figure 3).

On the day of surgery, the surgeon routinely checked the biopsy report as well as the photograph from the patient’s most recent HCP visit. The surgeon noted that biopsy A (right mid back) on the pathology report had been identified as the melanoma; however, biopsy C (mid lower back) was circled and presumed to be the melanoma in the recent photograph by the receiving HCP—a nurse practitioner. The surgeon compared the initial photos from the referring VAMC with those from the receiving HCP and subsequently matched biopsy A (melanoma) with the correct location on the right mid back.

This discrepancy was explained to the patient with photographic confirmation, allowing for agreement on the correct site before the surgery. The pathology results of the surgical excision confirmed melanoma in the specimen and clear margins. Thus, the correct site was operated on.

Case 2 Presentation

A veteran aged 86 years with a medical history of a double transplant and long-term immunosuppression leading to numerous skin cancers was referred for surgical excision of a confirmed squamous cell carcinoma (SCC) on the left upper back. On the day of surgery, the biopsy site could not be identified clearly due to numerous preexisting scars (Figure 4). No photograph of the original biopsy site was available. The referring HCP was called to the bedside to assist in identifying the biopsy site but also was unable to clearly identify the site. This was explained to the patient. As 2-person confirmation was unsuccessful, conservative treatment was used with patient consent. The patient has since had subsequent close follow-up to monitor for recurrence, as SCC in transplant patients can display aggressive growth and potential for metastasis.

Case 3 Presentation

A veteran was referred for surgical excision of a nonmelanoma skin cancer. The biopsy was completed well in advance of the anticipated surgery day. On the day of surgery, the site could not be detected as it healed well after the biopsy. Although a clinical photograph was available, it was taken too close-up to find a frame of reference for identifying the location of the biopsy site. The referring HCP was called to the bedside to assist in identification of the biopsy site, but 2-person confirmation was unsuccessful. This was explained to the patient, and with his consent, the HCPs agreed on conservative treatment and close follow-up.

Discussion

To prevent and minimize poor outcomes associated with WSS, the health care team should routinely document the lesion location in detail before the biopsy. Many HCPs believe a preoperative photograph is the best method for documentation. As demonstrated in the third case presentation, photographs must be taken at a distance that includes nearby anatomic landmarks for reference. It is suggested that the providers obtain 2 images, one that is far enough to include landmarks, and one that is close enough to clearly differentiate the targeted lesion from others.¹⁰

Although high-resolution digital cameras are preferred, mobile phones also can be used if they provide quality images. As phones with built-in cameras are ubiquitous, they offer a quick and easy method of photographic documentation. St John and colleagues also presented the possibility of having patients keep pictures of the lesion on their phones, as this removes potential privacy concerns and facilitates easy transportation of information between HCPs.¹⁰ If it is discovered that a photograph was not taken at the time of biopsy, our practice contacts the patient and asks them to photograph and circle the biopsy site using their mobile phone or camera and bring it to the surgery appointment. We propose a VA protocol for photographic documentation of biopsy sites (Table).

Conclusions

The cases described here highlight how the lack of proper photographic documentation can prevent the use of curative surgical treatment. In order to reduce WSS and improve quality care, HCPs must continue to take steps and create safeguards to minimize risk. Proper documentation of lesions prior to biopsy provides an effective route to reduce incidence of WSS. If the biopsy site cannot be found, various strategies to properly identify the site can be employed. If WSS occurs, it is important that HCPs provide full disclosure to patients. With a growing emphasis on patient safety measures and advances in technology, HCPs are becoming increasingly cognizant about the most effective ways to optimize patient care, and it is anticipated that this will result in a decrease in morbidity and mortality.

Preventable errors by health care workers are widespread and cause significant morbidity and mortality. Wrong site surgery (WSS) is a preventable error that causes harm through both the direct insult of surgery and propagation of the untreated initial problem. WSS also can cause poor patient outcomes, low morale, malpractice claims, and increased costs to the health care system. The estimated median prevalence of WSS across all specialties is 9 events per 1,000,000 surgical procedures, and an institutional study of 112,500 surgical procedures reported 1 wrong-site event, which involved removing the incorrect skin lesion and not removing the intended lesion.^1,2

Though the prevalence is low when examining all specialties together, dermatology is also susceptible to WSS.³ Watson and colleagues demonstrated that 31% of intervention errors were due to WSS and suggested that prebiopsy photography helps decrease errors.⁴ Thus, the American Academy of Dermatology has emphasized the importance of reducing WSS.⁵ A study by Nijhawan and colleagues found that 25% of patients receiving Mohs surgery at a private single cancer center could not identify their biopsy location because the duration between biopsy and surgery allowed biopsy sites to heal well, which made finding the lesion difficult.⁶

Risk factors for WSS include having multiple health care providers (HCPs) living remote from the surgery location involved in the case, being a traveling veteran, receiving care at multiple facilities inside and outside the US Department of Veterans Affairs (VA) system, mislabeling photographs or specimens, and photographs not taken at time of biopsy and too close with no frame of reference to assist in finding the correct site. The VA electronic health record (EHR) is not integrated with outside facility EHRs, and the Office of Community Care (OCC) at the VA is responsible for obtaining copies of outside records. If unsuccessful, the HCP and/or patient must provide the records. Frequently, records are not received or require multiple attempts to be obtained. This mostly affects veterans receiving care at multiple facilities inside and outside the VA system as the lack of or timely receipt of past health records could increase the risk for WSS.

To combat WSS, some institutions have implemented standardized protocols requiring photographic documentation of lesions before biopsy so that the surgeon can properly identify the correct site prior to operating.⁷ Fortunately, recent advances in technology have made it easier to provide photographic documentation of skin lesions. Highsmith and colleagues highlighted use of smartphones to avoid WSS in dermatology.⁷ Despite these advances, photographic documentation of lesions is not universal. A study by Rossy and colleagues found that less than half of patients referred for Mohs surgery had clear documentation of the biopsy site with photography, diagram, or measurements, and of those documented, only a small fraction used photographs.⁸

Photographic documentation is not currently required by the VA, increasing the risk of WSS. About 20% of the ~150 VA dermatology departments nationwide are associated with a dermatology residency program and have implemented photographic documentation of lesions before biopsy. The other 80% of departments may not be using photographic documentation. The following 3 cases experienced by the authors highlight instances of how quality photographic documentation of lesions prior to biopsy can improve patient care and save lives. Then, we propose a photographic documentation protocol for VA dermatology departments to follow based on the photographic standards outlined by the American Society for Dermatologic Surgery.⁹

Case 1 Presentation

A 36-year-old traveling veteran who relocates frequently and receives care at multiple VA medical centers (VAMCs) presented for excision of a melanoma. The patient had been managed at another VAMC where the lesion was biopsied in September 2016. He presented to the Orlando, Florida, VAMC dermatology clinic 5 months later with the photographs of his biopsy sites along with the biopsy reports. The patient had 6 biopsies labeled A through F. Lesion A at the right mid back was positive for melanoma (Figure 1), whereas lesion C on the mid lower back was not cancerous (Figure 2). On examination of the patient’s back, he had numerous moles and scars. The initial receiving HCP circled and photographed the scar presumed to be the melanoma on the mid lower back (Figure 3).

On the day of surgery, the surgeon routinely checked the biopsy report as well as the photograph from the patient’s most recent HCP visit. The surgeon noted that biopsy A (right mid back) on the pathology report had been identified as the melanoma; however, biopsy C (mid lower back) was circled and presumed to be the melanoma in the recent photograph by the receiving HCP—a nurse practitioner. The surgeon compared the initial photos from the referring VAMC with those from the receiving HCP and subsequently matched biopsy A (melanoma) with the correct location on the right mid back.

This discrepancy was explained to the patient with photographic confirmation, allowing for agreement on the correct site before the surgery. The pathology results of the surgical excision confirmed melanoma in the specimen and clear margins. Thus, the correct site was operated on.

Case 2 Presentation

A veteran aged 86 years with a medical history of a double transplant and long-term immunosuppression leading to numerous skin cancers was referred for surgical excision of a confirmed squamous cell carcinoma (SCC) on the left upper back. On the day of surgery, the biopsy site could not be identified clearly due to numerous preexisting scars (Figure 4). No photograph of the original biopsy site was available. The referring HCP was called to the bedside to assist in identifying the biopsy site but also was unable to clearly identify the site. This was explained to the patient. As 2-person confirmation was unsuccessful, conservative treatment was used with patient consent. The patient has since had subsequent close follow-up to monitor for recurrence, as SCC in transplant patients can display aggressive growth and potential for metastasis.

Case 3 Presentation

A veteran was referred for surgical excision of a nonmelanoma skin cancer. The biopsy was completed well in advance of the anticipated surgery day. On the day of surgery, the site could not be detected as it healed well after the biopsy. Although a clinical photograph was available, it was taken too close-up to find a frame of reference for identifying the location of the biopsy site. The referring HCP was called to the bedside to assist in identification of the biopsy site, but 2-person confirmation was unsuccessful. This was explained to the patient, and with his consent, the HCPs agreed on conservative treatment and close follow-up.

Discussion

To prevent and minimize poor outcomes associated with WSS, the health care team should routinely document the lesion location in detail before the biopsy. Many HCPs believe a preoperative photograph is the best method for documentation. As demonstrated in the third case presentation, photographs must be taken at a distance that includes nearby anatomic landmarks for reference. It is suggested that the providers obtain 2 images, one that is far enough to include landmarks, and one that is close enough to clearly differentiate the targeted lesion from others.¹⁰

Although high-resolution digital cameras are preferred, mobile phones also can be used if they provide quality images. As phones with built-in cameras are ubiquitous, they offer a quick and easy method of photographic documentation. St John and colleagues also presented the possibility of having patients keep pictures of the lesion on their phones, as this removes potential privacy concerns and facilitates easy transportation of information between HCPs.¹⁰ If it is discovered that a photograph was not taken at the time of biopsy, our practice contacts the patient and asks them to photograph and circle the biopsy site using their mobile phone or camera and bring it to the surgery appointment. We propose a VA protocol for photographic documentation of biopsy sites (Table).

Conclusions

The cases described here highlight how the lack of proper photographic documentation can prevent the use of curative surgical treatment. In order to reduce WSS and improve quality care, HCPs must continue to take steps and create safeguards to minimize risk. Proper documentation of lesions prior to biopsy provides an effective route to reduce incidence of WSS. If the biopsy site cannot be found, various strategies to properly identify the site can be employed. If WSS occurs, it is important that HCPs provide full disclosure to patients. With a growing emphasis on patient safety measures and advances in technology, HCPs are becoming increasingly cognizant about the most effective ways to optimize patient care, and it is anticipated that this will result in a decrease in morbidity and mortality.

Preventable errors by health care workers are widespread and cause significant morbidity and mortality. Wrong site surgery (WSS) is a preventable error that causes harm through both the direct insult of surgery and propagation of the untreated initial problem. WSS also can cause poor patient outcomes, low morale, malpractice claims, and increased costs to the health care system. The estimated median prevalence of WSS across all specialties is 9 events per 1,000,000 surgical procedures, and an institutional study of 112,500 surgical procedures reported 1 wrong-site event, which involved removing the incorrect skin lesion and not removing the intended lesion.^1,2

Though the prevalence is low when examining all specialties together, dermatology is also susceptible to WSS.³ Watson and colleagues demonstrated that 31% of intervention errors were due to WSS and suggested that prebiopsy photography helps decrease errors.⁴ Thus, the American Academy of Dermatology has emphasized the importance of reducing WSS.⁵ A study by Nijhawan and colleagues found that 25% of patients receiving Mohs surgery at a private single cancer center could not identify their biopsy location because the duration between biopsy and surgery allowed biopsy sites to heal well, which made finding the lesion difficult.⁶

Risk factors for WSS include having multiple health care providers (HCPs) living remote from the surgery location involved in the case, being a traveling veteran, receiving care at multiple facilities inside and outside the US Department of Veterans Affairs (VA) system, mislabeling photographs or specimens, and photographs not taken at time of biopsy and too close with no frame of reference to assist in finding the correct site. The VA electronic health record (EHR) is not integrated with outside facility EHRs, and the Office of Community Care (OCC) at the VA is responsible for obtaining copies of outside records. If unsuccessful, the HCP and/or patient must provide the records. Frequently, records are not received or require multiple attempts to be obtained. This mostly affects veterans receiving care at multiple facilities inside and outside the VA system as the lack of or timely receipt of past health records could increase the risk for WSS.

To combat WSS, some institutions have implemented standardized protocols requiring photographic documentation of lesions before biopsy so that the surgeon can properly identify the correct site prior to operating.⁷ Fortunately, recent advances in technology have made it easier to provide photographic documentation of skin lesions. Highsmith and colleagues highlighted use of smartphones to avoid WSS in dermatology.⁷ Despite these advances, photographic documentation of lesions is not universal. A study by Rossy and colleagues found that less than half of patients referred for Mohs surgery had clear documentation of the biopsy site with photography, diagram, or measurements, and of those documented, only a small fraction used photographs.⁸

Photographic documentation is not currently required by the VA, increasing the risk of WSS. About 20% of the ~150 VA dermatology departments nationwide are associated with a dermatology residency program and have implemented photographic documentation of lesions before biopsy. The other 80% of departments may not be using photographic documentation. The following 3 cases experienced by the authors highlight instances of how quality photographic documentation of lesions prior to biopsy can improve patient care and save lives. Then, we propose a photographic documentation protocol for VA dermatology departments to follow based on the photographic standards outlined by the American Society for Dermatologic Surgery.⁹

Case 1 Presentation

A 36-year-old traveling veteran who relocates frequently and receives care at multiple VA medical centers (VAMCs) presented for excision of a melanoma. The patient had been managed at another VAMC where the lesion was biopsied in September 2016. He presented to the Orlando, Florida, VAMC dermatology clinic 5 months later with the photographs of his biopsy sites along with the biopsy reports. The patient had 6 biopsies labeled A through F. Lesion A at the right mid back was positive for melanoma (Figure 1), whereas lesion C on the mid lower back was not cancerous (Figure 2). On examination of the patient’s back, he had numerous moles and scars. The initial receiving HCP circled and photographed the scar presumed to be the melanoma on the mid lower back (Figure 3).

On the day of surgery, the surgeon routinely checked the biopsy report as well as the photograph from the patient’s most recent HCP visit. The surgeon noted that biopsy A (right mid back) on the pathology report had been identified as the melanoma; however, biopsy C (mid lower back) was circled and presumed to be the melanoma in the recent photograph by the receiving HCP—a nurse practitioner. The surgeon compared the initial photos from the referring VAMC with those from the receiving HCP and subsequently matched biopsy A (melanoma) with the correct location on the right mid back.

This discrepancy was explained to the patient with photographic confirmation, allowing for agreement on the correct site before the surgery. The pathology results of the surgical excision confirmed melanoma in the specimen and clear margins. Thus, the correct site was operated on.

Case 2 Presentation

A veteran aged 86 years with a medical history of a double transplant and long-term immunosuppression leading to numerous skin cancers was referred for surgical excision of a confirmed squamous cell carcinoma (SCC) on the left upper back. On the day of surgery, the biopsy site could not be identified clearly due to numerous preexisting scars (Figure 4). No photograph of the original biopsy site was available. The referring HCP was called to the bedside to assist in identifying the biopsy site but also was unable to clearly identify the site. This was explained to the patient. As 2-person confirmation was unsuccessful, conservative treatment was used with patient consent. The patient has since had subsequent close follow-up to monitor for recurrence, as SCC in transplant patients can display aggressive growth and potential for metastasis.

Case 3 Presentation

A veteran was referred for surgical excision of a nonmelanoma skin cancer. The biopsy was completed well in advance of the anticipated surgery day. On the day of surgery, the site could not be detected as it healed well after the biopsy. Although a clinical photograph was available, it was taken too close-up to find a frame of reference for identifying the location of the biopsy site. The referring HCP was called to the bedside to assist in identification of the biopsy site, but 2-person confirmation was unsuccessful. This was explained to the patient, and with his consent, the HCPs agreed on conservative treatment and close follow-up.

Discussion

To prevent and minimize poor outcomes associated with WSS, the health care team should routinely document the lesion location in detail before the biopsy. Many HCPs believe a preoperative photograph is the best method for documentation. As demonstrated in the third case presentation, photographs must be taken at a distance that includes nearby anatomic landmarks for reference. It is suggested that the providers obtain 2 images, one that is far enough to include landmarks, and one that is close enough to clearly differentiate the targeted lesion from others.¹⁰

Although high-resolution digital cameras are preferred, mobile phones also can be used if they provide quality images. As phones with built-in cameras are ubiquitous, they offer a quick and easy method of photographic documentation. St John and colleagues also presented the possibility of having patients keep pictures of the lesion on their phones, as this removes potential privacy concerns and facilitates easy transportation of information between HCPs.¹⁰ If it is discovered that a photograph was not taken at the time of biopsy, our practice contacts the patient and asks them to photograph and circle the biopsy site using their mobile phone or camera and bring it to the surgery appointment. We propose a VA protocol for photographic documentation of biopsy sites (Table).

Conclusions

The cases described here highlight how the lack of proper photographic documentation can prevent the use of curative surgical treatment. In order to reduce WSS and improve quality care, HCPs must continue to take steps and create safeguards to minimize risk. Proper documentation of lesions prior to biopsy provides an effective route to reduce incidence of WSS. If the biopsy site cannot be found, various strategies to properly identify the site can be employed. If WSS occurs, it is important that HCPs provide full disclosure to patients. With a growing emphasis on patient safety measures and advances in technology, HCPs are becoming increasingly cognizant about the most effective ways to optimize patient care, and it is anticipated that this will result in a decrease in morbidity and mortality.