Hospital Medicine

Confirmed cases of coronavirus disease 2019 (COVID-19) exceed 111 million, and the disease is responsible for approximately 2.4 million deaths worldwide.¹ In the United States, 28 million cases of COVID-19 have been reported, and the disease has caused more than 497,000 deaths.² The clinical presentation of COVID-19 varies widely, with the most severe presentation characterized by acute respiratory distress syndrome and a marked systemic inflammatory response. Corticosteroids have emerged as a potential therapeutic option in a subset of patients. Results from the recently published RECOVERY trial suggest a substantial mortality benefit of dexamethasone in patients who require mechanical ventilation, with a risk reduction of approximately 33%.³ In addition, a recent large retrospective study demonstrated a reduction in the risk of mechanical ventilation or mortality with corticosteroids in a prespecified subset of patients with C-reactive protein (CRP) ≥20 mg/dL, which indicates a high burden of inflammation.⁴

Some patients with severe COVID-19 experience a positive feedback cascade of proinflammatory cytokines, called the cytokine storm, which can worsen lung injury and, in some cases, progress to vasodilatory shock and multiorgan failure.⁵ This complication’s cytokine cascade includes interleukin (IL) 6, IL-1β, and CC chemokine ligand 3 (CCL3), which are released by airway macrophages and all of which are heavily implicated in the maladaptive forms of immune response to COVID-19.^6,7 The cytokine IL-6 is the primary signal for the production of CRP, and corticosteroids have been shown, both in vitro and in vivo, to reduce the production of IL-6 and other cytokines by airway macrophages.⁶ Levels of CRP have been shown to correlate with outcomes in COVID-19 and bacterial pneumonias.^7,8 Reduction in CRP levels following the institution of therapy, known as CRP response, has been shown to predict outcomes in other inflammatory conditions, such as osteomyelitis, hidradenitis suppurativa, and some cases of bacterial pneumonia.^8-10 Similar CRP response in hemophagocytic lymphohistiocytosis, an entity which closely resembles cytokine storm syndrome, has been shown to correlate with disease activity in patients following treatment with an IL-1 antagonist.¹¹ Whether the CRP response as a response to therapeutics in COVID-19 is associated with improved outcomes remains unknown.

Laboratory measurement of CRP levels offers several advantages over the measurement of interleukins. Notably, the half-life of CRP is approximately 19 hours, which is comparable across different age groups and inflammatory conditions because its concentration depends primarily on synthesis in the liver, and a decreased level suggests decreased stimulus for synthesis.⁸ This makes CRP a useful biomarker to assess response to therapy, in contrast to interleukins, which have short half-lives, are variable in heterogeneous populations, and can be difficult to measure. In addition, CRP measurement is rapid and relatively inexpensive.

We hypothesized that reduction in CRP levels by 50% or more within 72 hours after the initiation of corticosteroids in patients with COVID-19 is associated with reduced inpatient mortality and may be an early indicator of therapeutic response.

Study Participants

In this retrospective cohort study, we reviewed all adult patients admitted to Montefiore Medical Center (Bronx, New York) for COVID-19 between March 10, 2020, and May 2, 2020. Patients must have been discharged (alive or deceased) by the administrative censor date (May 2, 2020) to be included. Patients who died within the first 48 hours of admission were excluded to allow sufficient time for corticosteroid treatment to take effect. For inclusion in the corticosteroid group, patients needed to have received at least 2 consecutive days of corticosteroid treatment beginning within the first 48 hours of admission with a total daily dose of 0.5 mg/kg prednisone equivalent or greater. Patients who received treatment-dose corticosteroids later in the hospital course were excluded (Appendix Figure).

Comparison Group and Outcome

We examined trends in CRP levels for patients who received corticosteroids vs trends among patients who did not receive corticosteroids. In addition, among patients who were treated with corticosteroids, we compared the inpatient mortality of those who did have a reduction in CRP level after treatment with inpatient mortality of those who did not have a reduction in CRP level after treatment. First, CRP level trends over time were examined in all patients, and compared between those who received corticosteroid treatment and those who did not. Then, patients who received corticosteroids were categorized based on changes in CRP levels after beginning corticosteroids. The first CRP level obtained during the first 48 hours of admission was used as the initial CRP level. For each patient, the last CRP level within the 72 hours after initiation of treatment was used to calculate the change in CRP level from admission. A patient was considered to be a “CRP responder” if their CRP level decreased by 50% or more within 72 hours after treatment and a “CRP nonresponder” if their CRP level did not drop by at least 50% within 72 hours of treatment. Patients who did not have a CRP level within the initial 48 hours of admission or a subsequent CRP measured in the 72 hours after treatment were considered to have an “undetermined CRP response” and excluded from the mortality analysis.

We observed a rise in CRP starting around day 6 among patients treated with corticosteroids and performed a post hoc analysis to determine if this was due to a selection effect whereby patients staying in the hospital longer had higher CRP levels or represented actual rise. In order to address this, we performed a stratified analysis comparing the trends in CRP levels among patients with a length of stay (LOS) of 7 or more days with trends among those with an LOS less than 7 days.

Statistical Analysis

To characterize differences in patients who received corticosteroids and those who did not, we examined their demographic, clinical characteristics, and admission laboratory values, using chi-square test for categorical variables and Kruskal-Wallis test for continuous variables (Table 1). The change in CRP levels from day 0 (presentation to the hospital) in both groups was plotted in a time-series analysis. For each day in the time series, the 95% CIs for the changes in CRP were computed using the t statistic for the corresponding distribution. The Kruskal-Wallis test was used to assess the significance of differences between groups at 72 hours after initiation of treatment.

After categorizing patients by CRP response, we compared demographic, clinical, and laboratory characteristics of patients who were CRP responsive with those of patients who were not, using the same tests of statistical inference mentioned above. To compare time to inpatient mortality differences between CRP response groups, Kaplan-Meier survival curves were generated and statistical significance determined via log-rank test. Univariable logistic regression was used to estimate the odds ratio of inpatient mortality between comparison groups in an unadjusted analysis. Last, to examine the independent association between CRP response and mortality, we constructed a multivariate model that included variables that were significantly associated with mortality in univariable analysis and considered to be important potential confounders by the authors. Details on variable selection for the model are listed in Appendix Table 1.

Data Collection

Data were directly extracted from our center’s electronic health record system. Data processing and recoding was performed using the Python programming language (version 2.7.17) and data analysis was done using Stata 12 (StataCorp LLC; 2011). This study was approved by the institutional review board of the Albert Einstein College of Medicine.

Corticosteroids vs No Corticosteroids

Between March 10, 2020, and May 2, 2020, a total of 3,382 adult patients were admitted for COVID-19 at Montefiore Medical Center. Of these, 2,707 patients met the study inclusion criteria, and 324 of those received corticosteroid treatment. Their demographic characteristics, comorbidities, and admission lab values are shown in Table 1. Patients who received corticosteroids were older, had higher comorbidity scores, were more likely to have asthma or chronic obstructive pulmonary disease, and were less likely to be full code status, compared with patients who did not receive corticosteroids. Patients who received corticosteroids also had higher initial white blood cell (WBC) and neutrophil counts but lower lymphocyte count. The two groups were comparable in initial creatinine level. Additional patient characteristics and addmission lab values are shown in Appendix Table 2.

Average change in CRP levels by hospital day for those who received corticosteroids and those who did not are shown in Figure 1A. Among patients who received corticosteroid treatment, there was a significant decrease in CRP level at 72 hours of treatment (P < .001). In the post hoc analysis of trends in CRP levels, we found that CRP levels among those treated with corticosteroids started to rise around day 6 after the initial drop. This trend was observed even after removing patients with shorter LOS (<7 days) (Figure 1B). The median durations of corticosteroid therapy were 3 days among patients whose LOS was less than 7 days and 6 days among those whose LOS was 7 days or greater. The rise in CRP level was seen at day 5 and day 7 within each group, respectively. Crude death rate was 41.7% among patients with LOS of less than 7 days and 40.6% in those with LOS of 7 days or greater.

CRP Responders vs Nonresponders

Among the 324 patients who received corticosteroids, 131 (40.4%) were classified as responders, 92 (28.4%) were classified as nonresponders, and 101 (31.2%) were undetermined. Characteristics of CRP responders and CRP nonresponders are shown in Table 2 and Appendix Table 3. CRP responders were more likely to have dementia, higher median admission platelet count, and fibrinogen level compared with CRP nonresponders. Patients whose CRP response was undetermined were excluded from the analysis. Their characteristics are shown in Appendix Table 4.

The observed inpatient mortality rate was 25.2% among CRP responders and 47.8% among CRP nonresponders. This was also demonstrated in the Kaplan-Meier survival curve (Figure 2). The odds of inpatient mortality among CRP responders was strongly and significantly reduced compared with those among nonresponders in an unadjusted analysis (odds ratio [OR], 0.37; 95% CI, 0.21-0.65; P = .001) and after adjustment for demographic and clinical characteristics including age, Charlson Comorbidity Index, initial WBC count, initial CRP level, and initial fibrinogen level (OR, 0.27; 95% CI, 0.14-0.54; P < .001). Details on how variables were operationalized and information on missing data are included in Appendix Table 1.

To explore whether this observed effect differed depending on severity of the respiratory illness, we examined the association between CRP response and mortality in subgroups stratified by intubation status. Within our cohort of 223 patients (92 CRP responders and 131 CRP nonresponders), 166 patients were never intubated, 50 patients were intubated in the first 48 hours, and 7 patients were intubated later on during the admission. The odds ratios for death among CRP responders vs nonresponders were 0.50 (P = .07) among patients never intubated and 0.46 (P = .2) among patients intubated within the initial 48 hours of admission.

In this retrospective study, we found that, on average, patients treated with corticosteroids had a swift and marked reduction in serum CRP. In addition, among patients treated with corticosteroids, those whose CRP was reduced by 50% or more within 72 hours after treatment had a dramatically reduced risk of inpatient mortality compared with the risk among nonresponders. This study contributes to a growing body of evidence that suggests that corticosteroids may be an efficacious treatment to reduce adverse events in patients with COVID-19 who have evidence of high levels of inflammation as measured by CRP level.^3,4,12,13

It remains unclear whether CRP is simply a biomarker of disease activity or if it plays a role in mediating inflammation. While CRP is commonly understood to be an acute phase reactant, it has been suggested that, after undergoing proteolysis, it functions as a chemoattractant for monocytes.¹⁴ In addition, it is now known that the inflammatory CD14+/CD16+ monocytes that express high levels of IL-6 are key drivers of the cytokine storm in COVID-19.¹⁵ Therefore, it may be possible that the high levels of circulating CRP in patients with cytokine storm recruits monocytes to the lungs, which leads to further lung injury.

Other mechanisms of immune dysregulation that may contribute to lung injury and respiratory failure in COVID-19, such as cytokine-induced T-cell suppression, have been proposed.^7,16 The related markers, such as levels of T-cells or specific cytokines, may therefore represent different but related underlying immune mechanisms affecting the clinical course of COVID-19 that may respond to different therapeutic modalities such as direct IL-6 blockade or chemokine receptor blockade, among others that are currently under investigation.^17,18

Regardless of the underlying mechanism of immune regulation, our study shows that serial measurement of CRP may serve as an early indicator of response to corticosteroids that correlates with decreased mortality. The association between CRP response and reduced risk of mortality was present in both subgroups, those requiring mechanical ventilation and those who did not. The risk reduction was similar in magnitude to the overall effect but was not statistically significant in either group. Interestingly, our time series analysis demonstrated a rise in CRP around day 6 among patients treated with corticosteroids (notably, most patients were treated for 5 to 7 days). Our post hoc analysis suggests that this may represent a “rebound” in inflammation after discontinuation of corticosteroids. However, the clinical significance of this rebound and whether a longer course of steroids would improve outcomes is not known. Because corticosteroid therapy may be associated with adverse effects in some patients,⁴ it is possible that CRP nonresponders represent a subset of patients in whom corticosteroids are not effective and for whom alternative therapies should be considered. In one study looking at the usefulness of IL-1 inhibition for severe COVID-19 infection, patients who received IL-1 inhibitor therapy had improved mortality and a significant decrease in CRP concentration as compared with the historical group.¹⁹ Finally, it is worth noting that, in one large retrospective study, there was harm associated with corticosteroid therapy in patients with low levels of CRP, and in the RECOVERY trial there was a trend toward harm for patients with no oxygen requirement.^3,4 Serial measurement of CRP may further identify the subset of patients in whom corticosteroid therapy might be harmful.

This study has several limitations. First, the retrospective nature of this study is inherently prone to selection bias, and despite the large number of clinical variables accounted for, unmeasured confounders may still exist. This study was also conducted at a single clinical center operating under emergency circumstances at a time during which healthcare resources were limited. Overall in-hospital mortality was high but similar to mortality rates reported at other hospitals in the New York City area during the same months.²⁰ The strengths of this study include a large cohort of COVID-19 patients from New York City, an epicenter of COVID-19, who received corticosteroids.

We found that therapy with corticosteroids in patients with COVID-19 is associated with a substantial reduction in CRP levels within 72 hours of therapy, and for those patients in whom CRP levels decrease by 50% or more, there is a significantly lower risk of inpatient mortality. Future studies are needed to validate these findings in other cohorts and to determine if markers other than CRP levels may be predictors of a therapeutic response or if CRP nonresponders would benefit from other targeted therapies.

Confirmed cases of coronavirus disease 2019 (COVID-19) exceed 111 million, and the disease is responsible for approximately 2.4 million deaths worldwide.¹ In the United States, 28 million cases of COVID-19 have been reported, and the disease has caused more than 497,000 deaths.² The clinical presentation of COVID-19 varies widely, with the most severe presentation characterized by acute respiratory distress syndrome and a marked systemic inflammatory response. Corticosteroids have emerged as a potential therapeutic option in a subset of patients. Results from the recently published RECOVERY trial suggest a substantial mortality benefit of dexamethasone in patients who require mechanical ventilation, with a risk reduction of approximately 33%.³ In addition, a recent large retrospective study demonstrated a reduction in the risk of mechanical ventilation or mortality with corticosteroids in a prespecified subset of patients with C-reactive protein (CRP) ≥20 mg/dL, which indicates a high burden of inflammation.⁴

Some patients with severe COVID-19 experience a positive feedback cascade of proinflammatory cytokines, called the cytokine storm, which can worsen lung injury and, in some cases, progress to vasodilatory shock and multiorgan failure.⁵ This complication’s cytokine cascade includes interleukin (IL) 6, IL-1β, and CC chemokine ligand 3 (CCL3), which are released by airway macrophages and all of which are heavily implicated in the maladaptive forms of immune response to COVID-19.^6,7 The cytokine IL-6 is the primary signal for the production of CRP, and corticosteroids have been shown, both in vitro and in vivo, to reduce the production of IL-6 and other cytokines by airway macrophages.⁶ Levels of CRP have been shown to correlate with outcomes in COVID-19 and bacterial pneumonias.^7,8 Reduction in CRP levels following the institution of therapy, known as CRP response, has been shown to predict outcomes in other inflammatory conditions, such as osteomyelitis, hidradenitis suppurativa, and some cases of bacterial pneumonia.^8-10 Similar CRP response in hemophagocytic lymphohistiocytosis, an entity which closely resembles cytokine storm syndrome, has been shown to correlate with disease activity in patients following treatment with an IL-1 antagonist.¹¹ Whether the CRP response as a response to therapeutics in COVID-19 is associated with improved outcomes remains unknown.

Laboratory measurement of CRP levels offers several advantages over the measurement of interleukins. Notably, the half-life of CRP is approximately 19 hours, which is comparable across different age groups and inflammatory conditions because its concentration depends primarily on synthesis in the liver, and a decreased level suggests decreased stimulus for synthesis.⁸ This makes CRP a useful biomarker to assess response to therapy, in contrast to interleukins, which have short half-lives, are variable in heterogeneous populations, and can be difficult to measure. In addition, CRP measurement is rapid and relatively inexpensive.

We hypothesized that reduction in CRP levels by 50% or more within 72 hours after the initiation of corticosteroids in patients with COVID-19 is associated with reduced inpatient mortality and may be an early indicator of therapeutic response.

Study Participants

In this retrospective cohort study, we reviewed all adult patients admitted to Montefiore Medical Center (Bronx, New York) for COVID-19 between March 10, 2020, and May 2, 2020. Patients must have been discharged (alive or deceased) by the administrative censor date (May 2, 2020) to be included. Patients who died within the first 48 hours of admission were excluded to allow sufficient time for corticosteroid treatment to take effect. For inclusion in the corticosteroid group, patients needed to have received at least 2 consecutive days of corticosteroid treatment beginning within the first 48 hours of admission with a total daily dose of 0.5 mg/kg prednisone equivalent or greater. Patients who received treatment-dose corticosteroids later in the hospital course were excluded (Appendix Figure).

Comparison Group and Outcome

We examined trends in CRP levels for patients who received corticosteroids vs trends among patients who did not receive corticosteroids. In addition, among patients who were treated with corticosteroids, we compared the inpatient mortality of those who did have a reduction in CRP level after treatment with inpatient mortality of those who did not have a reduction in CRP level after treatment. First, CRP level trends over time were examined in all patients, and compared between those who received corticosteroid treatment and those who did not. Then, patients who received corticosteroids were categorized based on changes in CRP levels after beginning corticosteroids. The first CRP level obtained during the first 48 hours of admission was used as the initial CRP level. For each patient, the last CRP level within the 72 hours after initiation of treatment was used to calculate the change in CRP level from admission. A patient was considered to be a “CRP responder” if their CRP level decreased by 50% or more within 72 hours after treatment and a “CRP nonresponder” if their CRP level did not drop by at least 50% within 72 hours of treatment. Patients who did not have a CRP level within the initial 48 hours of admission or a subsequent CRP measured in the 72 hours after treatment were considered to have an “undetermined CRP response” and excluded from the mortality analysis.

We observed a rise in CRP starting around day 6 among patients treated with corticosteroids and performed a post hoc analysis to determine if this was due to a selection effect whereby patients staying in the hospital longer had higher CRP levels or represented actual rise. In order to address this, we performed a stratified analysis comparing the trends in CRP levels among patients with a length of stay (LOS) of 7 or more days with trends among those with an LOS less than 7 days.

Statistical Analysis

To characterize differences in patients who received corticosteroids and those who did not, we examined their demographic, clinical characteristics, and admission laboratory values, using chi-square test for categorical variables and Kruskal-Wallis test for continuous variables (Table 1). The change in CRP levels from day 0 (presentation to the hospital) in both groups was plotted in a time-series analysis. For each day in the time series, the 95% CIs for the changes in CRP were computed using the t statistic for the corresponding distribution. The Kruskal-Wallis test was used to assess the significance of differences between groups at 72 hours after initiation of treatment.

After categorizing patients by CRP response, we compared demographic, clinical, and laboratory characteristics of patients who were CRP responsive with those of patients who were not, using the same tests of statistical inference mentioned above. To compare time to inpatient mortality differences between CRP response groups, Kaplan-Meier survival curves were generated and statistical significance determined via log-rank test. Univariable logistic regression was used to estimate the odds ratio of inpatient mortality between comparison groups in an unadjusted analysis. Last, to examine the independent association between CRP response and mortality, we constructed a multivariate model that included variables that were significantly associated with mortality in univariable analysis and considered to be important potential confounders by the authors. Details on variable selection for the model are listed in Appendix Table 1.

Data Collection

Data were directly extracted from our center’s electronic health record system. Data processing and recoding was performed using the Python programming language (version 2.7.17) and data analysis was done using Stata 12 (StataCorp LLC; 2011). This study was approved by the institutional review board of the Albert Einstein College of Medicine.

Corticosteroids vs No Corticosteroids

Between March 10, 2020, and May 2, 2020, a total of 3,382 adult patients were admitted for COVID-19 at Montefiore Medical Center. Of these, 2,707 patients met the study inclusion criteria, and 324 of those received corticosteroid treatment. Their demographic characteristics, comorbidities, and admission lab values are shown in Table 1. Patients who received corticosteroids were older, had higher comorbidity scores, were more likely to have asthma or chronic obstructive pulmonary disease, and were less likely to be full code status, compared with patients who did not receive corticosteroids. Patients who received corticosteroids also had higher initial white blood cell (WBC) and neutrophil counts but lower lymphocyte count. The two groups were comparable in initial creatinine level. Additional patient characteristics and addmission lab values are shown in Appendix Table 2.

Average change in CRP levels by hospital day for those who received corticosteroids and those who did not are shown in Figure 1A. Among patients who received corticosteroid treatment, there was a significant decrease in CRP level at 72 hours of treatment (P < .001). In the post hoc analysis of trends in CRP levels, we found that CRP levels among those treated with corticosteroids started to rise around day 6 after the initial drop. This trend was observed even after removing patients with shorter LOS (<7 days) (Figure 1B). The median durations of corticosteroid therapy were 3 days among patients whose LOS was less than 7 days and 6 days among those whose LOS was 7 days or greater. The rise in CRP level was seen at day 5 and day 7 within each group, respectively. Crude death rate was 41.7% among patients with LOS of less than 7 days and 40.6% in those with LOS of 7 days or greater.

CRP Responders vs Nonresponders

Among the 324 patients who received corticosteroids, 131 (40.4%) were classified as responders, 92 (28.4%) were classified as nonresponders, and 101 (31.2%) were undetermined. Characteristics of CRP responders and CRP nonresponders are shown in Table 2 and Appendix Table 3. CRP responders were more likely to have dementia, higher median admission platelet count, and fibrinogen level compared with CRP nonresponders. Patients whose CRP response was undetermined were excluded from the analysis. Their characteristics are shown in Appendix Table 4.

The observed inpatient mortality rate was 25.2% among CRP responders and 47.8% among CRP nonresponders. This was also demonstrated in the Kaplan-Meier survival curve (Figure 2). The odds of inpatient mortality among CRP responders was strongly and significantly reduced compared with those among nonresponders in an unadjusted analysis (odds ratio [OR], 0.37; 95% CI, 0.21-0.65; P = .001) and after adjustment for demographic and clinical characteristics including age, Charlson Comorbidity Index, initial WBC count, initial CRP level, and initial fibrinogen level (OR, 0.27; 95% CI, 0.14-0.54; P < .001). Details on how variables were operationalized and information on missing data are included in Appendix Table 1.

To explore whether this observed effect differed depending on severity of the respiratory illness, we examined the association between CRP response and mortality in subgroups stratified by intubation status. Within our cohort of 223 patients (92 CRP responders and 131 CRP nonresponders), 166 patients were never intubated, 50 patients were intubated in the first 48 hours, and 7 patients were intubated later on during the admission. The odds ratios for death among CRP responders vs nonresponders were 0.50 (P = .07) among patients never intubated and 0.46 (P = .2) among patients intubated within the initial 48 hours of admission.

In this retrospective study, we found that, on average, patients treated with corticosteroids had a swift and marked reduction in serum CRP. In addition, among patients treated with corticosteroids, those whose CRP was reduced by 50% or more within 72 hours after treatment had a dramatically reduced risk of inpatient mortality compared with the risk among nonresponders. This study contributes to a growing body of evidence that suggests that corticosteroids may be an efficacious treatment to reduce adverse events in patients with COVID-19 who have evidence of high levels of inflammation as measured by CRP level.^3,4,12,13

It remains unclear whether CRP is simply a biomarker of disease activity or if it plays a role in mediating inflammation. While CRP is commonly understood to be an acute phase reactant, it has been suggested that, after undergoing proteolysis, it functions as a chemoattractant for monocytes.¹⁴ In addition, it is now known that the inflammatory CD14+/CD16+ monocytes that express high levels of IL-6 are key drivers of the cytokine storm in COVID-19.¹⁵ Therefore, it may be possible that the high levels of circulating CRP in patients with cytokine storm recruits monocytes to the lungs, which leads to further lung injury.

Other mechanisms of immune dysregulation that may contribute to lung injury and respiratory failure in COVID-19, such as cytokine-induced T-cell suppression, have been proposed.^7,16 The related markers, such as levels of T-cells or specific cytokines, may therefore represent different but related underlying immune mechanisms affecting the clinical course of COVID-19 that may respond to different therapeutic modalities such as direct IL-6 blockade or chemokine receptor blockade, among others that are currently under investigation.^17,18

Regardless of the underlying mechanism of immune regulation, our study shows that serial measurement of CRP may serve as an early indicator of response to corticosteroids that correlates with decreased mortality. The association between CRP response and reduced risk of mortality was present in both subgroups, those requiring mechanical ventilation and those who did not. The risk reduction was similar in magnitude to the overall effect but was not statistically significant in either group. Interestingly, our time series analysis demonstrated a rise in CRP around day 6 among patients treated with corticosteroids (notably, most patients were treated for 5 to 7 days). Our post hoc analysis suggests that this may represent a “rebound” in inflammation after discontinuation of corticosteroids. However, the clinical significance of this rebound and whether a longer course of steroids would improve outcomes is not known. Because corticosteroid therapy may be associated with adverse effects in some patients,⁴ it is possible that CRP nonresponders represent a subset of patients in whom corticosteroids are not effective and for whom alternative therapies should be considered. In one study looking at the usefulness of IL-1 inhibition for severe COVID-19 infection, patients who received IL-1 inhibitor therapy had improved mortality and a significant decrease in CRP concentration as compared with the historical group.¹⁹ Finally, it is worth noting that, in one large retrospective study, there was harm associated with corticosteroid therapy in patients with low levels of CRP, and in the RECOVERY trial there was a trend toward harm for patients with no oxygen requirement.^3,4 Serial measurement of CRP may further identify the subset of patients in whom corticosteroid therapy might be harmful.

This study has several limitations. First, the retrospective nature of this study is inherently prone to selection bias, and despite the large number of clinical variables accounted for, unmeasured confounders may still exist. This study was also conducted at a single clinical center operating under emergency circumstances at a time during which healthcare resources were limited. Overall in-hospital mortality was high but similar to mortality rates reported at other hospitals in the New York City area during the same months.²⁰ The strengths of this study include a large cohort of COVID-19 patients from New York City, an epicenter of COVID-19, who received corticosteroids.

We found that therapy with corticosteroids in patients with COVID-19 is associated with a substantial reduction in CRP levels within 72 hours of therapy, and for those patients in whom CRP levels decrease by 50% or more, there is a significantly lower risk of inpatient mortality. Future studies are needed to validate these findings in other cohorts and to determine if markers other than CRP levels may be predictors of a therapeutic response or if CRP nonresponders would benefit from other targeted therapies.

Confirmed cases of coronavirus disease 2019 (COVID-19) exceed 111 million, and the disease is responsible for approximately 2.4 million deaths worldwide.¹ In the United States, 28 million cases of COVID-19 have been reported, and the disease has caused more than 497,000 deaths.² The clinical presentation of COVID-19 varies widely, with the most severe presentation characterized by acute respiratory distress syndrome and a marked systemic inflammatory response. Corticosteroids have emerged as a potential therapeutic option in a subset of patients. Results from the recently published RECOVERY trial suggest a substantial mortality benefit of dexamethasone in patients who require mechanical ventilation, with a risk reduction of approximately 33%.³ In addition, a recent large retrospective study demonstrated a reduction in the risk of mechanical ventilation or mortality with corticosteroids in a prespecified subset of patients with C-reactive protein (CRP) ≥20 mg/dL, which indicates a high burden of inflammation.⁴

Some patients with severe COVID-19 experience a positive feedback cascade of proinflammatory cytokines, called the cytokine storm, which can worsen lung injury and, in some cases, progress to vasodilatory shock and multiorgan failure.⁵ This complication’s cytokine cascade includes interleukin (IL) 6, IL-1β, and CC chemokine ligand 3 (CCL3), which are released by airway macrophages and all of which are heavily implicated in the maladaptive forms of immune response to COVID-19.^6,7 The cytokine IL-6 is the primary signal for the production of CRP, and corticosteroids have been shown, both in vitro and in vivo, to reduce the production of IL-6 and other cytokines by airway macrophages.⁶ Levels of CRP have been shown to correlate with outcomes in COVID-19 and bacterial pneumonias.^7,8 Reduction in CRP levels following the institution of therapy, known as CRP response, has been shown to predict outcomes in other inflammatory conditions, such as osteomyelitis, hidradenitis suppurativa, and some cases of bacterial pneumonia.^8-10 Similar CRP response in hemophagocytic lymphohistiocytosis, an entity which closely resembles cytokine storm syndrome, has been shown to correlate with disease activity in patients following treatment with an IL-1 antagonist.¹¹ Whether the CRP response as a response to therapeutics in COVID-19 is associated with improved outcomes remains unknown.

Laboratory measurement of CRP levels offers several advantages over the measurement of interleukins. Notably, the half-life of CRP is approximately 19 hours, which is comparable across different age groups and inflammatory conditions because its concentration depends primarily on synthesis in the liver, and a decreased level suggests decreased stimulus for synthesis.⁸ This makes CRP a useful biomarker to assess response to therapy, in contrast to interleukins, which have short half-lives, are variable in heterogeneous populations, and can be difficult to measure. In addition, CRP measurement is rapid and relatively inexpensive.

We hypothesized that reduction in CRP levels by 50% or more within 72 hours after the initiation of corticosteroids in patients with COVID-19 is associated with reduced inpatient mortality and may be an early indicator of therapeutic response.

Study Participants

In this retrospective cohort study, we reviewed all adult patients admitted to Montefiore Medical Center (Bronx, New York) for COVID-19 between March 10, 2020, and May 2, 2020. Patients must have been discharged (alive or deceased) by the administrative censor date (May 2, 2020) to be included. Patients who died within the first 48 hours of admission were excluded to allow sufficient time for corticosteroid treatment to take effect. For inclusion in the corticosteroid group, patients needed to have received at least 2 consecutive days of corticosteroid treatment beginning within the first 48 hours of admission with a total daily dose of 0.5 mg/kg prednisone equivalent or greater. Patients who received treatment-dose corticosteroids later in the hospital course were excluded (Appendix Figure).

Comparison Group and Outcome

We examined trends in CRP levels for patients who received corticosteroids vs trends among patients who did not receive corticosteroids. In addition, among patients who were treated with corticosteroids, we compared the inpatient mortality of those who did have a reduction in CRP level after treatment with inpatient mortality of those who did not have a reduction in CRP level after treatment. First, CRP level trends over time were examined in all patients, and compared between those who received corticosteroid treatment and those who did not. Then, patients who received corticosteroids were categorized based on changes in CRP levels after beginning corticosteroids. The first CRP level obtained during the first 48 hours of admission was used as the initial CRP level. For each patient, the last CRP level within the 72 hours after initiation of treatment was used to calculate the change in CRP level from admission. A patient was considered to be a “CRP responder” if their CRP level decreased by 50% or more within 72 hours after treatment and a “CRP nonresponder” if their CRP level did not drop by at least 50% within 72 hours of treatment. Patients who did not have a CRP level within the initial 48 hours of admission or a subsequent CRP measured in the 72 hours after treatment were considered to have an “undetermined CRP response” and excluded from the mortality analysis.

We observed a rise in CRP starting around day 6 among patients treated with corticosteroids and performed a post hoc analysis to determine if this was due to a selection effect whereby patients staying in the hospital longer had higher CRP levels or represented actual rise. In order to address this, we performed a stratified analysis comparing the trends in CRP levels among patients with a length of stay (LOS) of 7 or more days with trends among those with an LOS less than 7 days.

Statistical Analysis

To characterize differences in patients who received corticosteroids and those who did not, we examined their demographic, clinical characteristics, and admission laboratory values, using chi-square test for categorical variables and Kruskal-Wallis test for continuous variables (Table 1). The change in CRP levels from day 0 (presentation to the hospital) in both groups was plotted in a time-series analysis. For each day in the time series, the 95% CIs for the changes in CRP were computed using the t statistic for the corresponding distribution. The Kruskal-Wallis test was used to assess the significance of differences between groups at 72 hours after initiation of treatment.

After categorizing patients by CRP response, we compared demographic, clinical, and laboratory characteristics of patients who were CRP responsive with those of patients who were not, using the same tests of statistical inference mentioned above. To compare time to inpatient mortality differences between CRP response groups, Kaplan-Meier survival curves were generated and statistical significance determined via log-rank test. Univariable logistic regression was used to estimate the odds ratio of inpatient mortality between comparison groups in an unadjusted analysis. Last, to examine the independent association between CRP response and mortality, we constructed a multivariate model that included variables that were significantly associated with mortality in univariable analysis and considered to be important potential confounders by the authors. Details on variable selection for the model are listed in Appendix Table 1.

Data Collection

Data were directly extracted from our center’s electronic health record system. Data processing and recoding was performed using the Python programming language (version 2.7.17) and data analysis was done using Stata 12 (StataCorp LLC; 2011). This study was approved by the institutional review board of the Albert Einstein College of Medicine.

Corticosteroids vs No Corticosteroids

Between March 10, 2020, and May 2, 2020, a total of 3,382 adult patients were admitted for COVID-19 at Montefiore Medical Center. Of these, 2,707 patients met the study inclusion criteria, and 324 of those received corticosteroid treatment. Their demographic characteristics, comorbidities, and admission lab values are shown in Table 1. Patients who received corticosteroids were older, had higher comorbidity scores, were more likely to have asthma or chronic obstructive pulmonary disease, and were less likely to be full code status, compared with patients who did not receive corticosteroids. Patients who received corticosteroids also had higher initial white blood cell (WBC) and neutrophil counts but lower lymphocyte count. The two groups were comparable in initial creatinine level. Additional patient characteristics and addmission lab values are shown in Appendix Table 2.

Average change in CRP levels by hospital day for those who received corticosteroids and those who did not are shown in Figure 1A. Among patients who received corticosteroid treatment, there was a significant decrease in CRP level at 72 hours of treatment (P < .001). In the post hoc analysis of trends in CRP levels, we found that CRP levels among those treated with corticosteroids started to rise around day 6 after the initial drop. This trend was observed even after removing patients with shorter LOS (<7 days) (Figure 1B). The median durations of corticosteroid therapy were 3 days among patients whose LOS was less than 7 days and 6 days among those whose LOS was 7 days or greater. The rise in CRP level was seen at day 5 and day 7 within each group, respectively. Crude death rate was 41.7% among patients with LOS of less than 7 days and 40.6% in those with LOS of 7 days or greater.

CRP Responders vs Nonresponders

Among the 324 patients who received corticosteroids, 131 (40.4%) were classified as responders, 92 (28.4%) were classified as nonresponders, and 101 (31.2%) were undetermined. Characteristics of CRP responders and CRP nonresponders are shown in Table 2 and Appendix Table 3. CRP responders were more likely to have dementia, higher median admission platelet count, and fibrinogen level compared with CRP nonresponders. Patients whose CRP response was undetermined were excluded from the analysis. Their characteristics are shown in Appendix Table 4.

The observed inpatient mortality rate was 25.2% among CRP responders and 47.8% among CRP nonresponders. This was also demonstrated in the Kaplan-Meier survival curve (Figure 2). The odds of inpatient mortality among CRP responders was strongly and significantly reduced compared with those among nonresponders in an unadjusted analysis (odds ratio [OR], 0.37; 95% CI, 0.21-0.65; P = .001) and after adjustment for demographic and clinical characteristics including age, Charlson Comorbidity Index, initial WBC count, initial CRP level, and initial fibrinogen level (OR, 0.27; 95% CI, 0.14-0.54; P < .001). Details on how variables were operationalized and information on missing data are included in Appendix Table 1.

To explore whether this observed effect differed depending on severity of the respiratory illness, we examined the association between CRP response and mortality in subgroups stratified by intubation status. Within our cohort of 223 patients (92 CRP responders and 131 CRP nonresponders), 166 patients were never intubated, 50 patients were intubated in the first 48 hours, and 7 patients were intubated later on during the admission. The odds ratios for death among CRP responders vs nonresponders were 0.50 (P = .07) among patients never intubated and 0.46 (P = .2) among patients intubated within the initial 48 hours of admission.

In this retrospective study, we found that, on average, patients treated with corticosteroids had a swift and marked reduction in serum CRP. In addition, among patients treated with corticosteroids, those whose CRP was reduced by 50% or more within 72 hours after treatment had a dramatically reduced risk of inpatient mortality compared with the risk among nonresponders. This study contributes to a growing body of evidence that suggests that corticosteroids may be an efficacious treatment to reduce adverse events in patients with COVID-19 who have evidence of high levels of inflammation as measured by CRP level.^3,4,12,13

It remains unclear whether CRP is simply a biomarker of disease activity or if it plays a role in mediating inflammation. While CRP is commonly understood to be an acute phase reactant, it has been suggested that, after undergoing proteolysis, it functions as a chemoattractant for monocytes.¹⁴ In addition, it is now known that the inflammatory CD14+/CD16+ monocytes that express high levels of IL-6 are key drivers of the cytokine storm in COVID-19.¹⁵ Therefore, it may be possible that the high levels of circulating CRP in patients with cytokine storm recruits monocytes to the lungs, which leads to further lung injury.

Other mechanisms of immune dysregulation that may contribute to lung injury and respiratory failure in COVID-19, such as cytokine-induced T-cell suppression, have been proposed.^7,16 The related markers, such as levels of T-cells or specific cytokines, may therefore represent different but related underlying immune mechanisms affecting the clinical course of COVID-19 that may respond to different therapeutic modalities such as direct IL-6 blockade or chemokine receptor blockade, among others that are currently under investigation.^17,18

Regardless of the underlying mechanism of immune regulation, our study shows that serial measurement of CRP may serve as an early indicator of response to corticosteroids that correlates with decreased mortality. The association between CRP response and reduced risk of mortality was present in both subgroups, those requiring mechanical ventilation and those who did not. The risk reduction was similar in magnitude to the overall effect but was not statistically significant in either group. Interestingly, our time series analysis demonstrated a rise in CRP around day 6 among patients treated with corticosteroids (notably, most patients were treated for 5 to 7 days). Our post hoc analysis suggests that this may represent a “rebound” in inflammation after discontinuation of corticosteroids. However, the clinical significance of this rebound and whether a longer course of steroids would improve outcomes is not known. Because corticosteroid therapy may be associated with adverse effects in some patients,⁴ it is possible that CRP nonresponders represent a subset of patients in whom corticosteroids are not effective and for whom alternative therapies should be considered. In one study looking at the usefulness of IL-1 inhibition for severe COVID-19 infection, patients who received IL-1 inhibitor therapy had improved mortality and a significant decrease in CRP concentration as compared with the historical group.¹⁹ Finally, it is worth noting that, in one large retrospective study, there was harm associated with corticosteroid therapy in patients with low levels of CRP, and in the RECOVERY trial there was a trend toward harm for patients with no oxygen requirement.^3,4 Serial measurement of CRP may further identify the subset of patients in whom corticosteroid therapy might be harmful.

This study has several limitations. First, the retrospective nature of this study is inherently prone to selection bias, and despite the large number of clinical variables accounted for, unmeasured confounders may still exist. This study was also conducted at a single clinical center operating under emergency circumstances at a time during which healthcare resources were limited. Overall in-hospital mortality was high but similar to mortality rates reported at other hospitals in the New York City area during the same months.²⁰ The strengths of this study include a large cohort of COVID-19 patients from New York City, an epicenter of COVID-19, who received corticosteroids.

We found that therapy with corticosteroids in patients with COVID-19 is associated with a substantial reduction in CRP levels within 72 hours of therapy, and for those patients in whom CRP levels decrease by 50% or more, there is a significantly lower risk of inpatient mortality. Future studies are needed to validate these findings in other cohorts and to determine if markers other than CRP levels may be predictors of a therapeutic response or if CRP nonresponders would benefit from other targeted therapies.

Studies continue to demonstrate persistent gaps in equity for women and underrepresented minorities (URMs)¹ throughout nearly all aspects of academic medicine, including rank,^2-4 tenure,⁵ authorship,^6,7 funding opportunities,^8,9 awards,¹⁰ speakership,¹¹ leadership,^12,13 and salaries.^2,14,15 Hospital medicine, despite being a newer field,¹⁶ has also seen these disparities^17,18; however, there are numerous efforts in place to actively change our specialty’s course.^19-22 Hospital medicine is a field known for being a change agent in healthcare delivery,²² and its novel approaches are well poised to fundamentally shatter the glass ceilings imposed on traditionally underrepresented groups in medicine. The importance of diversity, equity, and inclusion (DEI) initiatives in healthcare has never been clearer,^23,24 particularly as they relate to cultural competence^25-28 and cultural humility,^29,30 implicit and explicit bias,²⁷ expanding care for underserved patient populations, supporting our workforce, and broadening research agendas.²⁸

In this article, we report DEI efforts within our division, focusing on the development of our strategic plan and specific outcomes related to compensation, recruitment, and policies.

Our Division’s Framework to DEI—“It Takes a Village”

Our Division of Hospital Medicine (DHM), previously within the Division of General Internal Medicine, was founded in October 2017. The DHM at the University of Colorado Hospital (UCH) is composed of 100 faculty members (70 physicians and 30 advanced-practice providers; 58% women and 42% men). In 2018, we implemented a stepwise approach to critically assess DEI within our group and to build a strategic plan to address the issues. Key areas of focus included institutional structures, our people, our environments, and our core missions (Figure 1 and Appendix Figure 1). DHM members helped drive our work and partnered with departmental, hospital, and school of medicine committees; national organizations; and collaborators to enhance implementation and dissemination efforts. In addition to stakeholder engagement, we utilized strategic planning and rapid Plan-Do-Study-Act (PDSA) cycles to advance DEI work in our DHM.

Needs Assessment

As a new division, we sought stakeholder feedback from division members. All faculty within the division were invited to attend a meeting in which issues related to DEI were discussed. A literature review that spanned both medical and nonmedical fields was also completed. Search terms included salary equity, gender equity, diverse teams, diversity recruitment and retention, diversifying leadership, and diverse speakers. Salaries, internally funded time, and other processes, such as recruitment, promotion, and hiring for leadership positions, were evaluated during the first year we became a division.

Interventions

TThrough this work, and with stakeholder engagement, we developed a divisional strategic plan to address DEI globally. Our strategic plan included developing a DEI director role to assist with overseeing DEI efforts. We have highlighted the various methods utilized for each component (Figure 1). This work occurred from October 2017 to December 2018.

Our institutional structures

Using best practices from both medical and nonmedical fields, we developed evidence-based approaches to compensation,³¹ recruitment,³² and policies that support and foster a culture of DEI.³² These strategies were used to support the following initiatives:

Compensation: transparent and consistent approaches based upon benchmarking with a framework of equal pay for equal work and similar advanced training/academic rank. In conjunction with efforts within the School of Medicine (SOM), Department of Medicine (DOM), and the UCH, our division sought to study salaries across DHM faculty members. We had an open call for faculty to participate in a newly developed DHM Compensation Committee, with the intent of rigorously examining our compensation practices and goals. Through faculty feedback and committee work, salary equity was defined as equal pay (ie, base salary for one clinical full-time equivalent [FTE]) for equal work based on academic rank and/or years of practice/advanced training. We also compared DHM salaries to regional academic hospital medicine groups and concluded that DHM salaries were lower than local and national benchmarks. This information was used to create a two-phase approach to increasing salaries for all individuals below the American Association of Medical Colleges (AAMC) benchmarks³³ for academic hospitalists. We also developed a stipend system for external roles that came with additional compensation and roles within our own division that came with additional pay (ie, nocturnist). Phase 1 focused on those whose salaries were furthest away from and below benchmark, and phase 2 targeted all remaining individuals below benchmark.

A similar review of FTEs (based on required number of shifts for a full-time hospitalist) tied to our internal DHM leadership positions was completed by the division head and director of DEI. Specifically, the mission for each of our internally funded roles, job descriptions, and responsibilities was reviewed to ensure equity in funding.

Recruitment and advancement: processes to ensure equity and diversity in recruitment, tracking, and reporting, working to eliminate/mitigate bias. In collaboration with members of the AAMC Group on Women in Medicine and Science (GWIMS) and coauthors from various institutions, we developed toolkits and checklists aimed at achieving equity and diversity within candidate pools and on major committees, including, but not limited to, search and promotion committees.³² Additionally, a checklist was developed to help recruit more diverse speakers, including women and URMs, for local, regional, and national conferences.

Policies: evidence-based approaches, tracking and reporting, standardized approaches to eliminate/mitigate bias, embracing nontraditional paths. In partnership with our departmental efforts, members of our team led data collection and reporting for salary benchmarking, leadership roles, and committee membership. This included developing surveys and reporting templates that can be used to identify disparities and inform future efforts. We worked to ensure that we have faculty representing our field at the department and SOM levels. Specifically, we made sure to nominate division members during open calls for departmental and schoolwide committees, including the promotions committee.

Our People

The faculty and staff within our division have been instrumental in moving efforts forward in the following important areas.

Leadership: develop the position of director of DEI as well as leadership structures to support and increase DEI. One of the first steps in our strategic plan was creating a director of DEI leadership role (Appendix Figure 2). The director is responsible for researching, applying, and promoting a broad scope of DEI initiatives and best practices within the DHM, DOM, and SOM (in collaboration with their leaders), including recruitment, retention, and promotion of medical students, residents, and faculty; educational program development; health disparities research; and community-engaged scholarship.

Support: develop family leave policies/develop flexible work policies. Several members of our division worked on departmental committees and served in leadership roles on staff and faculty council. Estimated costs were assessed. Through collective efforts of department leadership and division head support, the department approved parental leave to employees following the birth of an employee’s child or the placement of a child with an employee in connection with adoption or permanent foster care.

Mentorship/sponsorship: enhance faculty advancement programs/develop pipeline and trainings/collaborate with student groups and organizations/invest in all of our people. Faculty across our divisional sites have held important roles in developing pipeline programs for undergraduate students bound for health professions, as well as programs developed specifically for medical students and internal medicine residents. This includes two programs, the CU Hospitalist Scholars Program (CUHSP) and Leadership Education for Aspiring Doctors (LEAD), in which undergraduate students have the opportunity to round with hospital medicine teams, work on quality-improvement projects, and receive extensive mentorship and advising from a diverse faculty team. Additionally, our faculty advancement team within the DHM has grown and been restructured to include more defined goals and to ensure each faculty member has at least one mentor in their area of interest.

Supportive: lactation space and support/diverse space options/inclusive and diverse environments. We worked closely with hospital leadership to advocate for adequately equipped lactation spaces, including equipment such as pumps, refrigerators, and computer workstations. Additionally, our team members conducted environmental scans (eg, identified pictures, artwork, or other images that were not representative of a diverse and inclusive environment and raised concerns when the environment was not inclusive).

Measures

Our measures focused on (1) development and implementation of our DEI strategic plan, including new policies, processes, and practices related to key components of the DEI program; and (2) assessment of specific DEI programs, including pre-post salary data disparities based on rank and pre-post disparities for protected time for similar roles.

Analysis

Through rapid PDSA cycles, we evaluated salary equity, equity in leadership allotment, and committee membership. We have developed a tracking board to track progress of the multiple projects in the strategic plan.

Strategic Plan Development and Tracking

From October 2017 to December 2018, we developed a robust strategic plan and stepwise approach to DEI (Figure 1 and Figure 2). The director of DEI position was developed (see Appendix Figure 2 for job description) to help oversee these efforts. Figure 3 highlights the specific efforts and the progress made on implementation (ie, high-level dashboard or “tracking board”). While outcomes are still pending in the areas of recruitment and advancement and environment, we have made measurable improvements in compensation, as outlined in the following section.

Compensation

One year after the salary-equity interventions, all of our physician faculty’s salaries were at the goal benchmark (Table), and differences in salary for those in similar years of rank were nearly eliminated. Similarly, after implementing an internally consistent approach to assigning FTE for new and established positions within the division (ie, those that fall within the purview of the division), all faculty in similar types of roles had similar amounts of protected time.

Recruitment and Advancement

Toolkits³² and committee recommendations have been incorporated into division goals, though some aspects are still in implementation phases, as division-wide implicit bias training was delayed secondary to the COVID-19 pandemic. Key goals include: (1) implicit bias training for all members of major committees; (2) aiming for a goal of at least 40% representation of women and 40% URMs on committees; (3) having a diversity expert serve on each committee in order to identify and discuss any potential bias in the search and candidate-selection processes; and (4) careful tracking of diversity metrics in regard to diversity of candidates at each step of the interview and selection process.

Surveys and reporting templates for equity on committees and leadership positions have been developed and deployed. Data dashboards for our division have been developed as well (for compensation, leadership, and committee membership). A divisional dashboard to report recruitment efforts is in progress.

We have successfully nominated several faculty members to the SOM promotions committee and departmental committees during open calls for these positions. At the division level, we have also adapted internal policies to ensure promotion occurs on time and offers alternative pathways for faculty that may primarily focus on clinical pathways. All faculty who have gone up for promotion thus far have been successfully promoted in their desired pathway.

Environment

We successfully advocated and achieved adequately equipped lactation spaces, including equipment such as pumps, refrigerators, and computer workstations. This achievement was possible because of our hospital partners. Our efforts helped us acquire sufficient space and facilities such that nursing mothers can pump and still be able to answer phones, enter orders, and document visits.

Our team members conducted environmental scans and raised concerns when the environment was not inclusive, such as conference rooms with portraits of leadership that do not show diversity. The all-male pictures were removed from one frequently used departmental conference room, which will eventually house a diverse group of pictures and achievements.

We aim to eliminate bias by offering implicit bias training for our faculty. While this is presently required for those who serve on committees, in leadership positions, or those involved in recruitment and interviewing for the DOM, our goal is to eventually provide this training to all faculty and staff in the division. We have also incorporated DEI topics into our educational conferences for faculty, including sessions on recognizing bias in medicine, how to be an upstander/ally, and the impact of race and racism on medicine.

DISCUSSION

The important findings of this work are: (1) that successes in DEI can be achieved with strategic planning and stakeholder engagement; (2) through simple modification of processes, we can improve equity in compensation and FTE allotted to leadership; (3) though it takes time, diversity recruitment can be improved using sound, sustainable, evidence-based processes; (4) this work is time-intensive and challenging, requiring ongoing efforts to improve, modify, and enhance current efforts and future successes.

We have certainly made some progress with DEI initiatives within our division and have also learned a great deal from this experience. First, change is difficult for all parties involved, including those leading change and those affected by the changes. We purposely made an effort to facilitate discussions with all of the DHM faculty and staff to ensure that everyone felt included in this work and that everyone’s voice was heard. This was exemplified by inviting all faculty members to a feedback session in which we discussed DEI within our division and areas that we wanted to improve on. Early on, we were able to define what diversity, equity, and inclusion meant to us as a division and then use these definitions to develop tangible goals for all the areas of highest importance to the group.

By increasing faculty presence on key committees, such as the promotions committee, we now have faculty members who are well versed in promotions processes. We are fortunate to have a promotions process that supports faculty advancement for faculty with diverse interests that spans from supporting highly clinical faculty, clinician educators, as well as more traditional researchers.³⁴ By having hospitalists serve in these roles, we help to add to the diverse perspectives on these committees, including emphasizing the scholarship that is associated with quality improvement, as well as DEI efforts which can often be viewed as service as opposed to scholarship.

Clear communication and transparency were key to all of our DEI initiatives. We had monthly updates on our DEI efforts during business meetings and also held impromptu meetings (also known as flash mobs³⁵) to answer questions and discuss concerns in real time. As with all DEI work, it is important to know where you are starting (having accurate data and a clear understanding of the data) and be able to communicate that data to the group. For example, using AAMC salary benchmarking³³ as well as other benchmarks allowed us to accurately calculate variance among salaries and identify the appropriate goal salary for each of our faculty members. Likewise, by completing an in-depth inventory on the work being done by all of our faculty in leadership roles, we were able to standardize the compensation/FTE for each of these roles. Tracking these changes over time, via the use of dashboards in our case, allows for real-time measurements and accountability for all of those involved. Our end goal will be to have all of these initiatives feed into one large dashboard.

Collaborating with leadership and stakeholders in the DOM, SOM, and hospital helped to make our DEI initiatives successful. Much too often, we work in silos when it comes to DEI work. However, we tend to have similar goals and can achieve much more if we work together. Collaboration with multiple stakeholders allowed for wider dissemination and resulted in a larger impact to the campus and community at large. This has been exemplified by the committee composition guidance that has been utilized by the DOM, as well as implementation of campus-wide policies, specifically the parental leave policy, which our faculty members played an important role in creating. Likewise, it is important to look outside of our institutions and work with other hospital medicine groups around the country who are interested in promoting DEI.

We still have much work ahead of us. We are continuing to measure outcomes status postimplementation of the toolkit and checklists being used for diversity recruitment and committee composition. Additionally, we are actively working on several initiatives, including:

• Instituting implicit bias training for all of our faculty
• Partnering with national leaders and our hospital systems to develop zero-tolerance policies regarding abusive behaviors (verbal, physical, and other), racism, and sexism in the hospital and other work settings
• Development of specific recruitment strategies as a means of diversifying our healthcare workforce (of note, based on a 2020 survey of our faculty, in which there was a 70% response rate, 8.5% of our faculty identified as URMs)
• Completion of a diversity dashboard to track our progress in all of these efforts over time
• Development of a more robust pipeline to promotion and leadership for our URM faculty

This study has several strengths. Many of the plans and strategies described here can be used to guide others interested in implementing this work. Figure 2 provides a stepwise
approach to addressing DEI in hospital medicine groups and divisions. We conducted this work at a large academic medical center, and while it may not be generalizable, it does offer some ideas for others to consider in their own work to advance DEI at their institutions. There are also several limitations to this work. Eliminating salary inequities with our approach did take resources. We took advantage of already lower salaries and the need to increase salaries closer to benchmark and paired this effort with our DEI efforts to achieve salary equity. This required partnerships with the department and hospital. Efforts to advance DEI also take a lot of time and effort, and thus commitment from the division, department, and institution as a whole is key. While we have outcomes for our efforts related to salary equity, recruitment efforts should be realized over time, as currently it is too early to tell. We have highlighted the efforts that have been put in place at this time.

Using a systematic evidence-based approach with key stakeholder involvement, a division-wide DEI strategy was developed and implemented. While this work is still ongoing, short-term wins are possible, in particular around salary equity and development of policies and structures to promote DEI.

Studies continue to demonstrate persistent gaps in equity for women and underrepresented minorities (URMs)¹ throughout nearly all aspects of academic medicine, including rank,^2-4 tenure,⁵ authorship,^6,7 funding opportunities,^8,9 awards,¹⁰ speakership,¹¹ leadership,^12,13 and salaries.^2,14,15 Hospital medicine, despite being a newer field,¹⁶ has also seen these disparities^17,18; however, there are numerous efforts in place to actively change our specialty’s course.^19-22 Hospital medicine is a field known for being a change agent in healthcare delivery,²² and its novel approaches are well poised to fundamentally shatter the glass ceilings imposed on traditionally underrepresented groups in medicine. The importance of diversity, equity, and inclusion (DEI) initiatives in healthcare has never been clearer,^23,24 particularly as they relate to cultural competence^25-28 and cultural humility,^29,30 implicit and explicit bias,²⁷ expanding care for underserved patient populations, supporting our workforce, and broadening research agendas.²⁸

In this article, we report DEI efforts within our division, focusing on the development of our strategic plan and specific outcomes related to compensation, recruitment, and policies.

Our Division’s Framework to DEI—“It Takes a Village”

Our Division of Hospital Medicine (DHM), previously within the Division of General Internal Medicine, was founded in October 2017. The DHM at the University of Colorado Hospital (UCH) is composed of 100 faculty members (70 physicians and 30 advanced-practice providers; 58% women and 42% men). In 2018, we implemented a stepwise approach to critically assess DEI within our group and to build a strategic plan to address the issues. Key areas of focus included institutional structures, our people, our environments, and our core missions (Figure 1 and Appendix Figure 1). DHM members helped drive our work and partnered with departmental, hospital, and school of medicine committees; national organizations; and collaborators to enhance implementation and dissemination efforts. In addition to stakeholder engagement, we utilized strategic planning and rapid Plan-Do-Study-Act (PDSA) cycles to advance DEI work in our DHM.

Needs Assessment

As a new division, we sought stakeholder feedback from division members. All faculty within the division were invited to attend a meeting in which issues related to DEI were discussed. A literature review that spanned both medical and nonmedical fields was also completed. Search terms included salary equity, gender equity, diverse teams, diversity recruitment and retention, diversifying leadership, and diverse speakers. Salaries, internally funded time, and other processes, such as recruitment, promotion, and hiring for leadership positions, were evaluated during the first year we became a division.

Interventions

TThrough this work, and with stakeholder engagement, we developed a divisional strategic plan to address DEI globally. Our strategic plan included developing a DEI director role to assist with overseeing DEI efforts. We have highlighted the various methods utilized for each component (Figure 1). This work occurred from October 2017 to December 2018.

Our institutional structures

Using best practices from both medical and nonmedical fields, we developed evidence-based approaches to compensation,³¹ recruitment,³² and policies that support and foster a culture of DEI.³² These strategies were used to support the following initiatives:

Compensation: transparent and consistent approaches based upon benchmarking with a framework of equal pay for equal work and similar advanced training/academic rank. In conjunction with efforts within the School of Medicine (SOM), Department of Medicine (DOM), and the UCH, our division sought to study salaries across DHM faculty members. We had an open call for faculty to participate in a newly developed DHM Compensation Committee, with the intent of rigorously examining our compensation practices and goals. Through faculty feedback and committee work, salary equity was defined as equal pay (ie, base salary for one clinical full-time equivalent [FTE]) for equal work based on academic rank and/or years of practice/advanced training. We also compared DHM salaries to regional academic hospital medicine groups and concluded that DHM salaries were lower than local and national benchmarks. This information was used to create a two-phase approach to increasing salaries for all individuals below the American Association of Medical Colleges (AAMC) benchmarks³³ for academic hospitalists. We also developed a stipend system for external roles that came with additional compensation and roles within our own division that came with additional pay (ie, nocturnist). Phase 1 focused on those whose salaries were furthest away from and below benchmark, and phase 2 targeted all remaining individuals below benchmark.

A similar review of FTEs (based on required number of shifts for a full-time hospitalist) tied to our internal DHM leadership positions was completed by the division head and director of DEI. Specifically, the mission for each of our internally funded roles, job descriptions, and responsibilities was reviewed to ensure equity in funding.

Recruitment and advancement: processes to ensure equity and diversity in recruitment, tracking, and reporting, working to eliminate/mitigate bias. In collaboration with members of the AAMC Group on Women in Medicine and Science (GWIMS) and coauthors from various institutions, we developed toolkits and checklists aimed at achieving equity and diversity within candidate pools and on major committees, including, but not limited to, search and promotion committees.³² Additionally, a checklist was developed to help recruit more diverse speakers, including women and URMs, for local, regional, and national conferences.

Policies: evidence-based approaches, tracking and reporting, standardized approaches to eliminate/mitigate bias, embracing nontraditional paths. In partnership with our departmental efforts, members of our team led data collection and reporting for salary benchmarking, leadership roles, and committee membership. This included developing surveys and reporting templates that can be used to identify disparities and inform future efforts. We worked to ensure that we have faculty representing our field at the department and SOM levels. Specifically, we made sure to nominate division members during open calls for departmental and schoolwide committees, including the promotions committee.

Our People

The faculty and staff within our division have been instrumental in moving efforts forward in the following important areas.

Leadership: develop the position of director of DEI as well as leadership structures to support and increase DEI. One of the first steps in our strategic plan was creating a director of DEI leadership role (Appendix Figure 2). The director is responsible for researching, applying, and promoting a broad scope of DEI initiatives and best practices within the DHM, DOM, and SOM (in collaboration with their leaders), including recruitment, retention, and promotion of medical students, residents, and faculty; educational program development; health disparities research; and community-engaged scholarship.

Support: develop family leave policies/develop flexible work policies. Several members of our division worked on departmental committees and served in leadership roles on staff and faculty council. Estimated costs were assessed. Through collective efforts of department leadership and division head support, the department approved parental leave to employees following the birth of an employee’s child or the placement of a child with an employee in connection with adoption or permanent foster care.

Mentorship/sponsorship: enhance faculty advancement programs/develop pipeline and trainings/collaborate with student groups and organizations/invest in all of our people. Faculty across our divisional sites have held important roles in developing pipeline programs for undergraduate students bound for health professions, as well as programs developed specifically for medical students and internal medicine residents. This includes two programs, the CU Hospitalist Scholars Program (CUHSP) and Leadership Education for Aspiring Doctors (LEAD), in which undergraduate students have the opportunity to round with hospital medicine teams, work on quality-improvement projects, and receive extensive mentorship and advising from a diverse faculty team. Additionally, our faculty advancement team within the DHM has grown and been restructured to include more defined goals and to ensure each faculty member has at least one mentor in their area of interest.

Supportive: lactation space and support/diverse space options/inclusive and diverse environments. We worked closely with hospital leadership to advocate for adequately equipped lactation spaces, including equipment such as pumps, refrigerators, and computer workstations. Additionally, our team members conducted environmental scans (eg, identified pictures, artwork, or other images that were not representative of a diverse and inclusive environment and raised concerns when the environment was not inclusive).

Measures

Our measures focused on (1) development and implementation of our DEI strategic plan, including new policies, processes, and practices related to key components of the DEI program; and (2) assessment of specific DEI programs, including pre-post salary data disparities based on rank and pre-post disparities for protected time for similar roles.

Analysis

Through rapid PDSA cycles, we evaluated salary equity, equity in leadership allotment, and committee membership. We have developed a tracking board to track progress of the multiple projects in the strategic plan.

Strategic Plan Development and Tracking

From October 2017 to December 2018, we developed a robust strategic plan and stepwise approach to DEI (Figure 1 and Figure 2). The director of DEI position was developed (see Appendix Figure 2 for job description) to help oversee these efforts. Figure 3 highlights the specific efforts and the progress made on implementation (ie, high-level dashboard or “tracking board”). While outcomes are still pending in the areas of recruitment and advancement and environment, we have made measurable improvements in compensation, as outlined in the following section.

Compensation

One year after the salary-equity interventions, all of our physician faculty’s salaries were at the goal benchmark (Table), and differences in salary for those in similar years of rank were nearly eliminated. Similarly, after implementing an internally consistent approach to assigning FTE for new and established positions within the division (ie, those that fall within the purview of the division), all faculty in similar types of roles had similar amounts of protected time.

Recruitment and Advancement

Toolkits³² and committee recommendations have been incorporated into division goals, though some aspects are still in implementation phases, as division-wide implicit bias training was delayed secondary to the COVID-19 pandemic. Key goals include: (1) implicit bias training for all members of major committees; (2) aiming for a goal of at least 40% representation of women and 40% URMs on committees; (3) having a diversity expert serve on each committee in order to identify and discuss any potential bias in the search and candidate-selection processes; and (4) careful tracking of diversity metrics in regard to diversity of candidates at each step of the interview and selection process.

Surveys and reporting templates for equity on committees and leadership positions have been developed and deployed. Data dashboards for our division have been developed as well (for compensation, leadership, and committee membership). A divisional dashboard to report recruitment efforts is in progress.

We have successfully nominated several faculty members to the SOM promotions committee and departmental committees during open calls for these positions. At the division level, we have also adapted internal policies to ensure promotion occurs on time and offers alternative pathways for faculty that may primarily focus on clinical pathways. All faculty who have gone up for promotion thus far have been successfully promoted in their desired pathway.

Environment

We successfully advocated and achieved adequately equipped lactation spaces, including equipment such as pumps, refrigerators, and computer workstations. This achievement was possible because of our hospital partners. Our efforts helped us acquire sufficient space and facilities such that nursing mothers can pump and still be able to answer phones, enter orders, and document visits.

Our team members conducted environmental scans and raised concerns when the environment was not inclusive, such as conference rooms with portraits of leadership that do not show diversity. The all-male pictures were removed from one frequently used departmental conference room, which will eventually house a diverse group of pictures and achievements.

We aim to eliminate bias by offering implicit bias training for our faculty. While this is presently required for those who serve on committees, in leadership positions, or those involved in recruitment and interviewing for the DOM, our goal is to eventually provide this training to all faculty and staff in the division. We have also incorporated DEI topics into our educational conferences for faculty, including sessions on recognizing bias in medicine, how to be an upstander/ally, and the impact of race and racism on medicine.

DISCUSSION

The important findings of this work are: (1) that successes in DEI can be achieved with strategic planning and stakeholder engagement; (2) through simple modification of processes, we can improve equity in compensation and FTE allotted to leadership; (3) though it takes time, diversity recruitment can be improved using sound, sustainable, evidence-based processes; (4) this work is time-intensive and challenging, requiring ongoing efforts to improve, modify, and enhance current efforts and future successes.

We have certainly made some progress with DEI initiatives within our division and have also learned a great deal from this experience. First, change is difficult for all parties involved, including those leading change and those affected by the changes. We purposely made an effort to facilitate discussions with all of the DHM faculty and staff to ensure that everyone felt included in this work and that everyone’s voice was heard. This was exemplified by inviting all faculty members to a feedback session in which we discussed DEI within our division and areas that we wanted to improve on. Early on, we were able to define what diversity, equity, and inclusion meant to us as a division and then use these definitions to develop tangible goals for all the areas of highest importance to the group.

By increasing faculty presence on key committees, such as the promotions committee, we now have faculty members who are well versed in promotions processes. We are fortunate to have a promotions process that supports faculty advancement for faculty with diverse interests that spans from supporting highly clinical faculty, clinician educators, as well as more traditional researchers.³⁴ By having hospitalists serve in these roles, we help to add to the diverse perspectives on these committees, including emphasizing the scholarship that is associated with quality improvement, as well as DEI efforts which can often be viewed as service as opposed to scholarship.

Clear communication and transparency were key to all of our DEI initiatives. We had monthly updates on our DEI efforts during business meetings and also held impromptu meetings (also known as flash mobs³⁵) to answer questions and discuss concerns in real time. As with all DEI work, it is important to know where you are starting (having accurate data and a clear understanding of the data) and be able to communicate that data to the group. For example, using AAMC salary benchmarking³³ as well as other benchmarks allowed us to accurately calculate variance among salaries and identify the appropriate goal salary for each of our faculty members. Likewise, by completing an in-depth inventory on the work being done by all of our faculty in leadership roles, we were able to standardize the compensation/FTE for each of these roles. Tracking these changes over time, via the use of dashboards in our case, allows for real-time measurements and accountability for all of those involved. Our end goal will be to have all of these initiatives feed into one large dashboard.

Collaborating with leadership and stakeholders in the DOM, SOM, and hospital helped to make our DEI initiatives successful. Much too often, we work in silos when it comes to DEI work. However, we tend to have similar goals and can achieve much more if we work together. Collaboration with multiple stakeholders allowed for wider dissemination and resulted in a larger impact to the campus and community at large. This has been exemplified by the committee composition guidance that has been utilized by the DOM, as well as implementation of campus-wide policies, specifically the parental leave policy, which our faculty members played an important role in creating. Likewise, it is important to look outside of our institutions and work with other hospital medicine groups around the country who are interested in promoting DEI.

We still have much work ahead of us. We are continuing to measure outcomes status postimplementation of the toolkit and checklists being used for diversity recruitment and committee composition. Additionally, we are actively working on several initiatives, including:

• Instituting implicit bias training for all of our faculty
• Partnering with national leaders and our hospital systems to develop zero-tolerance policies regarding abusive behaviors (verbal, physical, and other), racism, and sexism in the hospital and other work settings
• Development of specific recruitment strategies as a means of diversifying our healthcare workforce (of note, based on a 2020 survey of our faculty, in which there was a 70% response rate, 8.5% of our faculty identified as URMs)
• Completion of a diversity dashboard to track our progress in all of these efforts over time
• Development of a more robust pipeline to promotion and leadership for our URM faculty

This study has several strengths. Many of the plans and strategies described here can be used to guide others interested in implementing this work. Figure 2 provides a stepwise
approach to addressing DEI in hospital medicine groups and divisions. We conducted this work at a large academic medical center, and while it may not be generalizable, it does offer some ideas for others to consider in their own work to advance DEI at their institutions. There are also several limitations to this work. Eliminating salary inequities with our approach did take resources. We took advantage of already lower salaries and the need to increase salaries closer to benchmark and paired this effort with our DEI efforts to achieve salary equity. This required partnerships with the department and hospital. Efforts to advance DEI also take a lot of time and effort, and thus commitment from the division, department, and institution as a whole is key. While we have outcomes for our efforts related to salary equity, recruitment efforts should be realized over time, as currently it is too early to tell. We have highlighted the efforts that have been put in place at this time.

Using a systematic evidence-based approach with key stakeholder involvement, a division-wide DEI strategy was developed and implemented. While this work is still ongoing, short-term wins are possible, in particular around salary equity and development of policies and structures to promote DEI.

Studies continue to demonstrate persistent gaps in equity for women and underrepresented minorities (URMs)¹ throughout nearly all aspects of academic medicine, including rank,^2-4 tenure,⁵ authorship,^6,7 funding opportunities,^8,9 awards,¹⁰ speakership,¹¹ leadership,^12,13 and salaries.^2,14,15 Hospital medicine, despite being a newer field,¹⁶ has also seen these disparities^17,18; however, there are numerous efforts in place to actively change our specialty’s course.^19-22 Hospital medicine is a field known for being a change agent in healthcare delivery,²² and its novel approaches are well poised to fundamentally shatter the glass ceilings imposed on traditionally underrepresented groups in medicine. The importance of diversity, equity, and inclusion (DEI) initiatives in healthcare has never been clearer,^23,24 particularly as they relate to cultural competence^25-28 and cultural humility,^29,30 implicit and explicit bias,²⁷ expanding care for underserved patient populations, supporting our workforce, and broadening research agendas.²⁸

In this article, we report DEI efforts within our division, focusing on the development of our strategic plan and specific outcomes related to compensation, recruitment, and policies.

Our Division’s Framework to DEI—“It Takes a Village”

Our Division of Hospital Medicine (DHM), previously within the Division of General Internal Medicine, was founded in October 2017. The DHM at the University of Colorado Hospital (UCH) is composed of 100 faculty members (70 physicians and 30 advanced-practice providers; 58% women and 42% men). In 2018, we implemented a stepwise approach to critically assess DEI within our group and to build a strategic plan to address the issues. Key areas of focus included institutional structures, our people, our environments, and our core missions (Figure 1 and Appendix Figure 1). DHM members helped drive our work and partnered with departmental, hospital, and school of medicine committees; national organizations; and collaborators to enhance implementation and dissemination efforts. In addition to stakeholder engagement, we utilized strategic planning and rapid Plan-Do-Study-Act (PDSA) cycles to advance DEI work in our DHM.

Needs Assessment

As a new division, we sought stakeholder feedback from division members. All faculty within the division were invited to attend a meeting in which issues related to DEI were discussed. A literature review that spanned both medical and nonmedical fields was also completed. Search terms included salary equity, gender equity, diverse teams, diversity recruitment and retention, diversifying leadership, and diverse speakers. Salaries, internally funded time, and other processes, such as recruitment, promotion, and hiring for leadership positions, were evaluated during the first year we became a division.

Interventions

TThrough this work, and with stakeholder engagement, we developed a divisional strategic plan to address DEI globally. Our strategic plan included developing a DEI director role to assist with overseeing DEI efforts. We have highlighted the various methods utilized for each component (Figure 1). This work occurred from October 2017 to December 2018.

Our institutional structures

Using best practices from both medical and nonmedical fields, we developed evidence-based approaches to compensation,³¹ recruitment,³² and policies that support and foster a culture of DEI.³² These strategies were used to support the following initiatives:

Compensation: transparent and consistent approaches based upon benchmarking with a framework of equal pay for equal work and similar advanced training/academic rank. In conjunction with efforts within the School of Medicine (SOM), Department of Medicine (DOM), and the UCH, our division sought to study salaries across DHM faculty members. We had an open call for faculty to participate in a newly developed DHM Compensation Committee, with the intent of rigorously examining our compensation practices and goals. Through faculty feedback and committee work, salary equity was defined as equal pay (ie, base salary for one clinical full-time equivalent [FTE]) for equal work based on academic rank and/or years of practice/advanced training. We also compared DHM salaries to regional academic hospital medicine groups and concluded that DHM salaries were lower than local and national benchmarks. This information was used to create a two-phase approach to increasing salaries for all individuals below the American Association of Medical Colleges (AAMC) benchmarks³³ for academic hospitalists. We also developed a stipend system for external roles that came with additional compensation and roles within our own division that came with additional pay (ie, nocturnist). Phase 1 focused on those whose salaries were furthest away from and below benchmark, and phase 2 targeted all remaining individuals below benchmark.

A similar review of FTEs (based on required number of shifts for a full-time hospitalist) tied to our internal DHM leadership positions was completed by the division head and director of DEI. Specifically, the mission for each of our internally funded roles, job descriptions, and responsibilities was reviewed to ensure equity in funding.

Recruitment and advancement: processes to ensure equity and diversity in recruitment, tracking, and reporting, working to eliminate/mitigate bias. In collaboration with members of the AAMC Group on Women in Medicine and Science (GWIMS) and coauthors from various institutions, we developed toolkits and checklists aimed at achieving equity and diversity within candidate pools and on major committees, including, but not limited to, search and promotion committees.³² Additionally, a checklist was developed to help recruit more diverse speakers, including women and URMs, for local, regional, and national conferences.

Policies: evidence-based approaches, tracking and reporting, standardized approaches to eliminate/mitigate bias, embracing nontraditional paths. In partnership with our departmental efforts, members of our team led data collection and reporting for salary benchmarking, leadership roles, and committee membership. This included developing surveys and reporting templates that can be used to identify disparities and inform future efforts. We worked to ensure that we have faculty representing our field at the department and SOM levels. Specifically, we made sure to nominate division members during open calls for departmental and schoolwide committees, including the promotions committee.

Our People

The faculty and staff within our division have been instrumental in moving efforts forward in the following important areas.

Leadership: develop the position of director of DEI as well as leadership structures to support and increase DEI. One of the first steps in our strategic plan was creating a director of DEI leadership role (Appendix Figure 2). The director is responsible for researching, applying, and promoting a broad scope of DEI initiatives and best practices within the DHM, DOM, and SOM (in collaboration with their leaders), including recruitment, retention, and promotion of medical students, residents, and faculty; educational program development; health disparities research; and community-engaged scholarship.

Support: develop family leave policies/develop flexible work policies. Several members of our division worked on departmental committees and served in leadership roles on staff and faculty council. Estimated costs were assessed. Through collective efforts of department leadership and division head support, the department approved parental leave to employees following the birth of an employee’s child or the placement of a child with an employee in connection with adoption or permanent foster care.

Mentorship/sponsorship: enhance faculty advancement programs/develop pipeline and trainings/collaborate with student groups and organizations/invest in all of our people. Faculty across our divisional sites have held important roles in developing pipeline programs for undergraduate students bound for health professions, as well as programs developed specifically for medical students and internal medicine residents. This includes two programs, the CU Hospitalist Scholars Program (CUHSP) and Leadership Education for Aspiring Doctors (LEAD), in which undergraduate students have the opportunity to round with hospital medicine teams, work on quality-improvement projects, and receive extensive mentorship and advising from a diverse faculty team. Additionally, our faculty advancement team within the DHM has grown and been restructured to include more defined goals and to ensure each faculty member has at least one mentor in their area of interest.

Supportive: lactation space and support/diverse space options/inclusive and diverse environments. We worked closely with hospital leadership to advocate for adequately equipped lactation spaces, including equipment such as pumps, refrigerators, and computer workstations. Additionally, our team members conducted environmental scans (eg, identified pictures, artwork, or other images that were not representative of a diverse and inclusive environment and raised concerns when the environment was not inclusive).

Measures

Our measures focused on (1) development and implementation of our DEI strategic plan, including new policies, processes, and practices related to key components of the DEI program; and (2) assessment of specific DEI programs, including pre-post salary data disparities based on rank and pre-post disparities for protected time for similar roles.

Analysis

Through rapid PDSA cycles, we evaluated salary equity, equity in leadership allotment, and committee membership. We have developed a tracking board to track progress of the multiple projects in the strategic plan.

Strategic Plan Development and Tracking

From October 2017 to December 2018, we developed a robust strategic plan and stepwise approach to DEI (Figure 1 and Figure 2). The director of DEI position was developed (see Appendix Figure 2 for job description) to help oversee these efforts. Figure 3 highlights the specific efforts and the progress made on implementation (ie, high-level dashboard or “tracking board”). While outcomes are still pending in the areas of recruitment and advancement and environment, we have made measurable improvements in compensation, as outlined in the following section.

Compensation

One year after the salary-equity interventions, all of our physician faculty’s salaries were at the goal benchmark (Table), and differences in salary for those in similar years of rank were nearly eliminated. Similarly, after implementing an internally consistent approach to assigning FTE for new and established positions within the division (ie, those that fall within the purview of the division), all faculty in similar types of roles had similar amounts of protected time.

Recruitment and Advancement

Toolkits³² and committee recommendations have been incorporated into division goals, though some aspects are still in implementation phases, as division-wide implicit bias training was delayed secondary to the COVID-19 pandemic. Key goals include: (1) implicit bias training for all members of major committees; (2) aiming for a goal of at least 40% representation of women and 40% URMs on committees; (3) having a diversity expert serve on each committee in order to identify and discuss any potential bias in the search and candidate-selection processes; and (4) careful tracking of diversity metrics in regard to diversity of candidates at each step of the interview and selection process.

Surveys and reporting templates for equity on committees and leadership positions have been developed and deployed. Data dashboards for our division have been developed as well (for compensation, leadership, and committee membership). A divisional dashboard to report recruitment efforts is in progress.

We have successfully nominated several faculty members to the SOM promotions committee and departmental committees during open calls for these positions. At the division level, we have also adapted internal policies to ensure promotion occurs on time and offers alternative pathways for faculty that may primarily focus on clinical pathways. All faculty who have gone up for promotion thus far have been successfully promoted in their desired pathway.

Environment

We successfully advocated and achieved adequately equipped lactation spaces, including equipment such as pumps, refrigerators, and computer workstations. This achievement was possible because of our hospital partners. Our efforts helped us acquire sufficient space and facilities such that nursing mothers can pump and still be able to answer phones, enter orders, and document visits.

Our team members conducted environmental scans and raised concerns when the environment was not inclusive, such as conference rooms with portraits of leadership that do not show diversity. The all-male pictures were removed from one frequently used departmental conference room, which will eventually house a diverse group of pictures and achievements.

We aim to eliminate bias by offering implicit bias training for our faculty. While this is presently required for those who serve on committees, in leadership positions, or those involved in recruitment and interviewing for the DOM, our goal is to eventually provide this training to all faculty and staff in the division. We have also incorporated DEI topics into our educational conferences for faculty, including sessions on recognizing bias in medicine, how to be an upstander/ally, and the impact of race and racism on medicine.

DISCUSSION

The important findings of this work are: (1) that successes in DEI can be achieved with strategic planning and stakeholder engagement; (2) through simple modification of processes, we can improve equity in compensation and FTE allotted to leadership; (3) though it takes time, diversity recruitment can be improved using sound, sustainable, evidence-based processes; (4) this work is time-intensive and challenging, requiring ongoing efforts to improve, modify, and enhance current efforts and future successes.

We have certainly made some progress with DEI initiatives within our division and have also learned a great deal from this experience. First, change is difficult for all parties involved, including those leading change and those affected by the changes. We purposely made an effort to facilitate discussions with all of the DHM faculty and staff to ensure that everyone felt included in this work and that everyone’s voice was heard. This was exemplified by inviting all faculty members to a feedback session in which we discussed DEI within our division and areas that we wanted to improve on. Early on, we were able to define what diversity, equity, and inclusion meant to us as a division and then use these definitions to develop tangible goals for all the areas of highest importance to the group.

By increasing faculty presence on key committees, such as the promotions committee, we now have faculty members who are well versed in promotions processes. We are fortunate to have a promotions process that supports faculty advancement for faculty with diverse interests that spans from supporting highly clinical faculty, clinician educators, as well as more traditional researchers.³⁴ By having hospitalists serve in these roles, we help to add to the diverse perspectives on these committees, including emphasizing the scholarship that is associated with quality improvement, as well as DEI efforts which can often be viewed as service as opposed to scholarship.

Clear communication and transparency were key to all of our DEI initiatives. We had monthly updates on our DEI efforts during business meetings and also held impromptu meetings (also known as flash mobs³⁵) to answer questions and discuss concerns in real time. As with all DEI work, it is important to know where you are starting (having accurate data and a clear understanding of the data) and be able to communicate that data to the group. For example, using AAMC salary benchmarking³³ as well as other benchmarks allowed us to accurately calculate variance among salaries and identify the appropriate goal salary for each of our faculty members. Likewise, by completing an in-depth inventory on the work being done by all of our faculty in leadership roles, we were able to standardize the compensation/FTE for each of these roles. Tracking these changes over time, via the use of dashboards in our case, allows for real-time measurements and accountability for all of those involved. Our end goal will be to have all of these initiatives feed into one large dashboard.

Collaborating with leadership and stakeholders in the DOM, SOM, and hospital helped to make our DEI initiatives successful. Much too often, we work in silos when it comes to DEI work. However, we tend to have similar goals and can achieve much more if we work together. Collaboration with multiple stakeholders allowed for wider dissemination and resulted in a larger impact to the campus and community at large. This has been exemplified by the committee composition guidance that has been utilized by the DOM, as well as implementation of campus-wide policies, specifically the parental leave policy, which our faculty members played an important role in creating. Likewise, it is important to look outside of our institutions and work with other hospital medicine groups around the country who are interested in promoting DEI.

We still have much work ahead of us. We are continuing to measure outcomes status postimplementation of the toolkit and checklists being used for diversity recruitment and committee composition. Additionally, we are actively working on several initiatives, including:

• Instituting implicit bias training for all of our faculty
• Partnering with national leaders and our hospital systems to develop zero-tolerance policies regarding abusive behaviors (verbal, physical, and other), racism, and sexism in the hospital and other work settings
• Development of specific recruitment strategies as a means of diversifying our healthcare workforce (of note, based on a 2020 survey of our faculty, in which there was a 70% response rate, 8.5% of our faculty identified as URMs)
• Completion of a diversity dashboard to track our progress in all of these efforts over time
• Development of a more robust pipeline to promotion and leadership for our URM faculty

This study has several strengths. Many of the plans and strategies described here can be used to guide others interested in implementing this work. Figure 2 provides a stepwise
approach to addressing DEI in hospital medicine groups and divisions. We conducted this work at a large academic medical center, and while it may not be generalizable, it does offer some ideas for others to consider in their own work to advance DEI at their institutions. There are also several limitations to this work. Eliminating salary inequities with our approach did take resources. We took advantage of already lower salaries and the need to increase salaries closer to benchmark and paired this effort with our DEI efforts to achieve salary equity. This required partnerships with the department and hospital. Efforts to advance DEI also take a lot of time and effort, and thus commitment from the division, department, and institution as a whole is key. While we have outcomes for our efforts related to salary equity, recruitment efforts should be realized over time, as currently it is too early to tell. We have highlighted the efforts that have been put in place at this time.

Using a systematic evidence-based approach with key stakeholder involvement, a division-wide DEI strategy was developed and implemented. While this work is still ongoing, short-term wins are possible, in particular around salary equity and development of policies and structures to promote DEI.

Staphylococcal scalded skin syndrome (SSSS) is an exfoliative toxin-mediated dermatitis that predominantly occurs in young children. Multiple recent reports indicate a rising incidence of this disease.^1-4 Recommended treatment for SSSS includes antistaphylococcal antibiotics and supportive care measures.^5,6 Elimination or reduction of the toxin-producing Staphylococcus aureus is thought to help limit disease progression and promote recovery. Experts advocate for the use of antibiotics even when there is no apparent focal source of infection, such as an abscess.^6,7

Several factors may affect antibiotic selection, including the desire to inhibit toxin production and to target the causative pathogen in a bactericidal fashion. Because SSSS is toxin mediated, clindamycin is often recommended because of its inhibition of toxin synthesis.^5,8 The clinical utility of adding other antibiotics to clindamycin for coverage of methicillin-sensitive S aureus (MSSA) or methicillin-resistant S aureus (MRSA) is uncertain. Several studies report MSSA to be the predominant pathogen identified by culture^2,9; however, SSSS caused by MRSA has been reported.^9-11 Additionally, bactericidal antibiotics (eg, nafcillin) have been considered to hold potential clinical advantage as compared with bacteriostatic antibiotics (eg, clindamycin), even though clinical studies have not clearly demonstrated this advantage in the general population.^12,13 Some experts recommend additional MRSA or MSSA coverage (such as vancomycin or nafcillin) in patients with high illness severity or nonresponse to therapy, or in areas where there is high prevalence of staphylococcal resistance to clindamycin.^5,7,9,14 Alternatively, for areas with low MRSA prevalence, monotherapy with an anti-MSSA antibiotic is another potential option. No recent studies have compared patient outcomes among antibiotic regimens in children with SSSS.

Knowledge of the outcomes associated with different antibiotic regimens for children hospitalized with SSSS is needed and could be used to improve patient outcomes and potentially promote antibiotic stewardship. In this study, our objectives were to (1) describe antibiotic regimens given to children hospitalized with SSSS, and (2) examine the association of three antibiotic regimens commonly used for SSSS (clindamycin monotherapy, clindamycin plus additional MSSA coverage, and clindamycin plus additional MRSA coverage) with patient outcomes of length of stay (LOS), treatment failure, and cost in a large cohort of children at US children’s hospitals.

We conducted a multicenter, retrospective cohort study utilizing data within the Pediatric Health Information System (PHIS) database from July 1, 2011, to June 30, 2016. Thirty-five free-standing tertiary care US children’s hospitals within 24 states were included. The Children’s Hospital Association (Lenexa, Kansas) maintains the PHIS database, which contains de-identified patient information, including diagnoses (with International Classification of Diseases, Ninth and Tenth Revision, Clinical Modification [ICD-9-CM, ICD-10-CM]), demographics, procedures, and daily billing records. Data quality and reliability are confirmed by participating institutions and the Children’s Hospital Association.¹⁵ The local institutional review board (IRB) deemed the study exempt from formal IRB review, as patient information was de-identified.

Study Population

We included hospitalized children aged newborn to 18 years with a primary or secondary diagnosis of SSSS (ICD-9, 695.81; ICD-10, L00). Children whose primary presentation and admission were to a PHIS hospital were included; children transferred from another hospital were excluded. The following exclusion criteria were based on previously published methodology.¹⁶ Children with complex chronic medical conditions as classified by Feudtner et al¹⁷ were excluded, since these children may require a different treatment approach than the general pediatric population. In order to decrease diagnostic ambiguity, we excluded children if an alternative dermatologic diagnosis was recorded as a principal or secondary diagnosis (eg, Stevens-Johnson syndrome or scarlet fever).¹⁶ Finally, hospitals with fewer than 10 children with SSSS during the study period were excluded.

Antibiotic Regimen Groups

We used PHIS daily billing codes to determine the antibiotics received by the study population. Children were classified into antibiotic regimen groups based on whether they received specific antibiotic combinations. Antibiotics received on any day during the hospitalization, including in the emergency department (ED), were used to assign patients to regimen groups. Antibiotics were classified into regimen groups based on consensus among study investigators, which included two board-certified pediatric infectious diseases specialists (A.C., R.M.). Antibiotic group definitions are listed in Table 1. Oral and intravenous (IV) therapies were grouped together for clindamycin, cephalexin/cefazolin, and linezolid because of good oral bioavailability in most situations.¹⁸ The three most common antistaphylococcal groups were chosen for further analysis: clindamycin alone, clindamycin plus MSSA coverage, and clindamycin plus MRSA coverage. The clindamycin group was defined as children with receipt of oral or IV clindamycin. Children who received clindamycin with additional MSSA coverage, such as cefazolin or nafcillin, were categorized as the clindamycin plus MSSA group. Children who received clindamycin with additional MRSA coverage, such as vancomycin or linezolid, were categorized as the clindamycin plus MRSA group. We chose not to include children who received the above regimens plus other antibiotics with partial antistaphylococcal activity, such as ampicillin, gentamicin, or ceftriaxone, in the clindamycin plus MSSA and clindamycin plus MRSA groups. We excluded these antibiotics to decrease the heterogeneity in the definition of regimen groups and allow a more direct comparison for effectiveness.

Covariates

Covariates included age, sex, ethnicity and/or race, payer type, level of care, illness severity, and region. The variable definitions below are in keeping with a prior study of SSSS.¹⁶ Age was categorized as: birth to 59 days, 2 to 11 months, 1 to 4 years (preschool age), 5 to 10 years (school age), and 11 to 18 years (adolescent). We examined infants younger than 60 days separately from older infants because this population may warrant additional treatment considerations. Race and ethnicity were categorized as White (non-Hispanic), African American (non-Hispanic), Hispanic, or other. Payer types included government, private, or other. Level of care was assigned as either intensive care or acute care. Illness severity was assigned using the All Patient Refined Diagnosis Related Group (APR-DRG; 3M Corporation, St. Paul, Minnesota) severity levels.¹⁹ In line with a prior study,¹⁶ we defined “low illness severity” as the APR-DRG minor (1) classification. The moderate (2), major (3), and extreme (4) classifications were defined as “moderate to high illness severity,” since there were very few classifications of major or extreme (<5%) illness severity. We categorized hospitals into the following US regions: Northeast, Midwest, South, and West.

Outcome Measures

The primary outcome was hospital LOS in days, and secondary outcomes were treatment failure and hospital costs. Hospital LOS was chosen as the primary outcome to represent the time needed for the child to show clinical improvement. Treatment failure was defined as a same-cause 14-day ED revisit or hospital readmission, and these were determined to be same-cause if a diagnosis for SSSS (ICD-9, 695.81; ICD-10, L00) was documented for the return encounter. The 14-day interval for readmission and ED revisit was chosen to measure any relapse of symptoms after completion of antibiotic therapy, similar to a prior study of treatment failure in skin and soft tissue infections.²⁰ Total costs of the hospitalization were estimated from charges using hospital- and year-specific cost-to-charge ratios. Subcategories of cost, including clinical, pharmacy, imaging, laboratory, supply, and other, were also compared among the three groups.

Statistical Analysis

Demographic and clinical characteristics of children were summarized using frequencies and percentages for categorical variables and medians with interquartile ranges (IQRs) for continuous variables. These were compared across antibiotic groups using chi-square and Kruskal–Wallis tests, respectively. In unadjusted analyses, outcomes were compared across antibiotic regimen groups using these same statistical tests. In order to account for patient clustering within hospitals, generalized linear mixed-effects models were used to model outcomes with a random intercept for each hospital. Models were adjusted for SSSS being listed as a principal or secondary diagnosis, race, illness severity, and level of care. We log-transformed LOS and cost data prior to modeling because of the nonnormal distributions for these data. Owing to the inability to measure the number of antibiotic doses, and to reduce the possibility of including children who received few regimen-defined combination antibiotics, a post hoc sensitivity analysis was performed. This analysis used an alternative definition for antibiotic regimen groups, for which children admitted for 2 or more calendar days must have received regimen-specified antibiotics on at least 2 days of the admission. Additionally, outcomes were stratified by low and moderate/high illness severity and compared across the three antibiotic regimen groups. All analyses were performed with SAS (SAS 9.4; SAS Institute, Cary, North Carolina), and P values of less than .05 were considered statistically significant.

Overall, 1,815 hospitalized children with SSSS were identified in the PHIS database, and after application of the exclusion criteria, 1,259 children remained, with 1,247 (99%) receiving antibiotics (Figure). The antibiotic regimens received by these children are described in Table 1. Of these, 828 children (66%) received one of the three most common antistaphylococcal regimens (clindamycin, clindamycin + MSSA, and clindamycin + MRSA) and were included for further analysis.

Characteristics of the 828 children are presented in Table 2. Most children (82%) were aged 4 years or younger, and distributions of age, sex, and insurance payer were similar among children receiving the three regimens. Thirty-two percent had moderate to high illness severity, and 3.5% required management in the intensive care setting. Of the three antibiotic regimens, clindamycin monotherapy was most common (47%), followed by clindamycin plus MSSA coverage (33%), and clindamycin plus MRSA coverage (20%). A higher proportion of children in the clindamycin plus MRSA group were African American and were hospitalized in the South. Children receiving clindamycin plus MRSA coverage had higher illness severity (44%) as compared with clindamycin monotherapy (28%) and clindamycin plus MSSA coverage (32%) (P = .001). Additionally, a larger proportion of children treated with clindamycin plus MRSA coverage were managed in the intensive care setting as compared with the clindamycin plus MSSA or clindamycin monotherapy groups.

Among the 828 children with SSSS, the median LOS was 2 days (IQR, 2-3), and treatment failure was 1.1% (95% CI, 0.4-1.8). After adjustment for illness severity, race, payer, and region (Table 3), the three antibiotic regimens were not associated with significant differences in LOS or treatment failure. Costs were significantly different among the three antibiotic regimens. Clindamycin plus MRSA coverage was associated with the greatest costs, whereas clindamycin monotherapy was associated with the lowest costs (mean, $5,348 vs $4,839, respectively; P < .001) (Table 3). In a sensitivity analysis using an alternative antibiotic regimen definition, we found results in line with the primary analysis, with no statistically significant differences in LOS (P = .44) or treatment failure (P = .54), but significant differences in cost (P < .001). Additionally, the same findings were present for LOS, treatment failure, and cost when outcomes were stratified by illness severity (Appendix Table). However, significant contributors to the higher cost in the clindamycin plus MRSA group did vary by illness severity stratification. Laboratory, supply, and pharmacy cost categories differed significantly among antibiotic groups for the low illness severity strata, whereas pharmacy was the only significant cost category difference in moderate/high illness severity.

Clindamycin monotherapy, clindamycin plus MSSA coverage, and clindamycin plus MRSA coverage are the most commonly administered antistaphylococcal antibiotic regimens for children hospitalized with SSSS at US children’s hospitals. Our multicenter study found that, across these antistaphylococcal antibiotic regimens, there were no associated differences in hospital LOS or treatment failure. However, the antibiotic regimens were associated with significant differences in overall hospital costs. These findings suggest that the use of clindamycin with additional MSSA or MRSA antibiotic coverage for children with SSSS may not be associated with additional clinical benefit, as compared with clindamycin monotherapy, and could potentially be more costly.

Prior literature describing LOS in relation to antibiotic use for children with SSSS is limited. Authors of a recent case series of 21 children in Philadelphia reported approximately 50% of children received clindamycin monotherapy or combination therapy, but patient outcomes such as LOS were not described.⁹ Clindamycin use and outcomes have been described in smaller studies and case reports of SSSS, which reported positive outcomes such as patient recovery and lack of disease recurrence.^2,9,21 A small retrospective, comparative effectiveness study of 30 neonates with SSSS examined beta-lactamase–resistant penicillin use with and without cephalosporins. They found no effect on LOS, but findings were limited by a small sample size.²² Our study cohort included relatively few neonates, and thus our findings may not be applicable to this population subgroup. We chose not to include regimens with third-generation cephalosporins or ampicillin, which may have limited the number of included neonates, because these antibiotics are frequently administered during evaluation for invasive bacterial infections.²³ We found a very low occurrence of treatment failure in our study cohort across all three groups, which is consistent with other studies of SSSS that report an overall good prognosis and low recurrence and/or readmission rates.^6,16,24 The low prevalence of treatment failure, however, precluded our ability to detect small differences among antibiotic regimen groups that may exist.

We observed that cost differed significantly across antibiotic regimen groups, with lowest cost associated with clindamycin monotherapy in adjusted analysis despite similar LOS. Even with our illness-severity adjustment, there may have been other unmeasured factors resulting in the higher cost associated with the combination groups. Hence, we also examined cost breakdown with a stratified analysis by illness severity. We found that pharmacy costs were significantly different among antibiotic groups in both illness severity strata, whereas those with low illness severity also differed by laboratory and supply costs. Thus, pharmacy cost differences may be the largest driver in the cost differential among groups. Lower cost in the clindamycin monotherapy group is likely due to administration of a single antibiotic. The reason for supply and laboratory cost differences is uncertain, but higher cost in the clindamycin plus MRSA group could possibly be from laboratory testing related to drug monitoring (eg, renal function testing or drug levels). While other studies have reported costs for hospitalized children with SSSS associated with different patient characteristics or diagnostic testing,^1,16 to our knowledge, no other studies have reported cost related to antibiotic regimens for SSSS. As healthcare reimbursements shift to value-based models, identifying treatment regimens with equal efficacy but lower cost will become increasingly important. Future studies should also examine other covariates and outcomes, such as oral vs parenteral antibiotic use, use of monitoring laboratories related to antibiotic choice, and adverse drug effects.

Several strengths and additional limitations apply to our study. Our study is one of the few to describe outcomes associated with antibiotic regimens for children with SSSS. With the PHIS database, we were able to include a large number of children with SSSS from children’s hospitals across the United States. Although the PHIS database affords these strengths, there are limitations inherent to administrative data. Children with SSSS were identified by documented ICD-9 and ICD-10 diagnostic codes, which might lead to misclassification. However, misclassification is less likely because only one ICD-9 and ICD-10 code exists for SSSS, and the characteristics of this condition are specific. Also, diagnostic codes for other dermatologic conditions (eg, scarlet fever) were excluded to further reduce the chance of misclassification. A limitation to our use of PHIS billing codes was the inability to confirm the dosage of antibiotics given, the number of doses, or whether antibiotics were prescribed upon discharge. Another limitation is that children whose antibiotic therapy was changed during hospitalization (eg, from clindamycin monotherapy to cefazolin monotherapy) were categorized into the combination groups. However, the sensitivity analysis performed based on a stricter antibiotic group definition (receipt of both antibiotics on at least 2 calendar days) did not alter the outcomes, which is reassuring. We were unable to assess the use of targeted antibiotic therapy because clinical data (eg, microbiology results) were not available. However, this may be less important because some literature suggests that cultures for S aureus are obtained infrequently² and may be difficult to interpret when obtained,²⁵ since culture growth can represent colonization rather than causative strains. An additional limitation is that administrative data do not include certain clinical outcomes, such as fever duration or degree of skin involvement, which could have differed among the groups. Last, the PHIS database only captures revisits or readmissions to PHIS hospitals, and so we are unable to exclude the possibility of a child being seen at or readmitted to another hospital.

Due to the observational design of this study and potential for incomplete measurement of illness severity, we recommend a future prospective trial with randomization to confirm these findings. One possible reason that LOS did not differ among groups is that the burden of clindamycin-resistant strains in our cohort could be low, and the addition of MSSA or MRSA coverage does not result in a clinically important increase in S aureus coverage. However, pooled pediatric hospital antibiogram data suggest the overall rate of clindamycin resistance is close to 20% in hospitals located in all US regions.²⁶ Limited studies also suggest that MSSA may be the predominant pathogen associated with SSSS.^2,9 To address this, future randomized trials could compare the effectiveness of clindamycin monotherapy to MSSA-specific agents like cefazolin or nafcillin. Unfortunately, anti-MSSA monotherapy was not evaluated in our study because very few children received this treatment. Using monotherapy as opposed to multiple antibiotics has the potential to promote antibiotic stewardship for antistaphylococcal antibiotics in the management of SSSS. Reducing unnecessary antibiotic use not only potentially affects antibiotic resistance, but could also benefit patients in reducing possible side effects, cost, and IV catheter complications.²⁷ However, acknowledging our study limitations, our findings should be applied cautiously in clinical settings, in the context of local antibiogram data, individual culture results, and specific patient factors. The local clindamycin resistance rate for both MSSA and MRSA should be considered. Many antibiotics chosen to treat MRSA—such as vancomycin and trimethoprim/sulfamethoxazole—will also have anti-MSSA activity and may have lower local resistance rates than clindamycin. Practitioners may also consider how each antibiotic kills bacteria; for example, beta-lactams rely on bacterial replication, but clindamycin does not. Each factor should influence how empiric treatment, whether monotherapy or combination, is chosen for children with SSSS.

In this large, multicenter cohort of hospitalized children with SSSS, we found that the addition of MSSA or MRSA coverage to clindamycin monotherapy was not associated with differences in outcomes of hospital LOS and treatment failure. Furthermore, clindamycin monotherapy was associated with lower overall cost. Prospective randomized studies are needed to confirm these findings and assess whether clindamycin monotherapy, monotherapy with an anti-MSSA antibiotic, or alternative regimens are most effective for treatment of children with SSSS.

Staphylococcal scalded skin syndrome (SSSS) is an exfoliative toxin-mediated dermatitis that predominantly occurs in young children. Multiple recent reports indicate a rising incidence of this disease.^1-4 Recommended treatment for SSSS includes antistaphylococcal antibiotics and supportive care measures.^5,6 Elimination or reduction of the toxin-producing Staphylococcus aureus is thought to help limit disease progression and promote recovery. Experts advocate for the use of antibiotics even when there is no apparent focal source of infection, such as an abscess.^6,7

Several factors may affect antibiotic selection, including the desire to inhibit toxin production and to target the causative pathogen in a bactericidal fashion. Because SSSS is toxin mediated, clindamycin is often recommended because of its inhibition of toxin synthesis.^5,8 The clinical utility of adding other antibiotics to clindamycin for coverage of methicillin-sensitive S aureus (MSSA) or methicillin-resistant S aureus (MRSA) is uncertain. Several studies report MSSA to be the predominant pathogen identified by culture^2,9; however, SSSS caused by MRSA has been reported.^9-11 Additionally, bactericidal antibiotics (eg, nafcillin) have been considered to hold potential clinical advantage as compared with bacteriostatic antibiotics (eg, clindamycin), even though clinical studies have not clearly demonstrated this advantage in the general population.^12,13 Some experts recommend additional MRSA or MSSA coverage (such as vancomycin or nafcillin) in patients with high illness severity or nonresponse to therapy, or in areas where there is high prevalence of staphylococcal resistance to clindamycin.^5,7,9,14 Alternatively, for areas with low MRSA prevalence, monotherapy with an anti-MSSA antibiotic is another potential option. No recent studies have compared patient outcomes among antibiotic regimens in children with SSSS.

Knowledge of the outcomes associated with different antibiotic regimens for children hospitalized with SSSS is needed and could be used to improve patient outcomes and potentially promote antibiotic stewardship. In this study, our objectives were to (1) describe antibiotic regimens given to children hospitalized with SSSS, and (2) examine the association of three antibiotic regimens commonly used for SSSS (clindamycin monotherapy, clindamycin plus additional MSSA coverage, and clindamycin plus additional MRSA coverage) with patient outcomes of length of stay (LOS), treatment failure, and cost in a large cohort of children at US children’s hospitals.

We conducted a multicenter, retrospective cohort study utilizing data within the Pediatric Health Information System (PHIS) database from July 1, 2011, to June 30, 2016. Thirty-five free-standing tertiary care US children’s hospitals within 24 states were included. The Children’s Hospital Association (Lenexa, Kansas) maintains the PHIS database, which contains de-identified patient information, including diagnoses (with International Classification of Diseases, Ninth and Tenth Revision, Clinical Modification [ICD-9-CM, ICD-10-CM]), demographics, procedures, and daily billing records. Data quality and reliability are confirmed by participating institutions and the Children’s Hospital Association.¹⁵ The local institutional review board (IRB) deemed the study exempt from formal IRB review, as patient information was de-identified.

Study Population

We included hospitalized children aged newborn to 18 years with a primary or secondary diagnosis of SSSS (ICD-9, 695.81; ICD-10, L00). Children whose primary presentation and admission were to a PHIS hospital were included; children transferred from another hospital were excluded. The following exclusion criteria were based on previously published methodology.¹⁶ Children with complex chronic medical conditions as classified by Feudtner et al¹⁷ were excluded, since these children may require a different treatment approach than the general pediatric population. In order to decrease diagnostic ambiguity, we excluded children if an alternative dermatologic diagnosis was recorded as a principal or secondary diagnosis (eg, Stevens-Johnson syndrome or scarlet fever).¹⁶ Finally, hospitals with fewer than 10 children with SSSS during the study period were excluded.

Antibiotic Regimen Groups

We used PHIS daily billing codes to determine the antibiotics received by the study population. Children were classified into antibiotic regimen groups based on whether they received specific antibiotic combinations. Antibiotics received on any day during the hospitalization, including in the emergency department (ED), were used to assign patients to regimen groups. Antibiotics were classified into regimen groups based on consensus among study investigators, which included two board-certified pediatric infectious diseases specialists (A.C., R.M.). Antibiotic group definitions are listed in Table 1. Oral and intravenous (IV) therapies were grouped together for clindamycin, cephalexin/cefazolin, and linezolid because of good oral bioavailability in most situations.¹⁸ The three most common antistaphylococcal groups were chosen for further analysis: clindamycin alone, clindamycin plus MSSA coverage, and clindamycin plus MRSA coverage. The clindamycin group was defined as children with receipt of oral or IV clindamycin. Children who received clindamycin with additional MSSA coverage, such as cefazolin or nafcillin, were categorized as the clindamycin plus MSSA group. Children who received clindamycin with additional MRSA coverage, such as vancomycin or linezolid, were categorized as the clindamycin plus MRSA group. We chose not to include children who received the above regimens plus other antibiotics with partial antistaphylococcal activity, such as ampicillin, gentamicin, or ceftriaxone, in the clindamycin plus MSSA and clindamycin plus MRSA groups. We excluded these antibiotics to decrease the heterogeneity in the definition of regimen groups and allow a more direct comparison for effectiveness.

Covariates

Covariates included age, sex, ethnicity and/or race, payer type, level of care, illness severity, and region. The variable definitions below are in keeping with a prior study of SSSS.¹⁶ Age was categorized as: birth to 59 days, 2 to 11 months, 1 to 4 years (preschool age), 5 to 10 years (school age), and 11 to 18 years (adolescent). We examined infants younger than 60 days separately from older infants because this population may warrant additional treatment considerations. Race and ethnicity were categorized as White (non-Hispanic), African American (non-Hispanic), Hispanic, or other. Payer types included government, private, or other. Level of care was assigned as either intensive care or acute care. Illness severity was assigned using the All Patient Refined Diagnosis Related Group (APR-DRG; 3M Corporation, St. Paul, Minnesota) severity levels.¹⁹ In line with a prior study,¹⁶ we defined “low illness severity” as the APR-DRG minor (1) classification. The moderate (2), major (3), and extreme (4) classifications were defined as “moderate to high illness severity,” since there were very few classifications of major or extreme (<5%) illness severity. We categorized hospitals into the following US regions: Northeast, Midwest, South, and West.

Outcome Measures

The primary outcome was hospital LOS in days, and secondary outcomes were treatment failure and hospital costs. Hospital LOS was chosen as the primary outcome to represent the time needed for the child to show clinical improvement. Treatment failure was defined as a same-cause 14-day ED revisit or hospital readmission, and these were determined to be same-cause if a diagnosis for SSSS (ICD-9, 695.81; ICD-10, L00) was documented for the return encounter. The 14-day interval for readmission and ED revisit was chosen to measure any relapse of symptoms after completion of antibiotic therapy, similar to a prior study of treatment failure in skin and soft tissue infections.²⁰ Total costs of the hospitalization were estimated from charges using hospital- and year-specific cost-to-charge ratios. Subcategories of cost, including clinical, pharmacy, imaging, laboratory, supply, and other, were also compared among the three groups.

Statistical Analysis

Demographic and clinical characteristics of children were summarized using frequencies and percentages for categorical variables and medians with interquartile ranges (IQRs) for continuous variables. These were compared across antibiotic groups using chi-square and Kruskal–Wallis tests, respectively. In unadjusted analyses, outcomes were compared across antibiotic regimen groups using these same statistical tests. In order to account for patient clustering within hospitals, generalized linear mixed-effects models were used to model outcomes with a random intercept for each hospital. Models were adjusted for SSSS being listed as a principal or secondary diagnosis, race, illness severity, and level of care. We log-transformed LOS and cost data prior to modeling because of the nonnormal distributions for these data. Owing to the inability to measure the number of antibiotic doses, and to reduce the possibility of including children who received few regimen-defined combination antibiotics, a post hoc sensitivity analysis was performed. This analysis used an alternative definition for antibiotic regimen groups, for which children admitted for 2 or more calendar days must have received regimen-specified antibiotics on at least 2 days of the admission. Additionally, outcomes were stratified by low and moderate/high illness severity and compared across the three antibiotic regimen groups. All analyses were performed with SAS (SAS 9.4; SAS Institute, Cary, North Carolina), and P values of less than .05 were considered statistically significant.

Overall, 1,815 hospitalized children with SSSS were identified in the PHIS database, and after application of the exclusion criteria, 1,259 children remained, with 1,247 (99%) receiving antibiotics (Figure). The antibiotic regimens received by these children are described in Table 1. Of these, 828 children (66%) received one of the three most common antistaphylococcal regimens (clindamycin, clindamycin + MSSA, and clindamycin + MRSA) and were included for further analysis.

Characteristics of the 828 children are presented in Table 2. Most children (82%) were aged 4 years or younger, and distributions of age, sex, and insurance payer were similar among children receiving the three regimens. Thirty-two percent had moderate to high illness severity, and 3.5% required management in the intensive care setting. Of the three antibiotic regimens, clindamycin monotherapy was most common (47%), followed by clindamycin plus MSSA coverage (33%), and clindamycin plus MRSA coverage (20%). A higher proportion of children in the clindamycin plus MRSA group were African American and were hospitalized in the South. Children receiving clindamycin plus MRSA coverage had higher illness severity (44%) as compared with clindamycin monotherapy (28%) and clindamycin plus MSSA coverage (32%) (P = .001). Additionally, a larger proportion of children treated with clindamycin plus MRSA coverage were managed in the intensive care setting as compared with the clindamycin plus MSSA or clindamycin monotherapy groups.

Among the 828 children with SSSS, the median LOS was 2 days (IQR, 2-3), and treatment failure was 1.1% (95% CI, 0.4-1.8). After adjustment for illness severity, race, payer, and region (Table 3), the three antibiotic regimens were not associated with significant differences in LOS or treatment failure. Costs were significantly different among the three antibiotic regimens. Clindamycin plus MRSA coverage was associated with the greatest costs, whereas clindamycin monotherapy was associated with the lowest costs (mean, $5,348 vs $4,839, respectively; P < .001) (Table 3). In a sensitivity analysis using an alternative antibiotic regimen definition, we found results in line with the primary analysis, with no statistically significant differences in LOS (P = .44) or treatment failure (P = .54), but significant differences in cost (P < .001). Additionally, the same findings were present for LOS, treatment failure, and cost when outcomes were stratified by illness severity (Appendix Table). However, significant contributors to the higher cost in the clindamycin plus MRSA group did vary by illness severity stratification. Laboratory, supply, and pharmacy cost categories differed significantly among antibiotic groups for the low illness severity strata, whereas pharmacy was the only significant cost category difference in moderate/high illness severity.

Clindamycin monotherapy, clindamycin plus MSSA coverage, and clindamycin plus MRSA coverage are the most commonly administered antistaphylococcal antibiotic regimens for children hospitalized with SSSS at US children’s hospitals. Our multicenter study found that, across these antistaphylococcal antibiotic regimens, there were no associated differences in hospital LOS or treatment failure. However, the antibiotic regimens were associated with significant differences in overall hospital costs. These findings suggest that the use of clindamycin with additional MSSA or MRSA antibiotic coverage for children with SSSS may not be associated with additional clinical benefit, as compared with clindamycin monotherapy, and could potentially be more costly.

Prior literature describing LOS in relation to antibiotic use for children with SSSS is limited. Authors of a recent case series of 21 children in Philadelphia reported approximately 50% of children received clindamycin monotherapy or combination therapy, but patient outcomes such as LOS were not described.⁹ Clindamycin use and outcomes have been described in smaller studies and case reports of SSSS, which reported positive outcomes such as patient recovery and lack of disease recurrence.^2,9,21 A small retrospective, comparative effectiveness study of 30 neonates with SSSS examined beta-lactamase–resistant penicillin use with and without cephalosporins. They found no effect on LOS, but findings were limited by a small sample size.²² Our study cohort included relatively few neonates, and thus our findings may not be applicable to this population subgroup. We chose not to include regimens with third-generation cephalosporins or ampicillin, which may have limited the number of included neonates, because these antibiotics are frequently administered during evaluation for invasive bacterial infections.²³ We found a very low occurrence of treatment failure in our study cohort across all three groups, which is consistent with other studies of SSSS that report an overall good prognosis and low recurrence and/or readmission rates.^6,16,24 The low prevalence of treatment failure, however, precluded our ability to detect small differences among antibiotic regimen groups that may exist.

We observed that cost differed significantly across antibiotic regimen groups, with lowest cost associated with clindamycin monotherapy in adjusted analysis despite similar LOS. Even with our illness-severity adjustment, there may have been other unmeasured factors resulting in the higher cost associated with the combination groups. Hence, we also examined cost breakdown with a stratified analysis by illness severity. We found that pharmacy costs were significantly different among antibiotic groups in both illness severity strata, whereas those with low illness severity also differed by laboratory and supply costs. Thus, pharmacy cost differences may be the largest driver in the cost differential among groups. Lower cost in the clindamycin monotherapy group is likely due to administration of a single antibiotic. The reason for supply and laboratory cost differences is uncertain, but higher cost in the clindamycin plus MRSA group could possibly be from laboratory testing related to drug monitoring (eg, renal function testing or drug levels). While other studies have reported costs for hospitalized children with SSSS associated with different patient characteristics or diagnostic testing,^1,16 to our knowledge, no other studies have reported cost related to antibiotic regimens for SSSS. As healthcare reimbursements shift to value-based models, identifying treatment regimens with equal efficacy but lower cost will become increasingly important. Future studies should also examine other covariates and outcomes, such as oral vs parenteral antibiotic use, use of monitoring laboratories related to antibiotic choice, and adverse drug effects.

Several strengths and additional limitations apply to our study. Our study is one of the few to describe outcomes associated with antibiotic regimens for children with SSSS. With the PHIS database, we were able to include a large number of children with SSSS from children’s hospitals across the United States. Although the PHIS database affords these strengths, there are limitations inherent to administrative data. Children with SSSS were identified by documented ICD-9 and ICD-10 diagnostic codes, which might lead to misclassification. However, misclassification is less likely because only one ICD-9 and ICD-10 code exists for SSSS, and the characteristics of this condition are specific. Also, diagnostic codes for other dermatologic conditions (eg, scarlet fever) were excluded to further reduce the chance of misclassification. A limitation to our use of PHIS billing codes was the inability to confirm the dosage of antibiotics given, the number of doses, or whether antibiotics were prescribed upon discharge. Another limitation is that children whose antibiotic therapy was changed during hospitalization (eg, from clindamycin monotherapy to cefazolin monotherapy) were categorized into the combination groups. However, the sensitivity analysis performed based on a stricter antibiotic group definition (receipt of both antibiotics on at least 2 calendar days) did not alter the outcomes, which is reassuring. We were unable to assess the use of targeted antibiotic therapy because clinical data (eg, microbiology results) were not available. However, this may be less important because some literature suggests that cultures for S aureus are obtained infrequently² and may be difficult to interpret when obtained,²⁵ since culture growth can represent colonization rather than causative strains. An additional limitation is that administrative data do not include certain clinical outcomes, such as fever duration or degree of skin involvement, which could have differed among the groups. Last, the PHIS database only captures revisits or readmissions to PHIS hospitals, and so we are unable to exclude the possibility of a child being seen at or readmitted to another hospital.

Due to the observational design of this study and potential for incomplete measurement of illness severity, we recommend a future prospective trial with randomization to confirm these findings. One possible reason that LOS did not differ among groups is that the burden of clindamycin-resistant strains in our cohort could be low, and the addition of MSSA or MRSA coverage does not result in a clinically important increase in S aureus coverage. However, pooled pediatric hospital antibiogram data suggest the overall rate of clindamycin resistance is close to 20% in hospitals located in all US regions.²⁶ Limited studies also suggest that MSSA may be the predominant pathogen associated with SSSS.^2,9 To address this, future randomized trials could compare the effectiveness of clindamycin monotherapy to MSSA-specific agents like cefazolin or nafcillin. Unfortunately, anti-MSSA monotherapy was not evaluated in our study because very few children received this treatment. Using monotherapy as opposed to multiple antibiotics has the potential to promote antibiotic stewardship for antistaphylococcal antibiotics in the management of SSSS. Reducing unnecessary antibiotic use not only potentially affects antibiotic resistance, but could also benefit patients in reducing possible side effects, cost, and IV catheter complications.²⁷ However, acknowledging our study limitations, our findings should be applied cautiously in clinical settings, in the context of local antibiogram data, individual culture results, and specific patient factors. The local clindamycin resistance rate for both MSSA and MRSA should be considered. Many antibiotics chosen to treat MRSA—such as vancomycin and trimethoprim/sulfamethoxazole—will also have anti-MSSA activity and may have lower local resistance rates than clindamycin. Practitioners may also consider how each antibiotic kills bacteria; for example, beta-lactams rely on bacterial replication, but clindamycin does not. Each factor should influence how empiric treatment, whether monotherapy or combination, is chosen for children with SSSS.

In this large, multicenter cohort of hospitalized children with SSSS, we found that the addition of MSSA or MRSA coverage to clindamycin monotherapy was not associated with differences in outcomes of hospital LOS and treatment failure. Furthermore, clindamycin monotherapy was associated with lower overall cost. Prospective randomized studies are needed to confirm these findings and assess whether clindamycin monotherapy, monotherapy with an anti-MSSA antibiotic, or alternative regimens are most effective for treatment of children with SSSS.

Staphylococcal scalded skin syndrome (SSSS) is an exfoliative toxin-mediated dermatitis that predominantly occurs in young children. Multiple recent reports indicate a rising incidence of this disease.^1-4 Recommended treatment for SSSS includes antistaphylococcal antibiotics and supportive care measures.^5,6 Elimination or reduction of the toxin-producing Staphylococcus aureus is thought to help limit disease progression and promote recovery. Experts advocate for the use of antibiotics even when there is no apparent focal source of infection, such as an abscess.^6,7

Several factors may affect antibiotic selection, including the desire to inhibit toxin production and to target the causative pathogen in a bactericidal fashion. Because SSSS is toxin mediated, clindamycin is often recommended because of its inhibition of toxin synthesis.^5,8 The clinical utility of adding other antibiotics to clindamycin for coverage of methicillin-sensitive S aureus (MSSA) or methicillin-resistant S aureus (MRSA) is uncertain. Several studies report MSSA to be the predominant pathogen identified by culture^2,9; however, SSSS caused by MRSA has been reported.^9-11 Additionally, bactericidal antibiotics (eg, nafcillin) have been considered to hold potential clinical advantage as compared with bacteriostatic antibiotics (eg, clindamycin), even though clinical studies have not clearly demonstrated this advantage in the general population.^12,13 Some experts recommend additional MRSA or MSSA coverage (such as vancomycin or nafcillin) in patients with high illness severity or nonresponse to therapy, or in areas where there is high prevalence of staphylococcal resistance to clindamycin.^5,7,9,14 Alternatively, for areas with low MRSA prevalence, monotherapy with an anti-MSSA antibiotic is another potential option. No recent studies have compared patient outcomes among antibiotic regimens in children with SSSS.

Knowledge of the outcomes associated with different antibiotic regimens for children hospitalized with SSSS is needed and could be used to improve patient outcomes and potentially promote antibiotic stewardship. In this study, our objectives were to (1) describe antibiotic regimens given to children hospitalized with SSSS, and (2) examine the association of three antibiotic regimens commonly used for SSSS (clindamycin monotherapy, clindamycin plus additional MSSA coverage, and clindamycin plus additional MRSA coverage) with patient outcomes of length of stay (LOS), treatment failure, and cost in a large cohort of children at US children’s hospitals.

We conducted a multicenter, retrospective cohort study utilizing data within the Pediatric Health Information System (PHIS) database from July 1, 2011, to June 30, 2016. Thirty-five free-standing tertiary care US children’s hospitals within 24 states were included. The Children’s Hospital Association (Lenexa, Kansas) maintains the PHIS database, which contains de-identified patient information, including diagnoses (with International Classification of Diseases, Ninth and Tenth Revision, Clinical Modification [ICD-9-CM, ICD-10-CM]), demographics, procedures, and daily billing records. Data quality and reliability are confirmed by participating institutions and the Children’s Hospital Association.¹⁵ The local institutional review board (IRB) deemed the study exempt from formal IRB review, as patient information was de-identified.

Study Population

We included hospitalized children aged newborn to 18 years with a primary or secondary diagnosis of SSSS (ICD-9, 695.81; ICD-10, L00). Children whose primary presentation and admission were to a PHIS hospital were included; children transferred from another hospital were excluded. The following exclusion criteria were based on previously published methodology.¹⁶ Children with complex chronic medical conditions as classified by Feudtner et al¹⁷ were excluded, since these children may require a different treatment approach than the general pediatric population. In order to decrease diagnostic ambiguity, we excluded children if an alternative dermatologic diagnosis was recorded as a principal or secondary diagnosis (eg, Stevens-Johnson syndrome or scarlet fever).¹⁶ Finally, hospitals with fewer than 10 children with SSSS during the study period were excluded.

Antibiotic Regimen Groups

We used PHIS daily billing codes to determine the antibiotics received by the study population. Children were classified into antibiotic regimen groups based on whether they received specific antibiotic combinations. Antibiotics received on any day during the hospitalization, including in the emergency department (ED), were used to assign patients to regimen groups. Antibiotics were classified into regimen groups based on consensus among study investigators, which included two board-certified pediatric infectious diseases specialists (A.C., R.M.). Antibiotic group definitions are listed in Table 1. Oral and intravenous (IV) therapies were grouped together for clindamycin, cephalexin/cefazolin, and linezolid because of good oral bioavailability in most situations.¹⁸ The three most common antistaphylococcal groups were chosen for further analysis: clindamycin alone, clindamycin plus MSSA coverage, and clindamycin plus MRSA coverage. The clindamycin group was defined as children with receipt of oral or IV clindamycin. Children who received clindamycin with additional MSSA coverage, such as cefazolin or nafcillin, were categorized as the clindamycin plus MSSA group. Children who received clindamycin with additional MRSA coverage, such as vancomycin or linezolid, were categorized as the clindamycin plus MRSA group. We chose not to include children who received the above regimens plus other antibiotics with partial antistaphylococcal activity, such as ampicillin, gentamicin, or ceftriaxone, in the clindamycin plus MSSA and clindamycin plus MRSA groups. We excluded these antibiotics to decrease the heterogeneity in the definition of regimen groups and allow a more direct comparison for effectiveness.

Covariates

Covariates included age, sex, ethnicity and/or race, payer type, level of care, illness severity, and region. The variable definitions below are in keeping with a prior study of SSSS.¹⁶ Age was categorized as: birth to 59 days, 2 to 11 months, 1 to 4 years (preschool age), 5 to 10 years (school age), and 11 to 18 years (adolescent). We examined infants younger than 60 days separately from older infants because this population may warrant additional treatment considerations. Race and ethnicity were categorized as White (non-Hispanic), African American (non-Hispanic), Hispanic, or other. Payer types included government, private, or other. Level of care was assigned as either intensive care or acute care. Illness severity was assigned using the All Patient Refined Diagnosis Related Group (APR-DRG; 3M Corporation, St. Paul, Minnesota) severity levels.¹⁹ In line with a prior study,¹⁶ we defined “low illness severity” as the APR-DRG minor (1) classification. The moderate (2), major (3), and extreme (4) classifications were defined as “moderate to high illness severity,” since there were very few classifications of major or extreme (<5%) illness severity. We categorized hospitals into the following US regions: Northeast, Midwest, South, and West.

Outcome Measures

The primary outcome was hospital LOS in days, and secondary outcomes were treatment failure and hospital costs. Hospital LOS was chosen as the primary outcome to represent the time needed for the child to show clinical improvement. Treatment failure was defined as a same-cause 14-day ED revisit or hospital readmission, and these were determined to be same-cause if a diagnosis for SSSS (ICD-9, 695.81; ICD-10, L00) was documented for the return encounter. The 14-day interval for readmission and ED revisit was chosen to measure any relapse of symptoms after completion of antibiotic therapy, similar to a prior study of treatment failure in skin and soft tissue infections.²⁰ Total costs of the hospitalization were estimated from charges using hospital- and year-specific cost-to-charge ratios. Subcategories of cost, including clinical, pharmacy, imaging, laboratory, supply, and other, were also compared among the three groups.

Statistical Analysis

Demographic and clinical characteristics of children were summarized using frequencies and percentages for categorical variables and medians with interquartile ranges (IQRs) for continuous variables. These were compared across antibiotic groups using chi-square and Kruskal–Wallis tests, respectively. In unadjusted analyses, outcomes were compared across antibiotic regimen groups using these same statistical tests. In order to account for patient clustering within hospitals, generalized linear mixed-effects models were used to model outcomes with a random intercept for each hospital. Models were adjusted for SSSS being listed as a principal or secondary diagnosis, race, illness severity, and level of care. We log-transformed LOS and cost data prior to modeling because of the nonnormal distributions for these data. Owing to the inability to measure the number of antibiotic doses, and to reduce the possibility of including children who received few regimen-defined combination antibiotics, a post hoc sensitivity analysis was performed. This analysis used an alternative definition for antibiotic regimen groups, for which children admitted for 2 or more calendar days must have received regimen-specified antibiotics on at least 2 days of the admission. Additionally, outcomes were stratified by low and moderate/high illness severity and compared across the three antibiotic regimen groups. All analyses were performed with SAS (SAS 9.4; SAS Institute, Cary, North Carolina), and P values of less than .05 were considered statistically significant.

Overall, 1,815 hospitalized children with SSSS were identified in the PHIS database, and after application of the exclusion criteria, 1,259 children remained, with 1,247 (99%) receiving antibiotics (Figure). The antibiotic regimens received by these children are described in Table 1. Of these, 828 children (66%) received one of the three most common antistaphylococcal regimens (clindamycin, clindamycin + MSSA, and clindamycin + MRSA) and were included for further analysis.

Characteristics of the 828 children are presented in Table 2. Most children (82%) were aged 4 years or younger, and distributions of age, sex, and insurance payer were similar among children receiving the three regimens. Thirty-two percent had moderate to high illness severity, and 3.5% required management in the intensive care setting. Of the three antibiotic regimens, clindamycin monotherapy was most common (47%), followed by clindamycin plus MSSA coverage (33%), and clindamycin plus MRSA coverage (20%). A higher proportion of children in the clindamycin plus MRSA group were African American and were hospitalized in the South. Children receiving clindamycin plus MRSA coverage had higher illness severity (44%) as compared with clindamycin monotherapy (28%) and clindamycin plus MSSA coverage (32%) (P = .001). Additionally, a larger proportion of children treated with clindamycin plus MRSA coverage were managed in the intensive care setting as compared with the clindamycin plus MSSA or clindamycin monotherapy groups.

Among the 828 children with SSSS, the median LOS was 2 days (IQR, 2-3), and treatment failure was 1.1% (95% CI, 0.4-1.8). After adjustment for illness severity, race, payer, and region (Table 3), the three antibiotic regimens were not associated with significant differences in LOS or treatment failure. Costs were significantly different among the three antibiotic regimens. Clindamycin plus MRSA coverage was associated with the greatest costs, whereas clindamycin monotherapy was associated with the lowest costs (mean, $5,348 vs $4,839, respectively; P < .001) (Table 3). In a sensitivity analysis using an alternative antibiotic regimen definition, we found results in line with the primary analysis, with no statistically significant differences in LOS (P = .44) or treatment failure (P = .54), but significant differences in cost (P < .001). Additionally, the same findings were present for LOS, treatment failure, and cost when outcomes were stratified by illness severity (Appendix Table). However, significant contributors to the higher cost in the clindamycin plus MRSA group did vary by illness severity stratification. Laboratory, supply, and pharmacy cost categories differed significantly among antibiotic groups for the low illness severity strata, whereas pharmacy was the only significant cost category difference in moderate/high illness severity.

Clindamycin monotherapy, clindamycin plus MSSA coverage, and clindamycin plus MRSA coverage are the most commonly administered antistaphylococcal antibiotic regimens for children hospitalized with SSSS at US children’s hospitals. Our multicenter study found that, across these antistaphylococcal antibiotic regimens, there were no associated differences in hospital LOS or treatment failure. However, the antibiotic regimens were associated with significant differences in overall hospital costs. These findings suggest that the use of clindamycin with additional MSSA or MRSA antibiotic coverage for children with SSSS may not be associated with additional clinical benefit, as compared with clindamycin monotherapy, and could potentially be more costly.

Prior literature describing LOS in relation to antibiotic use for children with SSSS is limited. Authors of a recent case series of 21 children in Philadelphia reported approximately 50% of children received clindamycin monotherapy or combination therapy, but patient outcomes such as LOS were not described.⁹ Clindamycin use and outcomes have been described in smaller studies and case reports of SSSS, which reported positive outcomes such as patient recovery and lack of disease recurrence.^2,9,21 A small retrospective, comparative effectiveness study of 30 neonates with SSSS examined beta-lactamase–resistant penicillin use with and without cephalosporins. They found no effect on LOS, but findings were limited by a small sample size.²² Our study cohort included relatively few neonates, and thus our findings may not be applicable to this population subgroup. We chose not to include regimens with third-generation cephalosporins or ampicillin, which may have limited the number of included neonates, because these antibiotics are frequently administered during evaluation for invasive bacterial infections.²³ We found a very low occurrence of treatment failure in our study cohort across all three groups, which is consistent with other studies of SSSS that report an overall good prognosis and low recurrence and/or readmission rates.^6,16,24 The low prevalence of treatment failure, however, precluded our ability to detect small differences among antibiotic regimen groups that may exist.

We observed that cost differed significantly across antibiotic regimen groups, with lowest cost associated with clindamycin monotherapy in adjusted analysis despite similar LOS. Even with our illness-severity adjustment, there may have been other unmeasured factors resulting in the higher cost associated with the combination groups. Hence, we also examined cost breakdown with a stratified analysis by illness severity. We found that pharmacy costs were significantly different among antibiotic groups in both illness severity strata, whereas those with low illness severity also differed by laboratory and supply costs. Thus, pharmacy cost differences may be the largest driver in the cost differential among groups. Lower cost in the clindamycin monotherapy group is likely due to administration of a single antibiotic. The reason for supply and laboratory cost differences is uncertain, but higher cost in the clindamycin plus MRSA group could possibly be from laboratory testing related to drug monitoring (eg, renal function testing or drug levels). While other studies have reported costs for hospitalized children with SSSS associated with different patient characteristics or diagnostic testing,^1,16 to our knowledge, no other studies have reported cost related to antibiotic regimens for SSSS. As healthcare reimbursements shift to value-based models, identifying treatment regimens with equal efficacy but lower cost will become increasingly important. Future studies should also examine other covariates and outcomes, such as oral vs parenteral antibiotic use, use of monitoring laboratories related to antibiotic choice, and adverse drug effects.

Several strengths and additional limitations apply to our study. Our study is one of the few to describe outcomes associated with antibiotic regimens for children with SSSS. With the PHIS database, we were able to include a large number of children with SSSS from children’s hospitals across the United States. Although the PHIS database affords these strengths, there are limitations inherent to administrative data. Children with SSSS were identified by documented ICD-9 and ICD-10 diagnostic codes, which might lead to misclassification. However, misclassification is less likely because only one ICD-9 and ICD-10 code exists for SSSS, and the characteristics of this condition are specific. Also, diagnostic codes for other dermatologic conditions (eg, scarlet fever) were excluded to further reduce the chance of misclassification. A limitation to our use of PHIS billing codes was the inability to confirm the dosage of antibiotics given, the number of doses, or whether antibiotics were prescribed upon discharge. Another limitation is that children whose antibiotic therapy was changed during hospitalization (eg, from clindamycin monotherapy to cefazolin monotherapy) were categorized into the combination groups. However, the sensitivity analysis performed based on a stricter antibiotic group definition (receipt of both antibiotics on at least 2 calendar days) did not alter the outcomes, which is reassuring. We were unable to assess the use of targeted antibiotic therapy because clinical data (eg, microbiology results) were not available. However, this may be less important because some literature suggests that cultures for S aureus are obtained infrequently² and may be difficult to interpret when obtained,²⁵ since culture growth can represent colonization rather than causative strains. An additional limitation is that administrative data do not include certain clinical outcomes, such as fever duration or degree of skin involvement, which could have differed among the groups. Last, the PHIS database only captures revisits or readmissions to PHIS hospitals, and so we are unable to exclude the possibility of a child being seen at or readmitted to another hospital.

Due to the observational design of this study and potential for incomplete measurement of illness severity, we recommend a future prospective trial with randomization to confirm these findings. One possible reason that LOS did not differ among groups is that the burden of clindamycin-resistant strains in our cohort could be low, and the addition of MSSA or MRSA coverage does not result in a clinically important increase in S aureus coverage. However, pooled pediatric hospital antibiogram data suggest the overall rate of clindamycin resistance is close to 20% in hospitals located in all US regions.²⁶ Limited studies also suggest that MSSA may be the predominant pathogen associated with SSSS.^2,9 To address this, future randomized trials could compare the effectiveness of clindamycin monotherapy to MSSA-specific agents like cefazolin or nafcillin. Unfortunately, anti-MSSA monotherapy was not evaluated in our study because very few children received this treatment. Using monotherapy as opposed to multiple antibiotics has the potential to promote antibiotic stewardship for antistaphylococcal antibiotics in the management of SSSS. Reducing unnecessary antibiotic use not only potentially affects antibiotic resistance, but could also benefit patients in reducing possible side effects, cost, and IV catheter complications.²⁷ However, acknowledging our study limitations, our findings should be applied cautiously in clinical settings, in the context of local antibiogram data, individual culture results, and specific patient factors. The local clindamycin resistance rate for both MSSA and MRSA should be considered. Many antibiotics chosen to treat MRSA—such as vancomycin and trimethoprim/sulfamethoxazole—will also have anti-MSSA activity and may have lower local resistance rates than clindamycin. Practitioners may also consider how each antibiotic kills bacteria; for example, beta-lactams rely on bacterial replication, but clindamycin does not. Each factor should influence how empiric treatment, whether monotherapy or combination, is chosen for children with SSSS.

In this large, multicenter cohort of hospitalized children with SSSS, we found that the addition of MSSA or MRSA coverage to clindamycin monotherapy was not associated with differences in outcomes of hospital LOS and treatment failure. Furthermore, clindamycin monotherapy was associated with lower overall cost. Prospective randomized studies are needed to confirm these findings and assess whether clindamycin monotherapy, monotherapy with an anti-MSSA antibiotic, or alternative regimens are most effective for treatment of children with SSSS.

Healthcare in rural areas faces increasing challenges due to community hospital closures, physician shortages, and a more concentrated population of older adults with higher rates of comorbid conditions than their urban counterparts.^1-3 Critical access hospitals (CAHs), which primarily serve rural areas, have fewer clinical capabilities, worse process-of-care measures, and higher mortality rates for some conditions when compared to non-CAHs.⁴ As such, CAHs are closing at record numbers across the United States,⁵ resulting in loss of available hospital beds and patient access to timely emergency services,⁶ which can worsen outcomes, further widening the rural-urban healthcare gap.^7,8 Furthermore, this strain on an overwhelmed health system in the most vulnerable areas restricts the ability to respond to healthcare crises like the coronavirus disease 2019 pandemic.⁹

Providing adequate staff for currently available hospital beds is also a problem in rural areas. Studies demonstrating improved outcomes, decreased length of stay (LOS), and increased quality with hospitalist services have resulted in a high demand for hospitalists nationwide.^10-12 Recruiting hospitalists to work in rural areas, however, has become increasingly challenging due to low-patient volumes, financial viability of hospitalist-model adoption, and provider shortages.^13,14 Recently, the Veterans Health Administration (VHA) reported a 28% nationwide shortage of hospitalists,¹⁵ which disproportionally affects rural VHA hospitals. Staffing difficulties and reliance on intermittent providers were reported by more than 80% of rural and low-complexity VHA facilities.¹⁶

Telehospitalist services (THS) can help deliver high-quality care to rural residents locally, decrease travel expenses, support hospital volume, and increase healthcare capacity in response to a pandemic.^14,17,18 Only a few studies have described THS (mostly with overnight or cross-coverage models directed to CAHs), and clinical outcomes have been inconsistently reported.^17,19-21 Furthermore, no program has been conducted within an integrated health system akin to the VHA. The primary objective of this quality improvement (QI) initiative was to perform a mixed-methods evaluation of THS between VHA hospitals to compare clinical outcomes and patient and staff satisfaction. Secondary outcomes included description of the implementation process, unexpected challenges, and subsequent QI initiatives. These results will expand the knowledge on feasibility of THS and provide implementation guidance.

A mixed-methods approach was used to evaluate outcomes of this QI project. Reporting follows the revised Standards for Quality Improvement Reporting Excellence (SQUIRE 2.0).²²

Context

The VHA is the largest integrated healthcare system in the United States, with more than 8 million veterans enrolled, more than 30% of whom reside in a rural area. The VHA comprises more than 1,000 outpatient clinics and 170 acute care VA Medical Centers,^23,24 including more than 35 rural and low-complexity hospitals.²⁵ Low-complexity hospitals are those with the lowest volume and levels of patient complexity and minimal or no teaching programs, research, intensive care unit (ICU) beds, and subspecialists. Lack of reimbursement and interstate licensing, often cited as barriers to telemedicine, do not apply to the VHA. The hub site was a large tertiary care (high-complexity) VHA hospital located in Iowa City, Iowa. The spoke site was a low-complexity (10-bed acute inpatient unit with no ICU) rural VA hospital located in Tomah, Wisconsin.

Study Population

The preimplementation cohort for comparison included all patients admitted between January 1, 2018, and January 6, 2019. The postimplementation study cohort included all observation and acute care admissions during the pilot phase (January 7 to May 3, 2019) and sustainability phase (July 15 to December 31, 2019). The postimplementation analysis excluded the time period of May 4 to July 14, 2019, due to an interruption (gap) in THS. The gap period allowed for preliminary data analysis, optimization of the telecommunication system, and the recruitment and training of additional providers who could provide long-term staffing to the service.

Intervention

Preimplementation

Prior to THS implementation, Tomah’s inpatient ward was staffed by one physician per shift, who could be a hospitalist, medical officer of the day (MOD), or an intermittent provider (locum tenens). Hospitalists covering the acute inpatient ward prior to the THS transitioned to cover weekends, nights, and urgent care service shifts.

We visited the spoke site and held information-sharing sessions with key stakeholders (administrators, clinician leaders, nurses, and ancillary staff) prior to kick-off. Recurrent phone meetings addressed anticipated and emerging challenges. Telehospitalist and local providers underwent technology and service training.

Technology and Connectivity

A low-cost technology system using tablet computers provided Health Insurance Portability and Accountability Act–compliant videoconferencing with a telehospitalist at the hub site. An Eko-Core digital stethoscope^® with a web-based audio stream was available. Telehospitalists conducted encounters from a private office space with telehealth capabilities. A total of $9,000 was spent on equipment at both sites. Due to connectivity problems and data limits, the tablets were switched to mobile computer-on-wheels workstations and hospital-based Wi-Fi for the sustainability phase.

THS Description

An experienced hub hospitalist, together with an advanced practice provider (APP; nurse practitioner [NP] or physician assistant [PA]), cared for all patients admitted to the 10-bed inpatient unit at the spoke site, Monday through Friday from 8:00 AM to 4:30 PM. The APP had limited or no prior experience in acute inpatient medicine. The telehospitalist worked as a team with the APP. The APP was the main point of contact for nurses, performed physical examinations, and directed patient care to their level of comfort (in a similar manner as a teaching team). The telehospitalist conducted bedside patient rounds, participated in multidisciplinary huddles, and shared clinical documentation and administrative duties with the APP. The telehospitalist was the primary staff for admitted patients and had full access to the electronic health record (EHR). The THS was staffed by 10 hospitalists during the study period. Overnight and weekend cross-coverage and admissions were performed by MODs, who also covered the urgent care and cross-covered other nonmedical units.

Quantitative Evaluation Methods

Workload and Clinical Outcomes

An EHR query identified all patients admitted during the pre- and postimplementation periods. Demographic data, clinical Nosos risk scores,^26,27 and top admission diagnoses were reported. Workload was evaluated using the average number of encounters per day and self-reported telehospitalist worksheets, which were cross-referenced with EHR data. Clinical outcomes included LOS, 30-day hospital readmission rate, 30-day standardized mortality (SMR30), in-hospital mortality, and VHA-specific inpatient quality metrics. Independent sample t tests for continuous variables and chi-square tests or Fisher’s exact test (for patient class) for categorical variables were used to compare pre- and postimplementation groups. Statistical process control (SPC) charts evaluated changes over time. All analyses were conducted using Microsoft Excel and R.²⁸

Provider Satisfaction

Anonymous surveys were distributed to spoke-site inpatient and administrative staff at 1 month and 12 months postimplementation, assessing satisfaction, technology/connectivity, communication, and challenges (Appendix Figure 1). Satisfaction of the telehospitalist physicians at the hub site was measured 12 months postimplementation by a 26-question survey assessing the same domains, plus quality of care (Appendix Figure 2).

Patient Satisfaction

The VHA Survey of Healthcare Experiences of Patients (SHEP), a version of the Hospital Consumer Assessment of Healthcare Providers and Systems Survey,^29,30 was mailed to all patients after discharge. Survey responses concerning inpatient provider care (eg, care coordination, communication, hospital rating, willingness to recommend the hospital) during the pre- and postimplementation phases were compared using a two-sample test of independent proportions. Responses obtained during May and June 2019 were excluded.

Qualitative Evaluation Methods

The qualitative researcher observed information-sharing meetings and facilitated unstructured interviews with clinical and administrative staff during site visits preimplementation and 3 months after implementation. Interviews with administrators and clinical staff addressed their experiences with the THS, staff’s perception of patient and family response to THS implementation, administrative impacts, challenges, and strengths. All interviews and meetings were documented with handwritten notes and audio recordings. Interview summary notes were typed into a Microsoft Word document, verified by the physician-investigator, and synthesized by inductive themes into site-visit reports. Audio recordings were uploaded to a secure computer, transcribed, and reviewed for accuracy. The qualitative researcher also identified emerging themes from open-ended survey responses. Process evaluation findings were shared with administration at the spoke site.

The authors had full access to, and took full responsibility for, the integrity of the data. The project was evaluated by the University of Iowa Institutional Review Board and the Iowa City VA Research and Development Committee and was determined to be a non–human-subjects QI project.

Quantitative Workload and Clinical Outcomes

There were 822 admissions during the preimplementation period and 550 admissions during the postimplementation period (253 during the pilot and 297 during sustainability phase). Patient characteristics pre- and postimplementation were not significantly different (Table 1). The median patient age was 65 years; 96% of patients were male, and 83% were rural residents. The most common admission diagnosis was alcohol-related (36%); regarding patient disposition, 78% of admissions were discharged home.

Workload

There were 502 patient encounters staffed by the telehospitalist in the pilot phase, with an average of 6.25 encounters per day, and a telehospitalist-reported workload of 7 hours per day. There were 538 patient encounters, with an average of 4.67 encounters per day and a workload of 5.6 hours per day in the sustainability phase. The average daily census decreased from 5.0 (SD, 1.1) patients per day during preimplementation to 3.1 (SD, 0.5) patients per day during postimplementation (Table 2). In some of the months during the study period, admissions decreased below the lower SPC limit, suggesting a significant change (Figure). Adjusted LOS was significantly lower, with 3.0 (SD, 0.7) days vs 2.3 (SD, 0.3) days in the pre- and postimplementation periods, respectively. Bed occupancy rates were significantly lower in the sustainability phase compared with the pilot phase and the preimplementation period. Readmission rates varied, ranging from <10% to >30%, not significantly different but slightly higher in the postimplementation period. Readmission rates for heart failure, chronic obstructive pulmonary disease, and pneumonia remained unchanged; other medical readmissions (mostly alcohol-related) were slightly higher in the postimplementation period.

In-hospital mortality and SMR30 did not change significantly, but there was improvement in the 12-month rolling average of the observed/expected SMR30 from 1.40 to 1.08. Additional VHA-specific quality metrics were monitored and showed either small improvements or no change (data not shown).

Satisfaction at Hub and Spoke Sites

After sending two reminder communications via email, the telehospitalist satisfaction survey had a total response rate of 90% (9/10). Telehospitalists were satisfied or very satisfied (89%) with the program and the local providers (88.9%), rating their experience as good or excellent (100%) (Table 3). Communication with patients, families, and local staff was noted as being “positive” or “mostly positive.” Telehospitalists reported confidence in the accuracy of their diagnoses and rated the quality of care as being equal to that of a face-to-face encounter. Connectivity problems were prevalent, although most providers were able to resort to a back-up plan. Other challenges included differences in culture and concerns about liability. We received 27 responses from the spoke-site satisfaction survey; the response rate could not be determined because the survey was distributed by the spoke site for anonymity. Of the respondents, 37% identified as nurses, 25.9% as healthcare providers (APPs or physicians), and 33.3% as other staff (eg, social worker, nutritionist, physical therapist, utilization management, administrators); 3.7% did not respond. Among the participants, 88% had personally interacted with the THS. Most providers and other staff perceived THS as valuable (57.1% and 77.8%, respectively) and were satisfied or highly satisfied with THS (57.1% and 55.6%, respectively). On average, nurses provided lower ratings across all survey items than providers and other staff. Challenges noted by all staff included issues with communication, workflow, and technology/connectivity.

Regarding patient satisfaction, the SHEP survey showed a significant improvement in care coordination (18%; P = .02) and a nonsignificant improvement in communications about medications (5%; P =.054). The remaining items in the survey, including overall hospital rating and willingness to recommend the hospital, were unchanged (Appendix Table).

Qualitative Strengths

Our process evaluation identified high quality of care and teamwork as contributors to the success of the program. Overall, staff credited perceived improvements in quality of care to the quality of providers staffing the THS, including the local APPs. Noting the telehospitalists’ knowledge base and level of engagement as key attributes, one staff member commented: “I prefer a telehospitalist that really care[s] about patients than some provider that is physically here but does not engage.” Staff perceived improvements in the continuity of care, as well as care processes such as handoffs and transitions of care.

Improvements in teamwork were perceived compared with the previous model of care. Telehospitalists were lauded for their professionalism and communication skills. Overall, nurses felt providers in the THS listened more to their views. In addition, nurse respondents felt they could learn from several providers and said they enjoyed the telehospitalists’ disposition to teach and discuss patient care. The responsiveness of the THS staff was instrumental in building teamwork and acceptance. A bedside interdisciplinary protocol was established for appropriate patients. Local staff felt this was crucial for teamwork and patient satisfaction. Telehospitalists reported high-value in interdisciplinary rounds, facilitating interaction with nurses and ancillary staff. Handoff problems were identified, leading to QI initiatives to mitigate those issues.

Challenges

The survey identified administrative barriers, technical difficulties, workflow constraints, and clinical concerns. The credentialing process was complicated, delaying the onboarding of telehospitalists. Internet connectivity was inconsistent, leading to disruption in video communications; however, during the sustainability phase, updated technology improved communications. The communication workflow was resisted by some nurses, who wanted to phone the telehospitalist directly rather than having the local APP as the first contact. Secure messaging was enabled to allow nurses direct contact during the sustainability phase.

Workload was a concern among telehospitalists and local staff. Telehospitalists perceived the documentation requirements and administrative workload to be two to three times higher than at other hospitals—despite the lower number of encounters. Finally, clinical concerns from spoke-site clinicians included a perceived rise in the acuity of patients (which was not evident by the Nosos score) and delayed decisions to transfer-out patients. These concerns were addressed with educational sessions for telehospitalists during the sustainability phase.

Additional Quality Improvement Projects

The implementation of THS resulted in QI initiatives at the spoke site, including an EHR-integrated handoff tool; a documentation evaluation that led to the elimination of duplicative, inefficient, and error-prone templates; and a revision of the alcohol withdrawal treatment protocol during the sustainability phase to reduce the use of intravenous benzodiazepines. A more comprehensive benzodiazepine-sparing alcohol withdrawal treatment protocol was also developed but was not implemented until after the study period (January 2020).

Our pre-post study evaluation found implementation of a THS to be noninferior to face-to-face care, with no significant change in mortality, readmission rate, or patient satisfaction. The significant improvement observed in LOS is consistent with the adoption of hospitalist models in other medical care settings,¹¹ but had not been reported by previous telehospitalist studies. For example, in their retrospective chart review comparing an NP-supported telehospitalist model to locum tenens hospitalists, Boltz et al found no difference in LOS.³¹ Moreover, as in our study, they found no differences in readmissions, mortality, and patient satisfaction.³¹ Similarly, Kuperman et al reported unchanged daily census, LOS, and transfer rates from a CAH with their virtual hospitalist program, but a decrease in the percentage of patients transferred-out from the emergency department, suggesting that more patients were treated locally.¹⁹

Reduction in LOS is one of the primary measures of efficiency in hospital care³¹; reducing LOS while maintaining the quality of care lowers hospital costs. The reduction in LOS in our study could be attributed to greater continuity of care, engagement/experience of the telehospitalists, or other factors. This decrease in LOS and slight reduction in admissions resulted in an overall lower daily census during the study period and impacted efficiency. Our study was unable to determine the cause for the reduction in admissions; however, several concurrent events, including the expansion of community-care options for veterans under the MISSION ACT (Maintaining Internal Systems and Strengthening Integrated Outside Networks Act) in June 2019, a nationwide smoking ban at VA facilities (October 2019), and a modification in the alcohol withdrawal treatment protocol might have influenced veterans’ choice of hospital.

Readmission rates were slightly higher, though nonsignificant, in the postimplementation period. Alcohol-related readmissions accounted for most readmissions; some of the protocol changes, such as admitting all patients with alcohol withdrawal to inpatient class instead of admitting some to the observation class, accounted for part of the increase in readmission rates. Readmission rates for other conditions such as chronic obstructive pulmonary disease, chronic heart failure, or pneumonia were not significantly different, suggesting that the reduction in LOS did not result in an unintended increased readmission rate for those conditions.

Rural hospitals are struggling with staffing and finances. Resorting to locum tenens staffing is costly and can result in variable quality of care.^32,33 APPs are increasingly taking on hospitalist positions, with 65% of adult hospitalist programs, including half of all VHA hospitals, employing NPs and PAs.^34,35 In response to this expanded scope of practice, hospitals employing APPs in hospitalist roles must comply with state and federal laws, which often require that APPs be supervised by or work in collaboration with an on-site or off-site physician. The THS is a great model to support APPs and address staffing and cost challenges in low-volume rural facilities, while maintaining quality of care. Some APP-telehospitalist programs similar to ours have reported cost reductions of up 58% compared to programs that employ locum tenens physicians.³¹ In our model, we assume that a single telehospitalist hub could provide coverage to two or three spoke sites with APP support, reducing staffing costs.

Hub telehospitalists reported satisfaction with the program, and they perceived the quality of care to be comparable to face-to-face encounters; their responses were consistent with those previously reported in an evaluation of telemedicine acute care by JaKa et al.²⁰ Spoke-site staff, however, had a mixed level of satisfaction, which was different from responses reported by JaKa et al.²⁰ The primary challenges encountered were technological and communication issues, differences in cultures of care between the hub and the spoke sites, and buy-in from frontline staff. Differences in expectations and unclear role definitions between the local APP and the telehospitalist were identified as contributors to dissatisfaction with the program by the nursing staff. Modifications to the communication processes between nurses and telehospitalists and role clarification improved the experience. Culture and practice differences between spoke physicians and the telehospitalist persisted throughout the program implementation, and likely affected the hub providers’ perception of the THS. This was evidenced by reluctance from spoke physicians to implement warm handoffs or participate in THS meetings and resistance to protocol changes. Additional evaluations, collaborations. and interventions are required to improve satisfaction of spoke-site staff.

This study has several limitations. First, the VHA is an integrated health system, one that serves an older, predominantly male patient population. Also, the lack of reimbursement and interstate licensing restrictions limit generalizability of these results to other CAHs or healthcare systems. Furthermore, the intervention was limited to a single rural site; while this allowed for a detailed evaluation, unique barriers or facilitators might exist that limit its applicability. In addition, QI initiatives implemented by the VHA during the project period might have confounded some of our results. Last, patient satisfaction survey data are overall limited in their ability to fully assess patient’s experience and satisfaction with the program. Further qualitative studies are needed to gain deeper insight into patient perspectives with the THS and whether modality of care delivery influences patients’ care decisions. Future studies should consider a multisite design with one or more hubs and multiple spoke sites.

Telehospitalist services are a feasible and safe approach to provide inpatient services and address staffing needs of rural hospitals. To enhance program performance, it is essential to ensure adequate technological quality, clearly delineate and define roles and responsibilities of the care team, and address communication issues or staff concerns in a timely manner.

The authors thank the staff, administration, and leadership at the Tomah and Iowa City VA Medical Centers for working with us on this project. They offer special thanks to Kevin Glenn, MD, MS, Ethan Kuperman, MD, MS, FHM, and Jennifer Chapin, MSN, RN, for sharing their expertise, and the telehealth team, including Nathaniel Samuelson, Angela McDowell, and Katrin Metcalf.

The views expressed in this article are those of the authors and do not necessarily represent the views of the Department of Veterans Affairs.

Healthcare in rural areas faces increasing challenges due to community hospital closures, physician shortages, and a more concentrated population of older adults with higher rates of comorbid conditions than their urban counterparts.^1-3 Critical access hospitals (CAHs), which primarily serve rural areas, have fewer clinical capabilities, worse process-of-care measures, and higher mortality rates for some conditions when compared to non-CAHs.⁴ As such, CAHs are closing at record numbers across the United States,⁵ resulting in loss of available hospital beds and patient access to timely emergency services,⁶ which can worsen outcomes, further widening the rural-urban healthcare gap.^7,8 Furthermore, this strain on an overwhelmed health system in the most vulnerable areas restricts the ability to respond to healthcare crises like the coronavirus disease 2019 pandemic.⁹

Providing adequate staff for currently available hospital beds is also a problem in rural areas. Studies demonstrating improved outcomes, decreased length of stay (LOS), and increased quality with hospitalist services have resulted in a high demand for hospitalists nationwide.^10-12 Recruiting hospitalists to work in rural areas, however, has become increasingly challenging due to low-patient volumes, financial viability of hospitalist-model adoption, and provider shortages.^13,14 Recently, the Veterans Health Administration (VHA) reported a 28% nationwide shortage of hospitalists,¹⁵ which disproportionally affects rural VHA hospitals. Staffing difficulties and reliance on intermittent providers were reported by more than 80% of rural and low-complexity VHA facilities.¹⁶

Telehospitalist services (THS) can help deliver high-quality care to rural residents locally, decrease travel expenses, support hospital volume, and increase healthcare capacity in response to a pandemic.^14,17,18 Only a few studies have described THS (mostly with overnight or cross-coverage models directed to CAHs), and clinical outcomes have been inconsistently reported.^17,19-21 Furthermore, no program has been conducted within an integrated health system akin to the VHA. The primary objective of this quality improvement (QI) initiative was to perform a mixed-methods evaluation of THS between VHA hospitals to compare clinical outcomes and patient and staff satisfaction. Secondary outcomes included description of the implementation process, unexpected challenges, and subsequent QI initiatives. These results will expand the knowledge on feasibility of THS and provide implementation guidance.

A mixed-methods approach was used to evaluate outcomes of this QI project. Reporting follows the revised Standards for Quality Improvement Reporting Excellence (SQUIRE 2.0).²²

Context

The VHA is the largest integrated healthcare system in the United States, with more than 8 million veterans enrolled, more than 30% of whom reside in a rural area. The VHA comprises more than 1,000 outpatient clinics and 170 acute care VA Medical Centers,^23,24 including more than 35 rural and low-complexity hospitals.²⁵ Low-complexity hospitals are those with the lowest volume and levels of patient complexity and minimal or no teaching programs, research, intensive care unit (ICU) beds, and subspecialists. Lack of reimbursement and interstate licensing, often cited as barriers to telemedicine, do not apply to the VHA. The hub site was a large tertiary care (high-complexity) VHA hospital located in Iowa City, Iowa. The spoke site was a low-complexity (10-bed acute inpatient unit with no ICU) rural VA hospital located in Tomah, Wisconsin.

Study Population

The preimplementation cohort for comparison included all patients admitted between January 1, 2018, and January 6, 2019. The postimplementation study cohort included all observation and acute care admissions during the pilot phase (January 7 to May 3, 2019) and sustainability phase (July 15 to December 31, 2019). The postimplementation analysis excluded the time period of May 4 to July 14, 2019, due to an interruption (gap) in THS. The gap period allowed for preliminary data analysis, optimization of the telecommunication system, and the recruitment and training of additional providers who could provide long-term staffing to the service.

Intervention

Preimplementation

Prior to THS implementation, Tomah’s inpatient ward was staffed by one physician per shift, who could be a hospitalist, medical officer of the day (MOD), or an intermittent provider (locum tenens). Hospitalists covering the acute inpatient ward prior to the THS transitioned to cover weekends, nights, and urgent care service shifts.

We visited the spoke site and held information-sharing sessions with key stakeholders (administrators, clinician leaders, nurses, and ancillary staff) prior to kick-off. Recurrent phone meetings addressed anticipated and emerging challenges. Telehospitalist and local providers underwent technology and service training.

Technology and Connectivity

A low-cost technology system using tablet computers provided Health Insurance Portability and Accountability Act–compliant videoconferencing with a telehospitalist at the hub site. An Eko-Core digital stethoscope^® with a web-based audio stream was available. Telehospitalists conducted encounters from a private office space with telehealth capabilities. A total of $9,000 was spent on equipment at both sites. Due to connectivity problems and data limits, the tablets were switched to mobile computer-on-wheels workstations and hospital-based Wi-Fi for the sustainability phase.

THS Description

An experienced hub hospitalist, together with an advanced practice provider (APP; nurse practitioner [NP] or physician assistant [PA]), cared for all patients admitted to the 10-bed inpatient unit at the spoke site, Monday through Friday from 8:00 AM to 4:30 PM. The APP had limited or no prior experience in acute inpatient medicine. The telehospitalist worked as a team with the APP. The APP was the main point of contact for nurses, performed physical examinations, and directed patient care to their level of comfort (in a similar manner as a teaching team). The telehospitalist conducted bedside patient rounds, participated in multidisciplinary huddles, and shared clinical documentation and administrative duties with the APP. The telehospitalist was the primary staff for admitted patients and had full access to the electronic health record (EHR). The THS was staffed by 10 hospitalists during the study period. Overnight and weekend cross-coverage and admissions were performed by MODs, who also covered the urgent care and cross-covered other nonmedical units.

Quantitative Evaluation Methods

Workload and Clinical Outcomes

An EHR query identified all patients admitted during the pre- and postimplementation periods. Demographic data, clinical Nosos risk scores,^26,27 and top admission diagnoses were reported. Workload was evaluated using the average number of encounters per day and self-reported telehospitalist worksheets, which were cross-referenced with EHR data. Clinical outcomes included LOS, 30-day hospital readmission rate, 30-day standardized mortality (SMR30), in-hospital mortality, and VHA-specific inpatient quality metrics. Independent sample t tests for continuous variables and chi-square tests or Fisher’s exact test (for patient class) for categorical variables were used to compare pre- and postimplementation groups. Statistical process control (SPC) charts evaluated changes over time. All analyses were conducted using Microsoft Excel and R.²⁸

Provider Satisfaction

Anonymous surveys were distributed to spoke-site inpatient and administrative staff at 1 month and 12 months postimplementation, assessing satisfaction, technology/connectivity, communication, and challenges (Appendix Figure 1). Satisfaction of the telehospitalist physicians at the hub site was measured 12 months postimplementation by a 26-question survey assessing the same domains, plus quality of care (Appendix Figure 2).

Patient Satisfaction

The VHA Survey of Healthcare Experiences of Patients (SHEP), a version of the Hospital Consumer Assessment of Healthcare Providers and Systems Survey,^29,30 was mailed to all patients after discharge. Survey responses concerning inpatient provider care (eg, care coordination, communication, hospital rating, willingness to recommend the hospital) during the pre- and postimplementation phases were compared using a two-sample test of independent proportions. Responses obtained during May and June 2019 were excluded.

Qualitative Evaluation Methods

The qualitative researcher observed information-sharing meetings and facilitated unstructured interviews with clinical and administrative staff during site visits preimplementation and 3 months after implementation. Interviews with administrators and clinical staff addressed their experiences with the THS, staff’s perception of patient and family response to THS implementation, administrative impacts, challenges, and strengths. All interviews and meetings were documented with handwritten notes and audio recordings. Interview summary notes were typed into a Microsoft Word document, verified by the physician-investigator, and synthesized by inductive themes into site-visit reports. Audio recordings were uploaded to a secure computer, transcribed, and reviewed for accuracy. The qualitative researcher also identified emerging themes from open-ended survey responses. Process evaluation findings were shared with administration at the spoke site.

The authors had full access to, and took full responsibility for, the integrity of the data. The project was evaluated by the University of Iowa Institutional Review Board and the Iowa City VA Research and Development Committee and was determined to be a non–human-subjects QI project.

Quantitative Workload and Clinical Outcomes

There were 822 admissions during the preimplementation period and 550 admissions during the postimplementation period (253 during the pilot and 297 during sustainability phase). Patient characteristics pre- and postimplementation were not significantly different (Table 1). The median patient age was 65 years; 96% of patients were male, and 83% were rural residents. The most common admission diagnosis was alcohol-related (36%); regarding patient disposition, 78% of admissions were discharged home.

Workload

There were 502 patient encounters staffed by the telehospitalist in the pilot phase, with an average of 6.25 encounters per day, and a telehospitalist-reported workload of 7 hours per day. There were 538 patient encounters, with an average of 4.67 encounters per day and a workload of 5.6 hours per day in the sustainability phase. The average daily census decreased from 5.0 (SD, 1.1) patients per day during preimplementation to 3.1 (SD, 0.5) patients per day during postimplementation (Table 2). In some of the months during the study period, admissions decreased below the lower SPC limit, suggesting a significant change (Figure). Adjusted LOS was significantly lower, with 3.0 (SD, 0.7) days vs 2.3 (SD, 0.3) days in the pre- and postimplementation periods, respectively. Bed occupancy rates were significantly lower in the sustainability phase compared with the pilot phase and the preimplementation period. Readmission rates varied, ranging from <10% to >30%, not significantly different but slightly higher in the postimplementation period. Readmission rates for heart failure, chronic obstructive pulmonary disease, and pneumonia remained unchanged; other medical readmissions (mostly alcohol-related) were slightly higher in the postimplementation period.

In-hospital mortality and SMR30 did not change significantly, but there was improvement in the 12-month rolling average of the observed/expected SMR30 from 1.40 to 1.08. Additional VHA-specific quality metrics were monitored and showed either small improvements or no change (data not shown).

Satisfaction at Hub and Spoke Sites

After sending two reminder communications via email, the telehospitalist satisfaction survey had a total response rate of 90% (9/10). Telehospitalists were satisfied or very satisfied (89%) with the program and the local providers (88.9%), rating their experience as good or excellent (100%) (Table 3). Communication with patients, families, and local staff was noted as being “positive” or “mostly positive.” Telehospitalists reported confidence in the accuracy of their diagnoses and rated the quality of care as being equal to that of a face-to-face encounter. Connectivity problems were prevalent, although most providers were able to resort to a back-up plan. Other challenges included differences in culture and concerns about liability. We received 27 responses from the spoke-site satisfaction survey; the response rate could not be determined because the survey was distributed by the spoke site for anonymity. Of the respondents, 37% identified as nurses, 25.9% as healthcare providers (APPs or physicians), and 33.3% as other staff (eg, social worker, nutritionist, physical therapist, utilization management, administrators); 3.7% did not respond. Among the participants, 88% had personally interacted with the THS. Most providers and other staff perceived THS as valuable (57.1% and 77.8%, respectively) and were satisfied or highly satisfied with THS (57.1% and 55.6%, respectively). On average, nurses provided lower ratings across all survey items than providers and other staff. Challenges noted by all staff included issues with communication, workflow, and technology/connectivity.

Regarding patient satisfaction, the SHEP survey showed a significant improvement in care coordination (18%; P = .02) and a nonsignificant improvement in communications about medications (5%; P =.054). The remaining items in the survey, including overall hospital rating and willingness to recommend the hospital, were unchanged (Appendix Table).

Qualitative Strengths

Our process evaluation identified high quality of care and teamwork as contributors to the success of the program. Overall, staff credited perceived improvements in quality of care to the quality of providers staffing the THS, including the local APPs. Noting the telehospitalists’ knowledge base and level of engagement as key attributes, one staff member commented: “I prefer a telehospitalist that really care[s] about patients than some provider that is physically here but does not engage.” Staff perceived improvements in the continuity of care, as well as care processes such as handoffs and transitions of care.

Improvements in teamwork were perceived compared with the previous model of care. Telehospitalists were lauded for their professionalism and communication skills. Overall, nurses felt providers in the THS listened more to their views. In addition, nurse respondents felt they could learn from several providers and said they enjoyed the telehospitalists’ disposition to teach and discuss patient care. The responsiveness of the THS staff was instrumental in building teamwork and acceptance. A bedside interdisciplinary protocol was established for appropriate patients. Local staff felt this was crucial for teamwork and patient satisfaction. Telehospitalists reported high-value in interdisciplinary rounds, facilitating interaction with nurses and ancillary staff. Handoff problems were identified, leading to QI initiatives to mitigate those issues.

Challenges

The survey identified administrative barriers, technical difficulties, workflow constraints, and clinical concerns. The credentialing process was complicated, delaying the onboarding of telehospitalists. Internet connectivity was inconsistent, leading to disruption in video communications; however, during the sustainability phase, updated technology improved communications. The communication workflow was resisted by some nurses, who wanted to phone the telehospitalist directly rather than having the local APP as the first contact. Secure messaging was enabled to allow nurses direct contact during the sustainability phase.

Workload was a concern among telehospitalists and local staff. Telehospitalists perceived the documentation requirements and administrative workload to be two to three times higher than at other hospitals—despite the lower number of encounters. Finally, clinical concerns from spoke-site clinicians included a perceived rise in the acuity of patients (which was not evident by the Nosos score) and delayed decisions to transfer-out patients. These concerns were addressed with educational sessions for telehospitalists during the sustainability phase.

Additional Quality Improvement Projects

The implementation of THS resulted in QI initiatives at the spoke site, including an EHR-integrated handoff tool; a documentation evaluation that led to the elimination of duplicative, inefficient, and error-prone templates; and a revision of the alcohol withdrawal treatment protocol during the sustainability phase to reduce the use of intravenous benzodiazepines. A more comprehensive benzodiazepine-sparing alcohol withdrawal treatment protocol was also developed but was not implemented until after the study period (January 2020).

Our pre-post study evaluation found implementation of a THS to be noninferior to face-to-face care, with no significant change in mortality, readmission rate, or patient satisfaction. The significant improvement observed in LOS is consistent with the adoption of hospitalist models in other medical care settings,¹¹ but had not been reported by previous telehospitalist studies. For example, in their retrospective chart review comparing an NP-supported telehospitalist model to locum tenens hospitalists, Boltz et al found no difference in LOS.³¹ Moreover, as in our study, they found no differences in readmissions, mortality, and patient satisfaction.³¹ Similarly, Kuperman et al reported unchanged daily census, LOS, and transfer rates from a CAH with their virtual hospitalist program, but a decrease in the percentage of patients transferred-out from the emergency department, suggesting that more patients were treated locally.¹⁹

Reduction in LOS is one of the primary measures of efficiency in hospital care³¹; reducing LOS while maintaining the quality of care lowers hospital costs. The reduction in LOS in our study could be attributed to greater continuity of care, engagement/experience of the telehospitalists, or other factors. This decrease in LOS and slight reduction in admissions resulted in an overall lower daily census during the study period and impacted efficiency. Our study was unable to determine the cause for the reduction in admissions; however, several concurrent events, including the expansion of community-care options for veterans under the MISSION ACT (Maintaining Internal Systems and Strengthening Integrated Outside Networks Act) in June 2019, a nationwide smoking ban at VA facilities (October 2019), and a modification in the alcohol withdrawal treatment protocol might have influenced veterans’ choice of hospital.

Readmission rates were slightly higher, though nonsignificant, in the postimplementation period. Alcohol-related readmissions accounted for most readmissions; some of the protocol changes, such as admitting all patients with alcohol withdrawal to inpatient class instead of admitting some to the observation class, accounted for part of the increase in readmission rates. Readmission rates for other conditions such as chronic obstructive pulmonary disease, chronic heart failure, or pneumonia were not significantly different, suggesting that the reduction in LOS did not result in an unintended increased readmission rate for those conditions.

Rural hospitals are struggling with staffing and finances. Resorting to locum tenens staffing is costly and can result in variable quality of care.^32,33 APPs are increasingly taking on hospitalist positions, with 65% of adult hospitalist programs, including half of all VHA hospitals, employing NPs and PAs.^34,35 In response to this expanded scope of practice, hospitals employing APPs in hospitalist roles must comply with state and federal laws, which often require that APPs be supervised by or work in collaboration with an on-site or off-site physician. The THS is a great model to support APPs and address staffing and cost challenges in low-volume rural facilities, while maintaining quality of care. Some APP-telehospitalist programs similar to ours have reported cost reductions of up 58% compared to programs that employ locum tenens physicians.³¹ In our model, we assume that a single telehospitalist hub could provide coverage to two or three spoke sites with APP support, reducing staffing costs.

Hub telehospitalists reported satisfaction with the program, and they perceived the quality of care to be comparable to face-to-face encounters; their responses were consistent with those previously reported in an evaluation of telemedicine acute care by JaKa et al.²⁰ Spoke-site staff, however, had a mixed level of satisfaction, which was different from responses reported by JaKa et al.²⁰ The primary challenges encountered were technological and communication issues, differences in cultures of care between the hub and the spoke sites, and buy-in from frontline staff. Differences in expectations and unclear role definitions between the local APP and the telehospitalist were identified as contributors to dissatisfaction with the program by the nursing staff. Modifications to the communication processes between nurses and telehospitalists and role clarification improved the experience. Culture and practice differences between spoke physicians and the telehospitalist persisted throughout the program implementation, and likely affected the hub providers’ perception of the THS. This was evidenced by reluctance from spoke physicians to implement warm handoffs or participate in THS meetings and resistance to protocol changes. Additional evaluations, collaborations. and interventions are required to improve satisfaction of spoke-site staff.

This study has several limitations. First, the VHA is an integrated health system, one that serves an older, predominantly male patient population. Also, the lack of reimbursement and interstate licensing restrictions limit generalizability of these results to other CAHs or healthcare systems. Furthermore, the intervention was limited to a single rural site; while this allowed for a detailed evaluation, unique barriers or facilitators might exist that limit its applicability. In addition, QI initiatives implemented by the VHA during the project period might have confounded some of our results. Last, patient satisfaction survey data are overall limited in their ability to fully assess patient’s experience and satisfaction with the program. Further qualitative studies are needed to gain deeper insight into patient perspectives with the THS and whether modality of care delivery influences patients’ care decisions. Future studies should consider a multisite design with one or more hubs and multiple spoke sites.

Telehospitalist services are a feasible and safe approach to provide inpatient services and address staffing needs of rural hospitals. To enhance program performance, it is essential to ensure adequate technological quality, clearly delineate and define roles and responsibilities of the care team, and address communication issues or staff concerns in a timely manner.

The authors thank the staff, administration, and leadership at the Tomah and Iowa City VA Medical Centers for working with us on this project. They offer special thanks to Kevin Glenn, MD, MS, Ethan Kuperman, MD, MS, FHM, and Jennifer Chapin, MSN, RN, for sharing their expertise, and the telehealth team, including Nathaniel Samuelson, Angela McDowell, and Katrin Metcalf.

The views expressed in this article are those of the authors and do not necessarily represent the views of the Department of Veterans Affairs.

Healthcare in rural areas faces increasing challenges due to community hospital closures, physician shortages, and a more concentrated population of older adults with higher rates of comorbid conditions than their urban counterparts.^1-3 Critical access hospitals (CAHs), which primarily serve rural areas, have fewer clinical capabilities, worse process-of-care measures, and higher mortality rates for some conditions when compared to non-CAHs.⁴ As such, CAHs are closing at record numbers across the United States,⁵ resulting in loss of available hospital beds and patient access to timely emergency services,⁶ which can worsen outcomes, further widening the rural-urban healthcare gap.^7,8 Furthermore, this strain on an overwhelmed health system in the most vulnerable areas restricts the ability to respond to healthcare crises like the coronavirus disease 2019 pandemic.⁹

Providing adequate staff for currently available hospital beds is also a problem in rural areas. Studies demonstrating improved outcomes, decreased length of stay (LOS), and increased quality with hospitalist services have resulted in a high demand for hospitalists nationwide.^10-12 Recruiting hospitalists to work in rural areas, however, has become increasingly challenging due to low-patient volumes, financial viability of hospitalist-model adoption, and provider shortages.^13,14 Recently, the Veterans Health Administration (VHA) reported a 28% nationwide shortage of hospitalists,¹⁵ which disproportionally affects rural VHA hospitals. Staffing difficulties and reliance on intermittent providers were reported by more than 80% of rural and low-complexity VHA facilities.¹⁶

Telehospitalist services (THS) can help deliver high-quality care to rural residents locally, decrease travel expenses, support hospital volume, and increase healthcare capacity in response to a pandemic.^14,17,18 Only a few studies have described THS (mostly with overnight or cross-coverage models directed to CAHs), and clinical outcomes have been inconsistently reported.^17,19-21 Furthermore, no program has been conducted within an integrated health system akin to the VHA. The primary objective of this quality improvement (QI) initiative was to perform a mixed-methods evaluation of THS between VHA hospitals to compare clinical outcomes and patient and staff satisfaction. Secondary outcomes included description of the implementation process, unexpected challenges, and subsequent QI initiatives. These results will expand the knowledge on feasibility of THS and provide implementation guidance.

A mixed-methods approach was used to evaluate outcomes of this QI project. Reporting follows the revised Standards for Quality Improvement Reporting Excellence (SQUIRE 2.0).²²

Context

The VHA is the largest integrated healthcare system in the United States, with more than 8 million veterans enrolled, more than 30% of whom reside in a rural area. The VHA comprises more than 1,000 outpatient clinics and 170 acute care VA Medical Centers,^23,24 including more than 35 rural and low-complexity hospitals.²⁵ Low-complexity hospitals are those with the lowest volume and levels of patient complexity and minimal or no teaching programs, research, intensive care unit (ICU) beds, and subspecialists. Lack of reimbursement and interstate licensing, often cited as barriers to telemedicine, do not apply to the VHA. The hub site was a large tertiary care (high-complexity) VHA hospital located in Iowa City, Iowa. The spoke site was a low-complexity (10-bed acute inpatient unit with no ICU) rural VA hospital located in Tomah, Wisconsin.

Study Population

The preimplementation cohort for comparison included all patients admitted between January 1, 2018, and January 6, 2019. The postimplementation study cohort included all observation and acute care admissions during the pilot phase (January 7 to May 3, 2019) and sustainability phase (July 15 to December 31, 2019). The postimplementation analysis excluded the time period of May 4 to July 14, 2019, due to an interruption (gap) in THS. The gap period allowed for preliminary data analysis, optimization of the telecommunication system, and the recruitment and training of additional providers who could provide long-term staffing to the service.

Intervention

Preimplementation

Prior to THS implementation, Tomah’s inpatient ward was staffed by one physician per shift, who could be a hospitalist, medical officer of the day (MOD), or an intermittent provider (locum tenens). Hospitalists covering the acute inpatient ward prior to the THS transitioned to cover weekends, nights, and urgent care service shifts.

We visited the spoke site and held information-sharing sessions with key stakeholders (administrators, clinician leaders, nurses, and ancillary staff) prior to kick-off. Recurrent phone meetings addressed anticipated and emerging challenges. Telehospitalist and local providers underwent technology and service training.

Technology and Connectivity

A low-cost technology system using tablet computers provided Health Insurance Portability and Accountability Act–compliant videoconferencing with a telehospitalist at the hub site. An Eko-Core digital stethoscope^® with a web-based audio stream was available. Telehospitalists conducted encounters from a private office space with telehealth capabilities. A total of $9,000 was spent on equipment at both sites. Due to connectivity problems and data limits, the tablets were switched to mobile computer-on-wheels workstations and hospital-based Wi-Fi for the sustainability phase.

THS Description

An experienced hub hospitalist, together with an advanced practice provider (APP; nurse practitioner [NP] or physician assistant [PA]), cared for all patients admitted to the 10-bed inpatient unit at the spoke site, Monday through Friday from 8:00 AM to 4:30 PM. The APP had limited or no prior experience in acute inpatient medicine. The telehospitalist worked as a team with the APP. The APP was the main point of contact for nurses, performed physical examinations, and directed patient care to their level of comfort (in a similar manner as a teaching team). The telehospitalist conducted bedside patient rounds, participated in multidisciplinary huddles, and shared clinical documentation and administrative duties with the APP. The telehospitalist was the primary staff for admitted patients and had full access to the electronic health record (EHR). The THS was staffed by 10 hospitalists during the study period. Overnight and weekend cross-coverage and admissions were performed by MODs, who also covered the urgent care and cross-covered other nonmedical units.

Quantitative Evaluation Methods

Workload and Clinical Outcomes

An EHR query identified all patients admitted during the pre- and postimplementation periods. Demographic data, clinical Nosos risk scores,^26,27 and top admission diagnoses were reported. Workload was evaluated using the average number of encounters per day and self-reported telehospitalist worksheets, which were cross-referenced with EHR data. Clinical outcomes included LOS, 30-day hospital readmission rate, 30-day standardized mortality (SMR30), in-hospital mortality, and VHA-specific inpatient quality metrics. Independent sample t tests for continuous variables and chi-square tests or Fisher’s exact test (for patient class) for categorical variables were used to compare pre- and postimplementation groups. Statistical process control (SPC) charts evaluated changes over time. All analyses were conducted using Microsoft Excel and R.²⁸

Provider Satisfaction

Anonymous surveys were distributed to spoke-site inpatient and administrative staff at 1 month and 12 months postimplementation, assessing satisfaction, technology/connectivity, communication, and challenges (Appendix Figure 1). Satisfaction of the telehospitalist physicians at the hub site was measured 12 months postimplementation by a 26-question survey assessing the same domains, plus quality of care (Appendix Figure 2).

Patient Satisfaction

The VHA Survey of Healthcare Experiences of Patients (SHEP), a version of the Hospital Consumer Assessment of Healthcare Providers and Systems Survey,^29,30 was mailed to all patients after discharge. Survey responses concerning inpatient provider care (eg, care coordination, communication, hospital rating, willingness to recommend the hospital) during the pre- and postimplementation phases were compared using a two-sample test of independent proportions. Responses obtained during May and June 2019 were excluded.

Qualitative Evaluation Methods

The qualitative researcher observed information-sharing meetings and facilitated unstructured interviews with clinical and administrative staff during site visits preimplementation and 3 months after implementation. Interviews with administrators and clinical staff addressed their experiences with the THS, staff’s perception of patient and family response to THS implementation, administrative impacts, challenges, and strengths. All interviews and meetings were documented with handwritten notes and audio recordings. Interview summary notes were typed into a Microsoft Word document, verified by the physician-investigator, and synthesized by inductive themes into site-visit reports. Audio recordings were uploaded to a secure computer, transcribed, and reviewed for accuracy. The qualitative researcher also identified emerging themes from open-ended survey responses. Process evaluation findings were shared with administration at the spoke site.

The authors had full access to, and took full responsibility for, the integrity of the data. The project was evaluated by the University of Iowa Institutional Review Board and the Iowa City VA Research and Development Committee and was determined to be a non–human-subjects QI project.

Quantitative Workload and Clinical Outcomes

There were 822 admissions during the preimplementation period and 550 admissions during the postimplementation period (253 during the pilot and 297 during sustainability phase). Patient characteristics pre- and postimplementation were not significantly different (Table 1). The median patient age was 65 years; 96% of patients were male, and 83% were rural residents. The most common admission diagnosis was alcohol-related (36%); regarding patient disposition, 78% of admissions were discharged home.

Workload

There were 502 patient encounters staffed by the telehospitalist in the pilot phase, with an average of 6.25 encounters per day, and a telehospitalist-reported workload of 7 hours per day. There were 538 patient encounters, with an average of 4.67 encounters per day and a workload of 5.6 hours per day in the sustainability phase. The average daily census decreased from 5.0 (SD, 1.1) patients per day during preimplementation to 3.1 (SD, 0.5) patients per day during postimplementation (Table 2). In some of the months during the study period, admissions decreased below the lower SPC limit, suggesting a significant change (Figure). Adjusted LOS was significantly lower, with 3.0 (SD, 0.7) days vs 2.3 (SD, 0.3) days in the pre- and postimplementation periods, respectively. Bed occupancy rates were significantly lower in the sustainability phase compared with the pilot phase and the preimplementation period. Readmission rates varied, ranging from <10% to >30%, not significantly different but slightly higher in the postimplementation period. Readmission rates for heart failure, chronic obstructive pulmonary disease, and pneumonia remained unchanged; other medical readmissions (mostly alcohol-related) were slightly higher in the postimplementation period.

In-hospital mortality and SMR30 did not change significantly, but there was improvement in the 12-month rolling average of the observed/expected SMR30 from 1.40 to 1.08. Additional VHA-specific quality metrics were monitored and showed either small improvements or no change (data not shown).

Satisfaction at Hub and Spoke Sites

After sending two reminder communications via email, the telehospitalist satisfaction survey had a total response rate of 90% (9/10). Telehospitalists were satisfied or very satisfied (89%) with the program and the local providers (88.9%), rating their experience as good or excellent (100%) (Table 3). Communication with patients, families, and local staff was noted as being “positive” or “mostly positive.” Telehospitalists reported confidence in the accuracy of their diagnoses and rated the quality of care as being equal to that of a face-to-face encounter. Connectivity problems were prevalent, although most providers were able to resort to a back-up plan. Other challenges included differences in culture and concerns about liability. We received 27 responses from the spoke-site satisfaction survey; the response rate could not be determined because the survey was distributed by the spoke site for anonymity. Of the respondents, 37% identified as nurses, 25.9% as healthcare providers (APPs or physicians), and 33.3% as other staff (eg, social worker, nutritionist, physical therapist, utilization management, administrators); 3.7% did not respond. Among the participants, 88% had personally interacted with the THS. Most providers and other staff perceived THS as valuable (57.1% and 77.8%, respectively) and were satisfied or highly satisfied with THS (57.1% and 55.6%, respectively). On average, nurses provided lower ratings across all survey items than providers and other staff. Challenges noted by all staff included issues with communication, workflow, and technology/connectivity.

Regarding patient satisfaction, the SHEP survey showed a significant improvement in care coordination (18%; P = .02) and a nonsignificant improvement in communications about medications (5%; P =.054). The remaining items in the survey, including overall hospital rating and willingness to recommend the hospital, were unchanged (Appendix Table).

Qualitative Strengths

Our process evaluation identified high quality of care and teamwork as contributors to the success of the program. Overall, staff credited perceived improvements in quality of care to the quality of providers staffing the THS, including the local APPs. Noting the telehospitalists’ knowledge base and level of engagement as key attributes, one staff member commented: “I prefer a telehospitalist that really care[s] about patients than some provider that is physically here but does not engage.” Staff perceived improvements in the continuity of care, as well as care processes such as handoffs and transitions of care.

Improvements in teamwork were perceived compared with the previous model of care. Telehospitalists were lauded for their professionalism and communication skills. Overall, nurses felt providers in the THS listened more to their views. In addition, nurse respondents felt they could learn from several providers and said they enjoyed the telehospitalists’ disposition to teach and discuss patient care. The responsiveness of the THS staff was instrumental in building teamwork and acceptance. A bedside interdisciplinary protocol was established for appropriate patients. Local staff felt this was crucial for teamwork and patient satisfaction. Telehospitalists reported high-value in interdisciplinary rounds, facilitating interaction with nurses and ancillary staff. Handoff problems were identified, leading to QI initiatives to mitigate those issues.

Challenges

The survey identified administrative barriers, technical difficulties, workflow constraints, and clinical concerns. The credentialing process was complicated, delaying the onboarding of telehospitalists. Internet connectivity was inconsistent, leading to disruption in video communications; however, during the sustainability phase, updated technology improved communications. The communication workflow was resisted by some nurses, who wanted to phone the telehospitalist directly rather than having the local APP as the first contact. Secure messaging was enabled to allow nurses direct contact during the sustainability phase.

Workload was a concern among telehospitalists and local staff. Telehospitalists perceived the documentation requirements and administrative workload to be two to three times higher than at other hospitals—despite the lower number of encounters. Finally, clinical concerns from spoke-site clinicians included a perceived rise in the acuity of patients (which was not evident by the Nosos score) and delayed decisions to transfer-out patients. These concerns were addressed with educational sessions for telehospitalists during the sustainability phase.

Additional Quality Improvement Projects

The implementation of THS resulted in QI initiatives at the spoke site, including an EHR-integrated handoff tool; a documentation evaluation that led to the elimination of duplicative, inefficient, and error-prone templates; and a revision of the alcohol withdrawal treatment protocol during the sustainability phase to reduce the use of intravenous benzodiazepines. A more comprehensive benzodiazepine-sparing alcohol withdrawal treatment protocol was also developed but was not implemented until after the study period (January 2020).

Our pre-post study evaluation found implementation of a THS to be noninferior to face-to-face care, with no significant change in mortality, readmission rate, or patient satisfaction. The significant improvement observed in LOS is consistent with the adoption of hospitalist models in other medical care settings,¹¹ but had not been reported by previous telehospitalist studies. For example, in their retrospective chart review comparing an NP-supported telehospitalist model to locum tenens hospitalists, Boltz et al found no difference in LOS.³¹ Moreover, as in our study, they found no differences in readmissions, mortality, and patient satisfaction.³¹ Similarly, Kuperman et al reported unchanged daily census, LOS, and transfer rates from a CAH with their virtual hospitalist program, but a decrease in the percentage of patients transferred-out from the emergency department, suggesting that more patients were treated locally.¹⁹

Reduction in LOS is one of the primary measures of efficiency in hospital care³¹; reducing LOS while maintaining the quality of care lowers hospital costs. The reduction in LOS in our study could be attributed to greater continuity of care, engagement/experience of the telehospitalists, or other factors. This decrease in LOS and slight reduction in admissions resulted in an overall lower daily census during the study period and impacted efficiency. Our study was unable to determine the cause for the reduction in admissions; however, several concurrent events, including the expansion of community-care options for veterans under the MISSION ACT (Maintaining Internal Systems and Strengthening Integrated Outside Networks Act) in June 2019, a nationwide smoking ban at VA facilities (October 2019), and a modification in the alcohol withdrawal treatment protocol might have influenced veterans’ choice of hospital.

Readmission rates were slightly higher, though nonsignificant, in the postimplementation period. Alcohol-related readmissions accounted for most readmissions; some of the protocol changes, such as admitting all patients with alcohol withdrawal to inpatient class instead of admitting some to the observation class, accounted for part of the increase in readmission rates. Readmission rates for other conditions such as chronic obstructive pulmonary disease, chronic heart failure, or pneumonia were not significantly different, suggesting that the reduction in LOS did not result in an unintended increased readmission rate for those conditions.

Rural hospitals are struggling with staffing and finances. Resorting to locum tenens staffing is costly and can result in variable quality of care.^32,33 APPs are increasingly taking on hospitalist positions, with 65% of adult hospitalist programs, including half of all VHA hospitals, employing NPs and PAs.^34,35 In response to this expanded scope of practice, hospitals employing APPs in hospitalist roles must comply with state and federal laws, which often require that APPs be supervised by or work in collaboration with an on-site or off-site physician. The THS is a great model to support APPs and address staffing and cost challenges in low-volume rural facilities, while maintaining quality of care. Some APP-telehospitalist programs similar to ours have reported cost reductions of up 58% compared to programs that employ locum tenens physicians.³¹ In our model, we assume that a single telehospitalist hub could provide coverage to two or three spoke sites with APP support, reducing staffing costs.

Hub telehospitalists reported satisfaction with the program, and they perceived the quality of care to be comparable to face-to-face encounters; their responses were consistent with those previously reported in an evaluation of telemedicine acute care by JaKa et al.²⁰ Spoke-site staff, however, had a mixed level of satisfaction, which was different from responses reported by JaKa et al.²⁰ The primary challenges encountered were technological and communication issues, differences in cultures of care between the hub and the spoke sites, and buy-in from frontline staff. Differences in expectations and unclear role definitions between the local APP and the telehospitalist were identified as contributors to dissatisfaction with the program by the nursing staff. Modifications to the communication processes between nurses and telehospitalists and role clarification improved the experience. Culture and practice differences between spoke physicians and the telehospitalist persisted throughout the program implementation, and likely affected the hub providers’ perception of the THS. This was evidenced by reluctance from spoke physicians to implement warm handoffs or participate in THS meetings and resistance to protocol changes. Additional evaluations, collaborations. and interventions are required to improve satisfaction of spoke-site staff.

This study has several limitations. First, the VHA is an integrated health system, one that serves an older, predominantly male patient population. Also, the lack of reimbursement and interstate licensing restrictions limit generalizability of these results to other CAHs or healthcare systems. Furthermore, the intervention was limited to a single rural site; while this allowed for a detailed evaluation, unique barriers or facilitators might exist that limit its applicability. In addition, QI initiatives implemented by the VHA during the project period might have confounded some of our results. Last, patient satisfaction survey data are overall limited in their ability to fully assess patient’s experience and satisfaction with the program. Further qualitative studies are needed to gain deeper insight into patient perspectives with the THS and whether modality of care delivery influences patients’ care decisions. Future studies should consider a multisite design with one or more hubs and multiple spoke sites.

Telehospitalist services are a feasible and safe approach to provide inpatient services and address staffing needs of rural hospitals. To enhance program performance, it is essential to ensure adequate technological quality, clearly delineate and define roles and responsibilities of the care team, and address communication issues or staff concerns in a timely manner.

The authors thank the staff, administration, and leadership at the Tomah and Iowa City VA Medical Centers for working with us on this project. They offer special thanks to Kevin Glenn, MD, MS, Ethan Kuperman, MD, MS, FHM, and Jennifer Chapin, MSN, RN, for sharing their expertise, and the telehealth team, including Nathaniel Samuelson, Angela McDowell, and Katrin Metcalf.

The views expressed in this article are those of the authors and do not necessarily represent the views of the Department of Veterans Affairs.

Venous thromboembolism (VTE) is a life-threatening event occurring with increasing frequency in hospitalized children and an incidence of more than 58 events per 10,000 hospitalizations.¹ In pediatric patients, VTEs occur less often than in adults, have bimodal peaks in neonates and adolescents, and are typically provoked, with central venous access as the most common risk factor.^1,

Treatment of pediatric VTE includes unfractionated heparin (UFH), low-molecular-weight heparin (LMWH), and vitamin K antagonists (ie, warfarin). These agents have limitations, including parenteral administration, frequent lab monitoring, and drug/dietary interactions complicating use. Only recently have there been pediatric studies to assess these agents’ pharmacokinetics, pharmacodynamics, safety, and efficacy.²

Direct oral anticoagulants (DOACs) commonly used to treat VTE in adults have two mechanisms of action: direct thrombin (activated factor II) inhibition (ie, dabigatran) and activated factor X (Xa) inhibition (ie, rivaroxaban, apixaban, edoxaban, betrixaban). DOACs offer practical advantages over and efficacy similar to that of warfarin and heparin products, including oral administration, predictable pharmacology, no required lab monitoring, and fewer drug/dietary interactions. DOACs are already approved for VTE treatment in patients 18 years and older.³

This clinical practice update synthesizes 6 years (2014-2020) of literature regarding DOACs for treatment of VTE, focusing on their current role in patients 18 years and older and their emerging role in pediatric patients.

DOACs are approved by the US Food and Drug Administration (FDA) for multiple anticoagulation indications in adults, including treatment and prevention of acute VTE and prevention of stroke in nonvalvular atrial fibrillation (Table). DOACs are well tolerated by most adults; however, use in certain populations, including patients with liver disease with coagulopathy, advanced renal disease (creatinine clearance <30 mL/min), and class III obesity (body mass index [BMI] >40 kg/m²), requires caution.^4,5 For adult patients with VTE without contraindications, DOACs are considered equivalent to warfarin; current CHEST guidelines even suggest preference of DOACs over warfarin.⁵ While it is prudent to exercise caution when extrapolating adult data to children, these data have informed ongoing pediatric DOAC clinical trials.

The efficacy and safety of each of the DOACs (aside from betrixaban, which is indicated only for prophylaxis) have compared with warfarin for treatment of VTE in adults.⁶ A meta-analysis of six clinical trials determined DOACs are noninferior to warfarin for VTE treatment.³ Only two of six trials included patients with provoked VTEs. The meta-analysis found no difference in rates of recurrent symptomatic VTE (primary outcome; relative risk [RR], 0.91; 95% CI, 0.79-1.06) or all-cause mortality (secondary outcome; RR, 0.98; 95% CI, 0.84-1.14). Additionally, DOACs were shown as possibly safer than warfarin due to fewer major bleeding events, particularly fatal bleeding (RR, 0.36; 95% CI, 0.15-0.84) and intracranial bleeding (RR, 0.34; 95% CI, 0.17-0.69). For clinically relevant nonmajor bleeding (eg, gastrointestinal bleeding requiring <2 U packed red blood cells), results were similar (RR, 0.73; 95% CI, 0.58-0.93).

DOACs appear to have effectiveness comparable with that of warfarin. A retrospective matched cohort study of 59,525 patients with acute VTE compared outcomes of patients on DOACs (95% on rivaroxaban) with those of patients on warfarin.⁶ There were no differences in all-cause mortality or major bleeding. Another retrospective cohort study of 62,431 patients with acute VTE compared rivaroxaban and apixaban with warfarin, as well as rivaroxaban and apixaban with each other.⁷ There were no differences in 3- and 6-month mortality between warfarin and DOAC users or between rivaroxaban and apixaban users.

Initial approval of DOACs brought concerns about reversibility in the setting of bleeding or urgent procedural need. Clinical practice guidelines, primarily based on observational studies and laboratory parameters in vitro or in healthy volunteers, recommend activated prothrombin complex concentrates as a first-line intervention.⁸ However, specific agents have now been FDA-approved for DOAC reversal.

Idarucizumab is an FDA-approved (2015) monoclonal antibody with high affinity for dabigatran. Approval was based on a multicenter prospective cohort study of 503 patients taking dabigatran who presented with major bleeding (301 patients) or requiring an urgent surgery (202 patients).⁹ Idarucizumab resulted in a median time to bleeding cessation of 2.5 hours for those 134 patients in whom time to bleeding cessation could be assessed. Patients with intracranial bleeding were excluded from the timed portion because follow up imaging was not mandated. For those requiring surgery, 93% had normal periprocedural hemostasis.

Andexanet alfa is an FDA-approved (2018) drug for reversal of apixaban and rivaroxaban that acts as a catalytically inactive decoy Xa molecule, binding Xa inhibitors with high affinity. A multicenter prospective cohort study of 352 patients on Xa inhibitors with major bleeding found administration of andexanet alfa resulted in excellent or good hemostasis in 82% of patients (204/249 patients) at 12 hours.¹⁰ There was no difference between rivaroxaban and apixaban patients. Both idarucizumab and andexanet alfa remain expensive and not universally available, but availability and use will likely increase with time.

In pediatric patients, most VTEs are provoked, with the most common risk factor being presence of a central line. Frequency of this risk factor varies based on age (>60% of cases in older children and nearly 90% in neonates).¹ The most recent American Society of Hematology guidelines recommend treating pediatric symptomatic VTE with anticoagulation and treating asymptomatic VTE instead of observation.² These recommendations rely on evidence in adult patients due to the current paucity of evidence in pediatrics.

“Pediatric investigation plans” are the cornerstone for ongoing clinical trials of DOACs in pediatrics. While studies evaluating safety and efficacy of standard anticoagulants (UFH, LMWH, and warfarin) in pediatrics exist, clinical trials at the time of drug development did not include pediatric patients. This means none of the currently used anticoagulants were initially developed or approved for children.¹ Under the Pediatric Research Equity Act of 2007, the FDA requires pharmaceutical companies to submit a New Drug Application to perform pediatric studies of drugs deemed likely for use in pediatric patients. Pediatric investigation plans allow for establishing safety, efficacy, dosing, and administration routes in pediatric populations. All four DOACs currently approved for treatment of VTE in adults have ongoing efficacy and safety clinical trials for children.

The first and only published clinical trial of DOAC efficacy and safety in pediatrics compared rivaroxaban to standard treatment of acute VTE (Appendix Table).¹¹ The industry-sponsored, open-label EINSTEIN-Jr trial randomized patients aged 0 to 17 years 2:1 to weight-based rivaroxaban or standard treatment after receiving initial parenteral therapy for 5 to 9 days. While most patients were treated for at least 3 months, patients younger than 2 years with line-related thrombosis were treated for only 1 month. The study population mostly consisted of patients with initial, symptomatic, provoked VTE, with types ranging from cerebral venous sinus thrombosis to catheter-associated thrombosis. VTE risk factors, which varied by age, included presence of a central line, major infection, surgery, or trauma. While most VTEs in pediatric patients are expected to be central-line related, in the EINSTEIN-Jr trial only 25.2% of VTEs were central line–associated. The study evaluated symptomatic recurrent VTE (primary efficacy outcome) and clinically relevant bleeding (safety outcome). No significant difference was found between treatment groups in efficacy or safety outcomes, and there were no treatment-related deaths. While the trial was not powered to assess noninferiority due to low incidence of VTE in pediatrics, the absolute number of symptomatic recurrent VTEs was lower in the rivaroxaban group compared with the standard-care group (1% vs 3%). The investigators concluded that rivaroxaban is similarly efficacious and safe in children as compared with adults. FDA approval of rivaroxaban in pediatrics is expected given the trial’s favorable results. Clinicians may wish to consider whether the studied population is comparable with their own patients because the trial had a lower percentage of line-associated VTE than previously reported in the pediatric population.

Multiple clinical trials evaluating the efficacy and safety of other DOACs in pediatric patients are currently underway (Appendix Table).^12-14 Apixaban and edoxaban have active multicenter, randomized, open-label clinical trials recruiting patients up to age 17 who have imaging-confirmed acute VTE. A similar trial for dabigatran has recently completed recruitment. Outcome measures include recurrent VTE, VTE-related mortality, and major or clinically relevant non-major bleeding. Like EINSTEIN-Jr, patients in the dabigatran and edoxaban trials were treated with parenteral therapy for at least 5 days prior to randomization.^12,14 In the apixaban trial, participants can be randomized without initial parenteral treatment.¹³ Betrixaban, the newest DOAC approved in adults, does not currently have any open pediatric trials.

Lack of approved reversal agents may initially limit DOAC use in children. An open-label study examining idarucizumab safety has completed enrollment, but it has not yet published results.¹⁵ To date, there are no pediatric clinical trials examining andexanet alpha. Future work will need to establish efficacy and safety of reversal agents in pediatrics.

DOACs have not been adequately studied in populations of patients with comorbidities, such as liver disease, renal disease, altered enteral absorption, and BMI higher than 40. Physiologic differences in children with cancer and in neonates merit further evaluation of DOAC safety and efficacy. While ongoing trials established weight-based dosing regimens for children, longitudinal studies will need to ensure adequate anticoagulation, especially in the populations listed here.

The safety outcomes in most DOAC studies include clinically relevant bleeding and VTE-related mortality. These outcomes are much less common in pediatric patients than they are in adults, and future studies may need to expand safety outcomes to those more frequently seen in children. Primary and secondary endpoint variability in pediatric DOAC clinical trials presents challenges interpreting and comparing study results.

VTE is an increasingly common complication in hospitalized children contributing to significant morbidity.¹ For decades, the only treatment options have been UFH, LMWH, or warfarin. DOACs offer many advantages compared with standard anticoagulation options. The only clinical trial evaluating efficacy and safety of DOACs published to date demonstrates that pediatric patients taking rivaroxaban have outcomes similar to those of patients receiving standard care. It is expected that DOACs will gain FDA approval for treatment of VTE in pediatric patients in the near future; therefore, hospitalists should understand indications for use of these medications.

Venous thromboembolism (VTE) is a life-threatening event occurring with increasing frequency in hospitalized children and an incidence of more than 58 events per 10,000 hospitalizations.¹ In pediatric patients, VTEs occur less often than in adults, have bimodal peaks in neonates and adolescents, and are typically provoked, with central venous access as the most common risk factor.^1,

Treatment of pediatric VTE includes unfractionated heparin (UFH), low-molecular-weight heparin (LMWH), and vitamin K antagonists (ie, warfarin). These agents have limitations, including parenteral administration, frequent lab monitoring, and drug/dietary interactions complicating use. Only recently have there been pediatric studies to assess these agents’ pharmacokinetics, pharmacodynamics, safety, and efficacy.²

Direct oral anticoagulants (DOACs) commonly used to treat VTE in adults have two mechanisms of action: direct thrombin (activated factor II) inhibition (ie, dabigatran) and activated factor X (Xa) inhibition (ie, rivaroxaban, apixaban, edoxaban, betrixaban). DOACs offer practical advantages over and efficacy similar to that of warfarin and heparin products, including oral administration, predictable pharmacology, no required lab monitoring, and fewer drug/dietary interactions. DOACs are already approved for VTE treatment in patients 18 years and older.³

This clinical practice update synthesizes 6 years (2014-2020) of literature regarding DOACs for treatment of VTE, focusing on their current role in patients 18 years and older and their emerging role in pediatric patients.

DOACs are approved by the US Food and Drug Administration (FDA) for multiple anticoagulation indications in adults, including treatment and prevention of acute VTE and prevention of stroke in nonvalvular atrial fibrillation (Table). DOACs are well tolerated by most adults; however, use in certain populations, including patients with liver disease with coagulopathy, advanced renal disease (creatinine clearance <30 mL/min), and class III obesity (body mass index [BMI] >40 kg/m²), requires caution.^4,5 For adult patients with VTE without contraindications, DOACs are considered equivalent to warfarin; current CHEST guidelines even suggest preference of DOACs over warfarin.⁵ While it is prudent to exercise caution when extrapolating adult data to children, these data have informed ongoing pediatric DOAC clinical trials.

The efficacy and safety of each of the DOACs (aside from betrixaban, which is indicated only for prophylaxis) have compared with warfarin for treatment of VTE in adults.⁶ A meta-analysis of six clinical trials determined DOACs are noninferior to warfarin for VTE treatment.³ Only two of six trials included patients with provoked VTEs. The meta-analysis found no difference in rates of recurrent symptomatic VTE (primary outcome; relative risk [RR], 0.91; 95% CI, 0.79-1.06) or all-cause mortality (secondary outcome; RR, 0.98; 95% CI, 0.84-1.14). Additionally, DOACs were shown as possibly safer than warfarin due to fewer major bleeding events, particularly fatal bleeding (RR, 0.36; 95% CI, 0.15-0.84) and intracranial bleeding (RR, 0.34; 95% CI, 0.17-0.69). For clinically relevant nonmajor bleeding (eg, gastrointestinal bleeding requiring <2 U packed red blood cells), results were similar (RR, 0.73; 95% CI, 0.58-0.93).

DOACs appear to have effectiveness comparable with that of warfarin. A retrospective matched cohort study of 59,525 patients with acute VTE compared outcomes of patients on DOACs (95% on rivaroxaban) with those of patients on warfarin.⁶ There were no differences in all-cause mortality or major bleeding. Another retrospective cohort study of 62,431 patients with acute VTE compared rivaroxaban and apixaban with warfarin, as well as rivaroxaban and apixaban with each other.⁷ There were no differences in 3- and 6-month mortality between warfarin and DOAC users or between rivaroxaban and apixaban users.

Initial approval of DOACs brought concerns about reversibility in the setting of bleeding or urgent procedural need. Clinical practice guidelines, primarily based on observational studies and laboratory parameters in vitro or in healthy volunteers, recommend activated prothrombin complex concentrates as a first-line intervention.⁸ However, specific agents have now been FDA-approved for DOAC reversal.

Idarucizumab is an FDA-approved (2015) monoclonal antibody with high affinity for dabigatran. Approval was based on a multicenter prospective cohort study of 503 patients taking dabigatran who presented with major bleeding (301 patients) or requiring an urgent surgery (202 patients).⁹ Idarucizumab resulted in a median time to bleeding cessation of 2.5 hours for those 134 patients in whom time to bleeding cessation could be assessed. Patients with intracranial bleeding were excluded from the timed portion because follow up imaging was not mandated. For those requiring surgery, 93% had normal periprocedural hemostasis.

Andexanet alfa is an FDA-approved (2018) drug for reversal of apixaban and rivaroxaban that acts as a catalytically inactive decoy Xa molecule, binding Xa inhibitors with high affinity. A multicenter prospective cohort study of 352 patients on Xa inhibitors with major bleeding found administration of andexanet alfa resulted in excellent or good hemostasis in 82% of patients (204/249 patients) at 12 hours.¹⁰ There was no difference between rivaroxaban and apixaban patients. Both idarucizumab and andexanet alfa remain expensive and not universally available, but availability and use will likely increase with time.

In pediatric patients, most VTEs are provoked, with the most common risk factor being presence of a central line. Frequency of this risk factor varies based on age (>60% of cases in older children and nearly 90% in neonates).¹ The most recent American Society of Hematology guidelines recommend treating pediatric symptomatic VTE with anticoagulation and treating asymptomatic VTE instead of observation.² These recommendations rely on evidence in adult patients due to the current paucity of evidence in pediatrics.

“Pediatric investigation plans” are the cornerstone for ongoing clinical trials of DOACs in pediatrics. While studies evaluating safety and efficacy of standard anticoagulants (UFH, LMWH, and warfarin) in pediatrics exist, clinical trials at the time of drug development did not include pediatric patients. This means none of the currently used anticoagulants were initially developed or approved for children.¹ Under the Pediatric Research Equity Act of 2007, the FDA requires pharmaceutical companies to submit a New Drug Application to perform pediatric studies of drugs deemed likely for use in pediatric patients. Pediatric investigation plans allow for establishing safety, efficacy, dosing, and administration routes in pediatric populations. All four DOACs currently approved for treatment of VTE in adults have ongoing efficacy and safety clinical trials for children.

The first and only published clinical trial of DOAC efficacy and safety in pediatrics compared rivaroxaban to standard treatment of acute VTE (Appendix Table).¹¹ The industry-sponsored, open-label EINSTEIN-Jr trial randomized patients aged 0 to 17 years 2:1 to weight-based rivaroxaban or standard treatment after receiving initial parenteral therapy for 5 to 9 days. While most patients were treated for at least 3 months, patients younger than 2 years with line-related thrombosis were treated for only 1 month. The study population mostly consisted of patients with initial, symptomatic, provoked VTE, with types ranging from cerebral venous sinus thrombosis to catheter-associated thrombosis. VTE risk factors, which varied by age, included presence of a central line, major infection, surgery, or trauma. While most VTEs in pediatric patients are expected to be central-line related, in the EINSTEIN-Jr trial only 25.2% of VTEs were central line–associated. The study evaluated symptomatic recurrent VTE (primary efficacy outcome) and clinically relevant bleeding (safety outcome). No significant difference was found between treatment groups in efficacy or safety outcomes, and there were no treatment-related deaths. While the trial was not powered to assess noninferiority due to low incidence of VTE in pediatrics, the absolute number of symptomatic recurrent VTEs was lower in the rivaroxaban group compared with the standard-care group (1% vs 3%). The investigators concluded that rivaroxaban is similarly efficacious and safe in children as compared with adults. FDA approval of rivaroxaban in pediatrics is expected given the trial’s favorable results. Clinicians may wish to consider whether the studied population is comparable with their own patients because the trial had a lower percentage of line-associated VTE than previously reported in the pediatric population.

Multiple clinical trials evaluating the efficacy and safety of other DOACs in pediatric patients are currently underway (Appendix Table).^12-14 Apixaban and edoxaban have active multicenter, randomized, open-label clinical trials recruiting patients up to age 17 who have imaging-confirmed acute VTE. A similar trial for dabigatran has recently completed recruitment. Outcome measures include recurrent VTE, VTE-related mortality, and major or clinically relevant non-major bleeding. Like EINSTEIN-Jr, patients in the dabigatran and edoxaban trials were treated with parenteral therapy for at least 5 days prior to randomization.^12,14 In the apixaban trial, participants can be randomized without initial parenteral treatment.¹³ Betrixaban, the newest DOAC approved in adults, does not currently have any open pediatric trials.

Lack of approved reversal agents may initially limit DOAC use in children. An open-label study examining idarucizumab safety has completed enrollment, but it has not yet published results.¹⁵ To date, there are no pediatric clinical trials examining andexanet alpha. Future work will need to establish efficacy and safety of reversal agents in pediatrics.

DOACs have not been adequately studied in populations of patients with comorbidities, such as liver disease, renal disease, altered enteral absorption, and BMI higher than 40. Physiologic differences in children with cancer and in neonates merit further evaluation of DOAC safety and efficacy. While ongoing trials established weight-based dosing regimens for children, longitudinal studies will need to ensure adequate anticoagulation, especially in the populations listed here.

The safety outcomes in most DOAC studies include clinically relevant bleeding and VTE-related mortality. These outcomes are much less common in pediatric patients than they are in adults, and future studies may need to expand safety outcomes to those more frequently seen in children. Primary and secondary endpoint variability in pediatric DOAC clinical trials presents challenges interpreting and comparing study results.

VTE is an increasingly common complication in hospitalized children contributing to significant morbidity.¹ For decades, the only treatment options have been UFH, LMWH, or warfarin. DOACs offer many advantages compared with standard anticoagulation options. The only clinical trial evaluating efficacy and safety of DOACs published to date demonstrates that pediatric patients taking rivaroxaban have outcomes similar to those of patients receiving standard care. It is expected that DOACs will gain FDA approval for treatment of VTE in pediatric patients in the near future; therefore, hospitalists should understand indications for use of these medications.

Venous thromboembolism (VTE) is a life-threatening event occurring with increasing frequency in hospitalized children and an incidence of more than 58 events per 10,000 hospitalizations.¹ In pediatric patients, VTEs occur less often than in adults, have bimodal peaks in neonates and adolescents, and are typically provoked, with central venous access as the most common risk factor.^1,

Treatment of pediatric VTE includes unfractionated heparin (UFH), low-molecular-weight heparin (LMWH), and vitamin K antagonists (ie, warfarin). These agents have limitations, including parenteral administration, frequent lab monitoring, and drug/dietary interactions complicating use. Only recently have there been pediatric studies to assess these agents’ pharmacokinetics, pharmacodynamics, safety, and efficacy.²

Direct oral anticoagulants (DOACs) commonly used to treat VTE in adults have two mechanisms of action: direct thrombin (activated factor II) inhibition (ie, dabigatran) and activated factor X (Xa) inhibition (ie, rivaroxaban, apixaban, edoxaban, betrixaban). DOACs offer practical advantages over and efficacy similar to that of warfarin and heparin products, including oral administration, predictable pharmacology, no required lab monitoring, and fewer drug/dietary interactions. DOACs are already approved for VTE treatment in patients 18 years and older.³

This clinical practice update synthesizes 6 years (2014-2020) of literature regarding DOACs for treatment of VTE, focusing on their current role in patients 18 years and older and their emerging role in pediatric patients.

DOACs are approved by the US Food and Drug Administration (FDA) for multiple anticoagulation indications in adults, including treatment and prevention of acute VTE and prevention of stroke in nonvalvular atrial fibrillation (Table). DOACs are well tolerated by most adults; however, use in certain populations, including patients with liver disease with coagulopathy, advanced renal disease (creatinine clearance <30 mL/min), and class III obesity (body mass index [BMI] >40 kg/m²), requires caution.^4,5 For adult patients with VTE without contraindications, DOACs are considered equivalent to warfarin; current CHEST guidelines even suggest preference of DOACs over warfarin.⁵ While it is prudent to exercise caution when extrapolating adult data to children, these data have informed ongoing pediatric DOAC clinical trials.

The efficacy and safety of each of the DOACs (aside from betrixaban, which is indicated only for prophylaxis) have compared with warfarin for treatment of VTE in adults.⁶ A meta-analysis of six clinical trials determined DOACs are noninferior to warfarin for VTE treatment.³ Only two of six trials included patients with provoked VTEs. The meta-analysis found no difference in rates of recurrent symptomatic VTE (primary outcome; relative risk [RR], 0.91; 95% CI, 0.79-1.06) or all-cause mortality (secondary outcome; RR, 0.98; 95% CI, 0.84-1.14). Additionally, DOACs were shown as possibly safer than warfarin due to fewer major bleeding events, particularly fatal bleeding (RR, 0.36; 95% CI, 0.15-0.84) and intracranial bleeding (RR, 0.34; 95% CI, 0.17-0.69). For clinically relevant nonmajor bleeding (eg, gastrointestinal bleeding requiring <2 U packed red blood cells), results were similar (RR, 0.73; 95% CI, 0.58-0.93).

DOACs appear to have effectiveness comparable with that of warfarin. A retrospective matched cohort study of 59,525 patients with acute VTE compared outcomes of patients on DOACs (95% on rivaroxaban) with those of patients on warfarin.⁶ There were no differences in all-cause mortality or major bleeding. Another retrospective cohort study of 62,431 patients with acute VTE compared rivaroxaban and apixaban with warfarin, as well as rivaroxaban and apixaban with each other.⁷ There were no differences in 3- and 6-month mortality between warfarin and DOAC users or between rivaroxaban and apixaban users.

Initial approval of DOACs brought concerns about reversibility in the setting of bleeding or urgent procedural need. Clinical practice guidelines, primarily based on observational studies and laboratory parameters in vitro or in healthy volunteers, recommend activated prothrombin complex concentrates as a first-line intervention.⁸ However, specific agents have now been FDA-approved for DOAC reversal.

Idarucizumab is an FDA-approved (2015) monoclonal antibody with high affinity for dabigatran. Approval was based on a multicenter prospective cohort study of 503 patients taking dabigatran who presented with major bleeding (301 patients) or requiring an urgent surgery (202 patients).⁹ Idarucizumab resulted in a median time to bleeding cessation of 2.5 hours for those 134 patients in whom time to bleeding cessation could be assessed. Patients with intracranial bleeding were excluded from the timed portion because follow up imaging was not mandated. For those requiring surgery, 93% had normal periprocedural hemostasis.

Andexanet alfa is an FDA-approved (2018) drug for reversal of apixaban and rivaroxaban that acts as a catalytically inactive decoy Xa molecule, binding Xa inhibitors with high affinity. A multicenter prospective cohort study of 352 patients on Xa inhibitors with major bleeding found administration of andexanet alfa resulted in excellent or good hemostasis in 82% of patients (204/249 patients) at 12 hours.¹⁰ There was no difference between rivaroxaban and apixaban patients. Both idarucizumab and andexanet alfa remain expensive and not universally available, but availability and use will likely increase with time.

In pediatric patients, most VTEs are provoked, with the most common risk factor being presence of a central line. Frequency of this risk factor varies based on age (>60% of cases in older children and nearly 90% in neonates).¹ The most recent American Society of Hematology guidelines recommend treating pediatric symptomatic VTE with anticoagulation and treating asymptomatic VTE instead of observation.² These recommendations rely on evidence in adult patients due to the current paucity of evidence in pediatrics.

“Pediatric investigation plans” are the cornerstone for ongoing clinical trials of DOACs in pediatrics. While studies evaluating safety and efficacy of standard anticoagulants (UFH, LMWH, and warfarin) in pediatrics exist, clinical trials at the time of drug development did not include pediatric patients. This means none of the currently used anticoagulants were initially developed or approved for children.¹ Under the Pediatric Research Equity Act of 2007, the FDA requires pharmaceutical companies to submit a New Drug Application to perform pediatric studies of drugs deemed likely for use in pediatric patients. Pediatric investigation plans allow for establishing safety, efficacy, dosing, and administration routes in pediatric populations. All four DOACs currently approved for treatment of VTE in adults have ongoing efficacy and safety clinical trials for children.

The first and only published clinical trial of DOAC efficacy and safety in pediatrics compared rivaroxaban to standard treatment of acute VTE (Appendix Table).¹¹ The industry-sponsored, open-label EINSTEIN-Jr trial randomized patients aged 0 to 17 years 2:1 to weight-based rivaroxaban or standard treatment after receiving initial parenteral therapy for 5 to 9 days. While most patients were treated for at least 3 months, patients younger than 2 years with line-related thrombosis were treated for only 1 month. The study population mostly consisted of patients with initial, symptomatic, provoked VTE, with types ranging from cerebral venous sinus thrombosis to catheter-associated thrombosis. VTE risk factors, which varied by age, included presence of a central line, major infection, surgery, or trauma. While most VTEs in pediatric patients are expected to be central-line related, in the EINSTEIN-Jr trial only 25.2% of VTEs were central line–associated. The study evaluated symptomatic recurrent VTE (primary efficacy outcome) and clinically relevant bleeding (safety outcome). No significant difference was found between treatment groups in efficacy or safety outcomes, and there were no treatment-related deaths. While the trial was not powered to assess noninferiority due to low incidence of VTE in pediatrics, the absolute number of symptomatic recurrent VTEs was lower in the rivaroxaban group compared with the standard-care group (1% vs 3%). The investigators concluded that rivaroxaban is similarly efficacious and safe in children as compared with adults. FDA approval of rivaroxaban in pediatrics is expected given the trial’s favorable results. Clinicians may wish to consider whether the studied population is comparable with their own patients because the trial had a lower percentage of line-associated VTE than previously reported in the pediatric population.

Multiple clinical trials evaluating the efficacy and safety of other DOACs in pediatric patients are currently underway (Appendix Table).^12-14 Apixaban and edoxaban have active multicenter, randomized, open-label clinical trials recruiting patients up to age 17 who have imaging-confirmed acute VTE. A similar trial for dabigatran has recently completed recruitment. Outcome measures include recurrent VTE, VTE-related mortality, and major or clinically relevant non-major bleeding. Like EINSTEIN-Jr, patients in the dabigatran and edoxaban trials were treated with parenteral therapy for at least 5 days prior to randomization.^12,14 In the apixaban trial, participants can be randomized without initial parenteral treatment.¹³ Betrixaban, the newest DOAC approved in adults, does not currently have any open pediatric trials.

Lack of approved reversal agents may initially limit DOAC use in children. An open-label study examining idarucizumab safety has completed enrollment, but it has not yet published results.¹⁵ To date, there are no pediatric clinical trials examining andexanet alpha. Future work will need to establish efficacy and safety of reversal agents in pediatrics.

DOACs have not been adequately studied in populations of patients with comorbidities, such as liver disease, renal disease, altered enteral absorption, and BMI higher than 40. Physiologic differences in children with cancer and in neonates merit further evaluation of DOAC safety and efficacy. While ongoing trials established weight-based dosing regimens for children, longitudinal studies will need to ensure adequate anticoagulation, especially in the populations listed here.

The safety outcomes in most DOAC studies include clinically relevant bleeding and VTE-related mortality. These outcomes are much less common in pediatric patients than they are in adults, and future studies may need to expand safety outcomes to those more frequently seen in children. Primary and secondary endpoint variability in pediatric DOAC clinical trials presents challenges interpreting and comparing study results.

VTE is an increasingly common complication in hospitalized children contributing to significant morbidity.¹ For decades, the only treatment options have been UFH, LMWH, or warfarin. DOACs offer many advantages compared with standard anticoagulation options. The only clinical trial evaluating efficacy and safety of DOACs published to date demonstrates that pediatric patients taking rivaroxaban have outcomes similar to those of patients receiving standard care. It is expected that DOACs will gain FDA approval for treatment of VTE in pediatric patients in the near future; therefore, hospitalists should understand indications for use of these medications.

A 70-year-old woman with Medicare insurance and a history of mild dementia and chronic bronchiectasis was hospitalized for acute respiratory failure due to influenza. She was treated in the intensive care unit (ICU) for 2 days, received mechanical ventilation, and was subsequently extubated and weaned to high-flow nasal cannula (HFNC) at 8 liters of oxygen per minute and noninvasive ventilation at bedtime. She had otherwise stable cognition and required no other medical or nursing therapies. For recovery, she was referred to a skilled nursing facility (SNF) for respiratory support and rehabilitation but was declined due to HFNC use, noninvasive ventilation, and mild dementia. Instead, she was transferred to a long-term acute care hospital (LTACH) for respiratory support. In the context of major post-acute care (PAC) policy changes, where should—and could—this patient go to recover after hospitalization?

In 2018, 44% of hospitalized patients with fee-for-service Medicare (herein referred to as Medicare) were discharged to PAC, accounting for nearly $60 billion in annual Medicare spending.¹ PAC includes four levels of care—home health agencies (HHAs), SNFs, inpatient rehabilitation facilities (IRFs), and LTACHs—which vary in intensity and complexity of the medical, skilled nursing, and rehabilitative services they provide; use separate reimbursement systems; employ different quality metrics; and have different regulatory requirements (Table 1). Because hospitalists care for the majority of these patients and commonly serve in leadership roles for transitions of care and PAC use, PAC policy is important, as it has direct implications on discharge patterns and the quality and nature of patient care after discharge.

HHAs, the most commonly used PAC setting, provide skilled nursing or therapy to homebound beneficiaries.¹ HHAs were historically reimbursed a standardized 60-day episode payment based on casemix, which was highly dependent on the number of therapy visits provided, with extremely little contribution from nontherapy services, such as skilled nursing and home health aide visits.²

SNFs, which comprise nearly half of PAC spending, provide short-term skilled nursing and rehabilitative services following hospitalization. SNFs are reimbursed on a per diem basis by Medicare, with reimbursement historically determined by the intensity of the dominant service furnished to the patient—either nursing, ancillary care (which includes medications, supplies/equipment, and diagnostic testing), or rehabilitation.³ Due to strong financial incentives, payment for more than 90% of SNF days was based solely on rehabilitation therapy furnished, with 33% of SNF patients receiving ultra-high rehabilitation (>720 minutes/week),³even if it was not considered beneficial or within the patient’s goals of care.⁴

IRFs provide intensive rehabilitation to patients who are able to participate in at least 3 hours of multidisciplinary therapy per day.¹ IRF admissions are paid a bundled rate by Medicare based on the patient’s primary reason for rehabilitation, their age, and their level of functioning and cognition.

LTACHs, the most intensive and expensive PAC setting, care for patients with a range of complex hospital-level care needs, including intravenous (IV) infusions, complex wound care, and respiratory support. Since 2002, the only requirements for LTACHs have been to meet Medicare’s requirements for hospital accreditation and maintain an average length of stay of 25 days for their population.⁵ LTACH stays are paid a bundled rate by Medicare based on diagnosis.

Due to considerable variation in PAC use, with concerns that similar patients can be treated in different PAC settings,^6,7 the Centers for Medicare & Medicaid Services (CMS) recently introduced several major policy changes for HHAs, SNFs, and LTACHs (Table 1).¹ No major policy changes were made for IRFs.

For HHAs and SNFs, CMS implemented new payment models to better align payment with patients’ care needs rather than the provision of rehabilitation therapy.¹ For SNFs, the Patient
Driven Payment Model (PDPM) was implemented October 1, 2019, and for HHAs, the Patient-Driven Groupings Model (PDGM) was implemented January 1, 2020. These policies increase payment for patients who have nursing or ancillary care needs, such as IV medications, wound care, and respiratory support. For example, the per diem payment to SNFs is projected to increase 10% to 30% for patients needing dialysis, IV medications, wound care, and respiratory support, such as tracheostomy care.⁸ These policies also increase payment for patients with greater severity and complexity, such as patients with severe cognitive impairment and multimorbidity. Importantly, these policies pay HHAs and SNFs based on patients’ clinical needs and not solely based on the amount of rehabilitation therapy delivered, which could increase both the number and complexity of patients that SNFs accept.

To discourage LTACH use by patients who are unlikely to benefit from this level of care, CMS fully implemented the site-neutral payment policy on October 1, 2020 (although it is paused during the coronavirus disease 2019 [COVID-19] pandemic), which substantially decreased payment to LTACHs for patients who either did not have an ICU stay of 3 or more days preceding the transfer or did not receive prolonged mechanical ventilation in the LTACH for 96 or more hours.

Historically, PAC payment policy has not properly incentivized the appropriate amount of care to be delivered in the appropriate setting.⁹ The recent HHA, SNF, and LTACH policy changes not only shift the discharge of patients across PAC settings, but also change the amount and type of care that occurs at each PAC site (Table 2). The potential benefit of these new policies is that they will help to align the right level of PAC with patients’ needs by discouraging inappropriate use and unnecessary services. Under the new HHA and SNF payment models, initial media reports suggest a decline in therapy services has occurred, which could be beneficial if the therapy was excessive and not indicated.^4,10,11 Similarly, LTACHs are experiencing a large decline in admissions as fewer patients meet the new payment criteria.¹ As with all policy changes, the potential exists for unintended consequences. Because HHAs and SNFs are no longer incentivized to provide therapy, they might withhold the provision of needed rehabilitation therapy.¹⁰ Furthermore, because payments are based on patient coding by HHA and SNF providers under the new payment models, coding practices may change in order to optimize their payments. Indeed, the PDGM policy for HHAs includes a “behavioral adjustment” to account for anticipated changes in improved documentation by HHAs. Because LTACHs will be less likely to admit patients without prolonged mechanical ventilation or a qualifying ICU stay of 3 or more days, these patients might remain in the hospital for longer periods of time if they are too sick or their care needs are too complex for other PAC settings. Given these possible unintended consequences, the implications for hospital discharge patterns, PAC access, and quality of care will need to be closely monitored, as it is unclear how these PAC policy changes will impact patient care.

In terms of broader payment reform, the four PAC settings are still fragmented, with little effort to unify payment, regulation, and quality across the PAC continuum. As required by the Improving Medicare Post-Acute Care Transformation (IMPACT) Act of 2014, we would encourage the adoption of a unified PAC payment system that spans the four settings, with payments based on patient characteristics and needs rather than site of service.¹² This type of reform would also harmonize regulation and quality measurement and reward payments across settings. Currently, CMS is standardizing patient assessment data and quality metrics across the four PAC settings. Given the COVID-19 pandemic, the transition to a unified PAC payment system is likely several years away.

For our patient who was transferred to an LTACH after referrals to SNFs were denied, PAC options now differ following these major PAC policy reforms, and SNF transfer would be an option. This is because SNFs will receive higher payment for providing respiratory support under the PDPM, and LTACHs will receive considerably lower reimbursement because the patient did not have a qualifying ICU stay or require prolonged mechanical ventilation. Furthermore, hospitals participating in accountable care organizations would achieve greater savings, given that LTACHs cost at least three times as much as SNFs for comparable diagnoses.

Instead of referring this patient to a LTACH, the care team (hospitalist, discharge navigator, and case manager) should inform and educate the patient about discharge options to SNFs for weaning from respiratory support. To help patients and caregivers choose a facility, the discharge planning team should provide data about the quality of SNFs (eg, CMS Star Ratings scores) instead of simply providing a list of names and locations.^13,14 Discharge planning should start as soon as possible to permit caregivers an opportunity to visit facilities and for the providers to coordinate the transfer as seamlessly as possible.

Recent major PAC policy changes will change where hospitals discharge medically complex patients and the services they will receive at these PAC settings. Historically, reduction in PAC use has been a key source for savings in alternative payment models that encourage value over volume, such as accountable care organizations and episode-based (“bundled”) payment models.¹⁵ We anticipate these PAC policy changes are a step in the right direction to further enable hospitals to achieve value by more closely aligning PAC incentives with patients’ needs.

A 70-year-old woman with Medicare insurance and a history of mild dementia and chronic bronchiectasis was hospitalized for acute respiratory failure due to influenza. She was treated in the intensive care unit (ICU) for 2 days, received mechanical ventilation, and was subsequently extubated and weaned to high-flow nasal cannula (HFNC) at 8 liters of oxygen per minute and noninvasive ventilation at bedtime. She had otherwise stable cognition and required no other medical or nursing therapies. For recovery, she was referred to a skilled nursing facility (SNF) for respiratory support and rehabilitation but was declined due to HFNC use, noninvasive ventilation, and mild dementia. Instead, she was transferred to a long-term acute care hospital (LTACH) for respiratory support. In the context of major post-acute care (PAC) policy changes, where should—and could—this patient go to recover after hospitalization?

In 2018, 44% of hospitalized patients with fee-for-service Medicare (herein referred to as Medicare) were discharged to PAC, accounting for nearly $60 billion in annual Medicare spending.¹ PAC includes four levels of care—home health agencies (HHAs), SNFs, inpatient rehabilitation facilities (IRFs), and LTACHs—which vary in intensity and complexity of the medical, skilled nursing, and rehabilitative services they provide; use separate reimbursement systems; employ different quality metrics; and have different regulatory requirements (Table 1). Because hospitalists care for the majority of these patients and commonly serve in leadership roles for transitions of care and PAC use, PAC policy is important, as it has direct implications on discharge patterns and the quality and nature of patient care after discharge.

HHAs, the most commonly used PAC setting, provide skilled nursing or therapy to homebound beneficiaries.¹ HHAs were historically reimbursed a standardized 60-day episode payment based on casemix, which was highly dependent on the number of therapy visits provided, with extremely little contribution from nontherapy services, such as skilled nursing and home health aide visits.²

SNFs, which comprise nearly half of PAC spending, provide short-term skilled nursing and rehabilitative services following hospitalization. SNFs are reimbursed on a per diem basis by Medicare, with reimbursement historically determined by the intensity of the dominant service furnished to the patient—either nursing, ancillary care (which includes medications, supplies/equipment, and diagnostic testing), or rehabilitation.³ Due to strong financial incentives, payment for more than 90% of SNF days was based solely on rehabilitation therapy furnished, with 33% of SNF patients receiving ultra-high rehabilitation (>720 minutes/week),³even if it was not considered beneficial or within the patient’s goals of care.⁴

IRFs provide intensive rehabilitation to patients who are able to participate in at least 3 hours of multidisciplinary therapy per day.¹ IRF admissions are paid a bundled rate by Medicare based on the patient’s primary reason for rehabilitation, their age, and their level of functioning and cognition.

LTACHs, the most intensive and expensive PAC setting, care for patients with a range of complex hospital-level care needs, including intravenous (IV) infusions, complex wound care, and respiratory support. Since 2002, the only requirements for LTACHs have been to meet Medicare’s requirements for hospital accreditation and maintain an average length of stay of 25 days for their population.⁵ LTACH stays are paid a bundled rate by Medicare based on diagnosis.

Due to considerable variation in PAC use, with concerns that similar patients can be treated in different PAC settings,^6,7 the Centers for Medicare & Medicaid Services (CMS) recently introduced several major policy changes for HHAs, SNFs, and LTACHs (Table 1).¹ No major policy changes were made for IRFs.

For HHAs and SNFs, CMS implemented new payment models to better align payment with patients’ care needs rather than the provision of rehabilitation therapy.¹ For SNFs, the Patient
Driven Payment Model (PDPM) was implemented October 1, 2019, and for HHAs, the Patient-Driven Groupings Model (PDGM) was implemented January 1, 2020. These policies increase payment for patients who have nursing or ancillary care needs, such as IV medications, wound care, and respiratory support. For example, the per diem payment to SNFs is projected to increase 10% to 30% for patients needing dialysis, IV medications, wound care, and respiratory support, such as tracheostomy care.⁸ These policies also increase payment for patients with greater severity and complexity, such as patients with severe cognitive impairment and multimorbidity. Importantly, these policies pay HHAs and SNFs based on patients’ clinical needs and not solely based on the amount of rehabilitation therapy delivered, which could increase both the number and complexity of patients that SNFs accept.

To discourage LTACH use by patients who are unlikely to benefit from this level of care, CMS fully implemented the site-neutral payment policy on October 1, 2020 (although it is paused during the coronavirus disease 2019 [COVID-19] pandemic), which substantially decreased payment to LTACHs for patients who either did not have an ICU stay of 3 or more days preceding the transfer or did not receive prolonged mechanical ventilation in the LTACH for 96 or more hours.

Historically, PAC payment policy has not properly incentivized the appropriate amount of care to be delivered in the appropriate setting.⁹ The recent HHA, SNF, and LTACH policy changes not only shift the discharge of patients across PAC settings, but also change the amount and type of care that occurs at each PAC site (Table 2). The potential benefit of these new policies is that they will help to align the right level of PAC with patients’ needs by discouraging inappropriate use and unnecessary services. Under the new HHA and SNF payment models, initial media reports suggest a decline in therapy services has occurred, which could be beneficial if the therapy was excessive and not indicated.^4,10,11 Similarly, LTACHs are experiencing a large decline in admissions as fewer patients meet the new payment criteria.¹ As with all policy changes, the potential exists for unintended consequences. Because HHAs and SNFs are no longer incentivized to provide therapy, they might withhold the provision of needed rehabilitation therapy.¹⁰ Furthermore, because payments are based on patient coding by HHA and SNF providers under the new payment models, coding practices may change in order to optimize their payments. Indeed, the PDGM policy for HHAs includes a “behavioral adjustment” to account for anticipated changes in improved documentation by HHAs. Because LTACHs will be less likely to admit patients without prolonged mechanical ventilation or a qualifying ICU stay of 3 or more days, these patients might remain in the hospital for longer periods of time if they are too sick or their care needs are too complex for other PAC settings. Given these possible unintended consequences, the implications for hospital discharge patterns, PAC access, and quality of care will need to be closely monitored, as it is unclear how these PAC policy changes will impact patient care.

In terms of broader payment reform, the four PAC settings are still fragmented, with little effort to unify payment, regulation, and quality across the PAC continuum. As required by the Improving Medicare Post-Acute Care Transformation (IMPACT) Act of 2014, we would encourage the adoption of a unified PAC payment system that spans the four settings, with payments based on patient characteristics and needs rather than site of service.¹² This type of reform would also harmonize regulation and quality measurement and reward payments across settings. Currently, CMS is standardizing patient assessment data and quality metrics across the four PAC settings. Given the COVID-19 pandemic, the transition to a unified PAC payment system is likely several years away.

For our patient who was transferred to an LTACH after referrals to SNFs were denied, PAC options now differ following these major PAC policy reforms, and SNF transfer would be an option. This is because SNFs will receive higher payment for providing respiratory support under the PDPM, and LTACHs will receive considerably lower reimbursement because the patient did not have a qualifying ICU stay or require prolonged mechanical ventilation. Furthermore, hospitals participating in accountable care organizations would achieve greater savings, given that LTACHs cost at least three times as much as SNFs for comparable diagnoses.

Instead of referring this patient to a LTACH, the care team (hospitalist, discharge navigator, and case manager) should inform and educate the patient about discharge options to SNFs for weaning from respiratory support. To help patients and caregivers choose a facility, the discharge planning team should provide data about the quality of SNFs (eg, CMS Star Ratings scores) instead of simply providing a list of names and locations.^13,14 Discharge planning should start as soon as possible to permit caregivers an opportunity to visit facilities and for the providers to coordinate the transfer as seamlessly as possible.

Recent major PAC policy changes will change where hospitals discharge medically complex patients and the services they will receive at these PAC settings. Historically, reduction in PAC use has been a key source for savings in alternative payment models that encourage value over volume, such as accountable care organizations and episode-based (“bundled”) payment models.¹⁵ We anticipate these PAC policy changes are a step in the right direction to further enable hospitals to achieve value by more closely aligning PAC incentives with patients’ needs.

A 70-year-old woman with Medicare insurance and a history of mild dementia and chronic bronchiectasis was hospitalized for acute respiratory failure due to influenza. She was treated in the intensive care unit (ICU) for 2 days, received mechanical ventilation, and was subsequently extubated and weaned to high-flow nasal cannula (HFNC) at 8 liters of oxygen per minute and noninvasive ventilation at bedtime. She had otherwise stable cognition and required no other medical or nursing therapies. For recovery, she was referred to a skilled nursing facility (SNF) for respiratory support and rehabilitation but was declined due to HFNC use, noninvasive ventilation, and mild dementia. Instead, she was transferred to a long-term acute care hospital (LTACH) for respiratory support. In the context of major post-acute care (PAC) policy changes, where should—and could—this patient go to recover after hospitalization?

In 2018, 44% of hospitalized patients with fee-for-service Medicare (herein referred to as Medicare) were discharged to PAC, accounting for nearly $60 billion in annual Medicare spending.¹ PAC includes four levels of care—home health agencies (HHAs), SNFs, inpatient rehabilitation facilities (IRFs), and LTACHs—which vary in intensity and complexity of the medical, skilled nursing, and rehabilitative services they provide; use separate reimbursement systems; employ different quality metrics; and have different regulatory requirements (Table 1). Because hospitalists care for the majority of these patients and commonly serve in leadership roles for transitions of care and PAC use, PAC policy is important, as it has direct implications on discharge patterns and the quality and nature of patient care after discharge.

HHAs, the most commonly used PAC setting, provide skilled nursing or therapy to homebound beneficiaries.¹ HHAs were historically reimbursed a standardized 60-day episode payment based on casemix, which was highly dependent on the number of therapy visits provided, with extremely little contribution from nontherapy services, such as skilled nursing and home health aide visits.²

SNFs, which comprise nearly half of PAC spending, provide short-term skilled nursing and rehabilitative services following hospitalization. SNFs are reimbursed on a per diem basis by Medicare, with reimbursement historically determined by the intensity of the dominant service furnished to the patient—either nursing, ancillary care (which includes medications, supplies/equipment, and diagnostic testing), or rehabilitation.³ Due to strong financial incentives, payment for more than 90% of SNF days was based solely on rehabilitation therapy furnished, with 33% of SNF patients receiving ultra-high rehabilitation (>720 minutes/week),³even if it was not considered beneficial or within the patient’s goals of care.⁴

IRFs provide intensive rehabilitation to patients who are able to participate in at least 3 hours of multidisciplinary therapy per day.¹ IRF admissions are paid a bundled rate by Medicare based on the patient’s primary reason for rehabilitation, their age, and their level of functioning and cognition.

LTACHs, the most intensive and expensive PAC setting, care for patients with a range of complex hospital-level care needs, including intravenous (IV) infusions, complex wound care, and respiratory support. Since 2002, the only requirements for LTACHs have been to meet Medicare’s requirements for hospital accreditation and maintain an average length of stay of 25 days for their population.⁵ LTACH stays are paid a bundled rate by Medicare based on diagnosis.

Due to considerable variation in PAC use, with concerns that similar patients can be treated in different PAC settings,^6,7 the Centers for Medicare & Medicaid Services (CMS) recently introduced several major policy changes for HHAs, SNFs, and LTACHs (Table 1).¹ No major policy changes were made for IRFs.

For HHAs and SNFs, CMS implemented new payment models to better align payment with patients’ care needs rather than the provision of rehabilitation therapy.¹ For SNFs, the Patient
Driven Payment Model (PDPM) was implemented October 1, 2019, and for HHAs, the Patient-Driven Groupings Model (PDGM) was implemented January 1, 2020. These policies increase payment for patients who have nursing or ancillary care needs, such as IV medications, wound care, and respiratory support. For example, the per diem payment to SNFs is projected to increase 10% to 30% for patients needing dialysis, IV medications, wound care, and respiratory support, such as tracheostomy care.⁸ These policies also increase payment for patients with greater severity and complexity, such as patients with severe cognitive impairment and multimorbidity. Importantly, these policies pay HHAs and SNFs based on patients’ clinical needs and not solely based on the amount of rehabilitation therapy delivered, which could increase both the number and complexity of patients that SNFs accept.

To discourage LTACH use by patients who are unlikely to benefit from this level of care, CMS fully implemented the site-neutral payment policy on October 1, 2020 (although it is paused during the coronavirus disease 2019 [COVID-19] pandemic), which substantially decreased payment to LTACHs for patients who either did not have an ICU stay of 3 or more days preceding the transfer or did not receive prolonged mechanical ventilation in the LTACH for 96 or more hours.

Historically, PAC payment policy has not properly incentivized the appropriate amount of care to be delivered in the appropriate setting.⁹ The recent HHA, SNF, and LTACH policy changes not only shift the discharge of patients across PAC settings, but also change the amount and type of care that occurs at each PAC site (Table 2). The potential benefit of these new policies is that they will help to align the right level of PAC with patients’ needs by discouraging inappropriate use and unnecessary services. Under the new HHA and SNF payment models, initial media reports suggest a decline in therapy services has occurred, which could be beneficial if the therapy was excessive and not indicated.^4,10,11 Similarly, LTACHs are experiencing a large decline in admissions as fewer patients meet the new payment criteria.¹ As with all policy changes, the potential exists for unintended consequences. Because HHAs and SNFs are no longer incentivized to provide therapy, they might withhold the provision of needed rehabilitation therapy.¹⁰ Furthermore, because payments are based on patient coding by HHA and SNF providers under the new payment models, coding practices may change in order to optimize their payments. Indeed, the PDGM policy for HHAs includes a “behavioral adjustment” to account for anticipated changes in improved documentation by HHAs. Because LTACHs will be less likely to admit patients without prolonged mechanical ventilation or a qualifying ICU stay of 3 or more days, these patients might remain in the hospital for longer periods of time if they are too sick or their care needs are too complex for other PAC settings. Given these possible unintended consequences, the implications for hospital discharge patterns, PAC access, and quality of care will need to be closely monitored, as it is unclear how these PAC policy changes will impact patient care.

In terms of broader payment reform, the four PAC settings are still fragmented, with little effort to unify payment, regulation, and quality across the PAC continuum. As required by the Improving Medicare Post-Acute Care Transformation (IMPACT) Act of 2014, we would encourage the adoption of a unified PAC payment system that spans the four settings, with payments based on patient characteristics and needs rather than site of service.¹² This type of reform would also harmonize regulation and quality measurement and reward payments across settings. Currently, CMS is standardizing patient assessment data and quality metrics across the four PAC settings. Given the COVID-19 pandemic, the transition to a unified PAC payment system is likely several years away.

For our patient who was transferred to an LTACH after referrals to SNFs were denied, PAC options now differ following these major PAC policy reforms, and SNF transfer would be an option. This is because SNFs will receive higher payment for providing respiratory support under the PDPM, and LTACHs will receive considerably lower reimbursement because the patient did not have a qualifying ICU stay or require prolonged mechanical ventilation. Furthermore, hospitals participating in accountable care organizations would achieve greater savings, given that LTACHs cost at least three times as much as SNFs for comparable diagnoses.

Instead of referring this patient to a LTACH, the care team (hospitalist, discharge navigator, and case manager) should inform and educate the patient about discharge options to SNFs for weaning from respiratory support. To help patients and caregivers choose a facility, the discharge planning team should provide data about the quality of SNFs (eg, CMS Star Ratings scores) instead of simply providing a list of names and locations.^13,14 Discharge planning should start as soon as possible to permit caregivers an opportunity to visit facilities and for the providers to coordinate the transfer as seamlessly as possible.

Recent major PAC policy changes will change where hospitals discharge medically complex patients and the services they will receive at these PAC settings. Historically, reduction in PAC use has been a key source for savings in alternative payment models that encourage value over volume, such as accountable care organizations and episode-based (“bundled”) payment models.¹⁵ We anticipate these PAC policy changes are a step in the right direction to further enable hospitals to achieve value by more closely aligning PAC incentives with patients’ needs.

A 23-year-old woman presented to the emergency department complaining of “feeling terrible” for the past week. She described subjective fevers, chills, nonproductive cough, myalgias, and nausea. Her symptoms worsened on the day of presentation, with drenching night sweats, worsening myalgias, and generalized fatigue. She was unable to tolerate oral intake due to persistent nausea and had one episode of emesis.

While the initial constellation of symptoms suggests a viral syndrome, its progression over a week raises concern for something more ominous. Of her relatively nonspecific symptoms, prominent myalgias accompanied by a febrile illness may be most helpful. Fever, myalgias, and nonproductive cough are typical of seasonal influenza, although the presence of nausea and vomiting is atypical in adults. (Though this patient presented for care prior to the coronavirus disease 2019 [COVID-19] pandemic, depending on the timing of this presentation, COVID-19 should be considered.) Acute viral myositis can complicate many viral illnesses, such as influenza, coxsackie, and Epstein-Barr virus infections. Other infectious causes of myositis include systemic bacterial infections, spirochete diseases, and other viral infections, including dengue fever. Myalgias can also be a prominent feature of noninfectious systemic inflammatory conditions, such as systemic lupus erythematosus, rheumatoid arthritis, polymyositis, and systemic vasculitis. Night sweats, while concerning, can be present in myriad conditions, and are not usually a discriminating symptom.

Her past medical history included depression, nephrolithiasis, frequent urinary tract infections, bladder spasms, and recurrent genital herpes simplex virus infection. Her medications included bupropion, microgestin, mirabegron, and valacyclovir. Her father had emphysema.

The patient was employed as a physical therapy assistant in a geriatric care center. Two weeks prior to presentation, she traveled from her home in North Carolina to visit a friend in Atlanta, Georgia. Shortly after the patient returned home, her friend in Atlanta became ill and was treated empirically for Legionella infection because of a recent outbreak in the area. One week prior to presentation, the patient and her boyfriend went on a day hike in the Smoky Mountains in North Carolina, but the patient did not recall any insect or tick bites. Her boyfriend had not been ill.

This history elucidates several potentially relevant medication and environmental exposures. Although bupropion can cause myalgias, neither it nor the other medications she is taking are likely to cause her constellation of symptoms. Her travel history to Atlanta suggests possible, though unconfirmed, exposure to Legionella pneumophila. Notably, she would have had to be exposed to the same source as her friend, since transmission of Legionella occurs via contaminated water and soil, not by human-to-human contact. Legionella infection typically causes a pneumonic process as described here, but her prominent myalgias would not be typical.

Her hike in the Smoky Mountains could have exposed her to several vector-borne diseases. Mosquito-borne dengue in North Carolina is extremely rare, but West Nile virus and eastern equine virus are found within that region. West Nile virus could cause a similar illness, although the cough and lack of neurologic symptoms would be unusual. Eastern equine virus can also cause similar symptoms but is quite rare.

Tick-borne illnesses that should be considered for this region include Lyme disease, Rocky Mountain spotted fever (RMSF), ehrlichiosis, and babesiosis. These tend to present with nonspecific symptoms, but myalgias and fever are consistent features. Lyme disease this close to tick exposure usually presents with the characteristic erythema migrans rash, present in 80% of cases, with or without an influenza-like illness. Approximately 80% of patients do not recall a tick bite, even though a tick must be attached for 36 to 48 hours to transmit the spirochete. RMSF often presents with fever and myalgias, with arthralgias and headache, which are lacking in this case. The common, characteristic rash of blanching erythematous macules that convert to petechiae, starting at the ankles and wrists and spreading to the trunk, is often absent at presentation, showing up at days 3 to 5 in most patients.

Ehrlichiosis presents with an influenza-like illness, but up to half of patients also have nausea and cough. It can also present with a macular and petechial rash in a minority of patients. Lastly, babesiosis presents with an influenza-like illness and less often with cough or nausea. At this juncture, RMSF and ehrlichiosis are possibilities given the hiking history and symptoms, although the absence of a rash points more to ehrlichiosis.

The patient did not smoke cigarettes but had used a JUUL^© vaporizer daily for the prior 2 years. Her last use was 1 week prior to admission. She used tetrahydrocannabinol (THC) pods purchased online in the vaporizer on a few occasions 1month prior but had not used THC since that time. She denied alcohol or other drug use.

Until recently, this important detail about vaping use would have been passed over without much consideration. Though reports of acute lung injury from vaping were published as early as 2017, it first came to national attention in August 2019 when the Centers for Disease Control and Prevention posted a Health Advisory about severe lung injury associated with e-cigarette use. Of note, this advisory and subsequent published case series outline that e-cigarette, or vaping, use-associated lung injury (EVALI) may present with more than just respiratory symptoms. Most patients have respiratory symptoms such as shortness of breath, cough, or pleurisy, but many have gastrointestinal symptoms which may include abdominal pain, nausea, vomiting, and diarrhea.¹ Constitutional symptoms, including fever, chills, or weight loss, may also predominate.² In some cases, the gastrointestinal symptoms precede the pulmonary symptoms. This patient’s symptoms warrant consideration of EVALI starting with a chest x-ray (CXR), which is usually abnormal in this disease.²

Physical examination revealed that the patient was alert, diaphoretic, and in mild respiratory distress. Temperature was 103.6 °F, blood pressure 129/75 mm Hg, pulse 130 beats per minute, respiratory rate 20 per minute, and oxygen saturation 97% while breathing ambient air. Cardiac examination revealed tachycardia without murmurs, rubs, or gallops. Lung exam revealed scattered rhonchi over the left posterior lower chest without egophony or dullness to percussion. Findings from abdominal, skin, neurologic, lymph node, and musculoskeletal exams were unremarkable.

Her fever, tachycardia, and respiratory distress point to a pulmonary process such as pneumonia or EVALI, even though she does not have definitive physical exam evidence of pneumonia. She presents with systemic inflammatory response syndrome without significant hypoxia and with borderline tachypnea, which could be related to sepsis or lactic acidosis from a systemic infection other than pneumonia. Her symptom complex could also be compatible with severe influenza infection. The absence of rash makes RMSF less likely.

Results of a complete blood count demonstrated a white blood cell count of 12,600/µL with 87% neutrophils. Results of a metabolic panel were normal, and a urine pregnancy test was negative. The electrocardiogram revealed sinus tachycardia without other abnormalities. A CXR showed no evidence of acute cardiopulmonary abnormalities.

Her lab studies lack thrombocytopenia, which is often found in ehrlichiosis and RMSF. Leukopenia is also absent, which can be seen in Lyme disease and ehrlichiosis. The mild leukocytosis could be consistent with pneumonia, influenza, and EVALI and is not discriminating. The normal CXR goes against pneumonia or EVALI; however, 9% of patients with EVALI in one case series had a normal CXR, while computed tomography (CT) of the chest demonstrated bilateral ground-glass opacities.³ Chest CT is indicated in this case given the poor correlation of the CXR findings and this patient’s pronounced respiratory symptoms.

CT of the chest with contrast did not show a pulmonary embolism but revealed diffuse ground-glass opacities, predominantly in the dependent lower lobes (Figure 1).

Acute conditions with diffuse ground-glass opacities include mycoplasma, Pneumocystis jiroveci and viral pneumonias, pulmonary hemorrhage and edema, acute interstitial pneumonia, eosinophilic lung diseases, and hypersensitivity pneumonitis. Diffuse ground-glass opacities are also seen in almost all patients with EVALI. Though less likely, RMSF, babesiosis, and ehrlichiosis are not ruled out by these chest CT findings, since these disease entities can sometimes cause pulmonary manifestations, including pneumonia, pulmonary edema, and acute respiratory distress syndrome (ARDS).⁴

In addition to Legionella and pneumococcal urinary antigen tests, respiratory viral panel, and blood cultures, it would be judicious to obtain HIV, C-reactive protein, and erythrocyte sedimentation rate (ESR) testing; these last two tests are often markedly elevated in EVALI. The utility of bronchoalveolar lavage (BAL) in suspected EVALI cases is not clearly defined, but should be considered in this case to ensure that infectious etiologies are not missed.² Because of her potential environmental exposures, serologic testing for RMSF and ehrlichiosis should be sent.

Given the overlap in signs and symptoms of EVALI with various, potentially life-threatening infections, she should be empirically treated with antibiotics to cover for community-acquired pneumonia. Adding or even substituting doxycycline for a macrolide antibiotic in this regimen should be considered given that it would treat both RMSF and ehrlichiosis pending further test results. Delay in treating RMSF is associated with worse outcomes. If she is presenting during influenza season, she should also be treated with a neuraminidase inhibitor while awaiting influenza test results. Though the pathophysiology of EVALI is not entirely known, it appears to be inflammatory in nature. Most presumed cases have responded to corticosteroids, with improvement in oxygenation.² Therefore, treatment with corticosteroids may be warranted to improve oxygenation while ruling out infectious processes.

The patient was admitted to the general medicine wards and started on ceftriaxone and azithromycin for empiric treatment of community-acquired pneumonia. On hospital day 2, a respiratory viral panel returned negative. Procalcitonin, HIV, and blood cultures all returned negative. An ESR was elevated at 86 mm/h. The patient continued to have daily fevers and developed erythematous, blanching macules on the neck, chest, back, and arms, which were noted to occur during febrile periods. Ceftriaxone and azithromycin were discontinued, and doxycycline was started. By hospital day 4, the patient’s oxygen saturation worsened to 86% on ambient air. She continued to have fevers and her cough worsened, with occasional blood-streaked sputum. The patient was transferred to the intensive care unit for closer monitoring.

On hospital day 5, she required intubation for worsening hypoxia. Bronchoscopy was performed, which revealed small mucosal crypts along the left mainstem bronchus. A small amount of bleeding after transbronchial biopsy of the left lower lobe was noted, which resolved with occlusion using the bronchoscope. BAL was performed, which revealed red, cloudy aspirate with 1,100 white blood cells (85% neutrophils) and 22,400 red blood cells. No bacteria were identified.

The patient has developed hypoxic respiratory failure despite appropriate antibiotics and negative cultures, increasing the likelihood of a noninfectious etiology. Her rash is not typical for RMSF, which usually starts as a macular or petechial rash at the ankles and wrists, and spreads centrally to the trunk. Rash is not typically associated with EVALI, and in this case, may represent miliaria caused by her fever.

The mucosal crypts seen on bronchoscopy are nonspecific, likely indicating inflammation from vaping. The BAL otherwise suggests diffuse alveolar hemorrhage (DAH), although sequential BAL aliquots are needed to confirm this diagnosis. DAH is usually caused by pulmonary capillaritis from vasculitis, Goodpasture disease, rheumatic diseases, or diffuse alveolar damage from toxins, infections, rheumatic diseases, or interstitial or organizing pneumonias. Diffuse alveolar damage is the pathologic finding of ARDS, which can be seen in severe cases of many of the conditions discussed, including EVALI, ehrlichiosis, babesiosis, sepsis, and community-acquired pneumonia.⁴

The BAL is most consistent with EVALI, which often shows elevated neutrophils. DAH due to vaping has also been reported.⁵ In patients with EVALI, varied pathologic findings of acute lung injury have been reported, including diffuse alveolar damage.⁶ At this point, laboratory evaluation for rheumatologic diseases and vasculitis should be obtained, and lung biopsy results reviewed. Given her clinical deterioration, treatment with intravenous corticosteroids for presumed EVALI is warranted.

Urine Legionella and Streptococcal pneumoniae antigen tests were negative. The patient was started on methylprednisolone 40 mg intravenously every 8 hours. Further testing included antinuclear antibodies, which was positive at 1:320, with a dense, fine speckled pattern. Perinuclear antineutrophilic cytoplasmic autoantibody, cytoplasmic antineutrophilic cytoplasmic autoantibody, myeloperoxidase, proteinase 3, double-stranded DNA, and glomerular basement membrane IgG were all negative. Transbronchial lung biopsy revealed severe acute lung injury consistent with diffuse alveolar damage. The pulmonary interstitium was mildly expanded by edema, with a moderate number of eosinophilic hyaline membranes. There were no eosinophils or evidence of hemorrhage, granulomas, or giant cells. These changes, within this clinical context, were diagnostic for EVALI.

The patient was intubated for 4 days and completed a course of empiric antibiotics as well as a 10-day course of prednisone. She was discharged on hospital day 17 on 2 L continuous oxygen via nasal cannula. Two days after discharge, she developed worsening dyspnea and chest pain and was readmitted with worsening ground-glass opacities, left upper lobe and right- sided pneumothoraces, and subcutaneous emphysema (Figure 2). She was treated with continuous oxygen to maintain oxygen saturation at 100% and eventually discharged home 3 days later on 3 L continuous oxygen. She attended pulmonary rehabilitation and was weaned off oxygen 2 months later, with marked improvement in aeration of both lungs (Figure 3). She continued to abstain from tobacco and THC products.

The first electronic cigarette (e-cigarette) device was developed in 2003 by a Chinese pharmacist and introduced to the American market in 2007.⁷ E-cigarettes produce an inhalable aerosol by heating a liquid containing a variety of chemicals, nicotine, and flavors, with or without other additives. Originally promoted as a safer nontobacco and cessation device by producers, e-cigarette sales grew at an annual rate of 115% between 2009 and 2012.⁸ E-cigarettes can also be used to deliver THC, the psychoactive component of cannabis.

Since the advent of e-cigarettes, their safety has been a topic of concern. In August 2019, the CDC announced 215 possible cases of severe pulmonary disease associated with the use of e-cigarette products that were reported by 25 state health departments.¹ By February 2020, EVALI had affected more than 2,800 patients hospitalized across the United States.⁹

The presenting symptoms of EVALI are varied and nonspecific. The largest EVALI case series, published by Layden et al in 2020, included 98 patients who had a median duration of 6 days of symptoms prior to presentation.³ Respiratory symptoms occurred in 97% of patients, including shortness of breath, any chest pain, pleuritic chest pain, cough, and hemoptysis.³ Presentations also included a variety of gastrointestinal (77%) and constitutional (100%) symptoms, which most commonly included nausea, vomiting, and fever.³ Additional case series have supported a specific pattern of presentation, most commonly including pleuritic chest pain, nonproductive cough, or shortness of breath occurring days to weeks prior to presentation. Associated fatigue, fever, and tachycardia may be present, as well as nausea, vomiting, diarrhea and abdominal pain, and in some cases, these have preceded respiratory symptoms.^3,10,11

The vital signs and physical examination, laboratory, and imaging results associated with EVALI are also fairly nonspecific. The most common reason for hospitalization in EVALI is hypoxia, which can progress to acute respiratory failure requiring supplemental oxygen or, as in this case, mechanical ventilation. The most common laboratory finding is leukocytosis greater than 11,000/µL, with more than 80% neutrophils and an ESR greater than 30 mm/hr. In the Layden et al case series, 83% of patients had an abnormal CXR. All patients who underwent CT scan of the chest had bilateral ground-glass opacities, often with subpleural sparing.³ A minority of patients were found to have a pneumothorax, generally a late finding.^3,12 Accordingly, the CDC now defines confirmed EVALI as use of e-cigarettes during the 90 days before symptom onset with the presence of pulmonary infiltrates (opacities on CXR or ground-glass opacities on chest CT), negative results on testing for all clinically indicated respiratory infections including respiratory viral panel and influenza PCR, and no alternative plausible diagnoses.¹³

The presumed etiology of EVALI is chemical exposure because no consistent infectious etiology has been identified.⁶ No consistent e-cigarette product, substance, or additive has been identified in all cases, nor has one product been directly linked to EVALI. However, the CDC recently announced that vitamin E acetate in vaping products appears to be associated with EVALI.⁹ In December 2019, Blount et al identified vitamin E acetate in BAL fluid samples from 48 of 51 EVALI patients.¹⁴ Additionally, while no other toxins were identified, 94% of samples contained THC or its metabolites or patients had reported vaping THC within 90 days preceding illness.¹⁴

The most effective treatment strategy for EVALI is still unknown. It is recommended to treat with empiric antibiotics for at least 48 hours (and antivirals during influenza season) if the history is unclear or if the patient is intubated or has severe hypoxemia.² If antibiotic and/or antiviral therapies do not lead to clinical improvement, corticosteroids should be added, as they lead to improved oxygenation in many patients.² Kalininskiy et al recommend initial administration of methylprednisolone 40 mg every 8 hours, with transition to oral prednisone to complete a 2-week course.² Given rates of rehospitalization (2.7%) and death (2%) in EVALI, the CDC advises that patients should be clinically stable for 24 to 48 hours prior to discharge; that follow-up visits should be arranged within 48 hours of discharge; and that cases of EVALI should be reported to the state and local health departments.¹⁵ As seen in the case presented here, with time and continued abstinence from e-cigarette use, the pulmonary effects of EVALI can improve, but long-term outcomes remain unclear. Clinicians must now consider EVALI in patients presenting with respiratory, constitutional, and gastrointestinal complaints when a history of e-cigarette use is present.

• EVALI presents most commonly with a combination of respiratory, gastrointestinal, and constitutional symptoms. including shortness of breath, cough, nausea, vomiting, and fever.
• When considering EVALI, evaluate and treat for potential infectious causes of disease first.
• Corticosteroids are the mainstay of therapy in EVALI, leading to improvement in oxygenation in many patients.
• Most of the reported cases of EVALI have occurred in patients who have vaped THC-containing products.

A 23-year-old woman presented to the emergency department complaining of “feeling terrible” for the past week. She described subjective fevers, chills, nonproductive cough, myalgias, and nausea. Her symptoms worsened on the day of presentation, with drenching night sweats, worsening myalgias, and generalized fatigue. She was unable to tolerate oral intake due to persistent nausea and had one episode of emesis.

While the initial constellation of symptoms suggests a viral syndrome, its progression over a week raises concern for something more ominous. Of her relatively nonspecific symptoms, prominent myalgias accompanied by a febrile illness may be most helpful. Fever, myalgias, and nonproductive cough are typical of seasonal influenza, although the presence of nausea and vomiting is atypical in adults. (Though this patient presented for care prior to the coronavirus disease 2019 [COVID-19] pandemic, depending on the timing of this presentation, COVID-19 should be considered.) Acute viral myositis can complicate many viral illnesses, such as influenza, coxsackie, and Epstein-Barr virus infections. Other infectious causes of myositis include systemic bacterial infections, spirochete diseases, and other viral infections, including dengue fever. Myalgias can also be a prominent feature of noninfectious systemic inflammatory conditions, such as systemic lupus erythematosus, rheumatoid arthritis, polymyositis, and systemic vasculitis. Night sweats, while concerning, can be present in myriad conditions, and are not usually a discriminating symptom.

Her past medical history included depression, nephrolithiasis, frequent urinary tract infections, bladder spasms, and recurrent genital herpes simplex virus infection. Her medications included bupropion, microgestin, mirabegron, and valacyclovir. Her father had emphysema.

The patient was employed as a physical therapy assistant in a geriatric care center. Two weeks prior to presentation, she traveled from her home in North Carolina to visit a friend in Atlanta, Georgia. Shortly after the patient returned home, her friend in Atlanta became ill and was treated empirically for Legionella infection because of a recent outbreak in the area. One week prior to presentation, the patient and her boyfriend went on a day hike in the Smoky Mountains in North Carolina, but the patient did not recall any insect or tick bites. Her boyfriend had not been ill.

This history elucidates several potentially relevant medication and environmental exposures. Although bupropion can cause myalgias, neither it nor the other medications she is taking are likely to cause her constellation of symptoms. Her travel history to Atlanta suggests possible, though unconfirmed, exposure to Legionella pneumophila. Notably, she would have had to be exposed to the same source as her friend, since transmission of Legionella occurs via contaminated water and soil, not by human-to-human contact. Legionella infection typically causes a pneumonic process as described here, but her prominent myalgias would not be typical.

Her hike in the Smoky Mountains could have exposed her to several vector-borne diseases. Mosquito-borne dengue in North Carolina is extremely rare, but West Nile virus and eastern equine virus are found within that region. West Nile virus could cause a similar illness, although the cough and lack of neurologic symptoms would be unusual. Eastern equine virus can also cause similar symptoms but is quite rare.

Tick-borne illnesses that should be considered for this region include Lyme disease, Rocky Mountain spotted fever (RMSF), ehrlichiosis, and babesiosis. These tend to present with nonspecific symptoms, but myalgias and fever are consistent features. Lyme disease this close to tick exposure usually presents with the characteristic erythema migrans rash, present in 80% of cases, with or without an influenza-like illness. Approximately 80% of patients do not recall a tick bite, even though a tick must be attached for 36 to 48 hours to transmit the spirochete. RMSF often presents with fever and myalgias, with arthralgias and headache, which are lacking in this case. The common, characteristic rash of blanching erythematous macules that convert to petechiae, starting at the ankles and wrists and spreading to the trunk, is often absent at presentation, showing up at days 3 to 5 in most patients.

Ehrlichiosis presents with an influenza-like illness, but up to half of patients also have nausea and cough. It can also present with a macular and petechial rash in a minority of patients. Lastly, babesiosis presents with an influenza-like illness and less often with cough or nausea. At this juncture, RMSF and ehrlichiosis are possibilities given the hiking history and symptoms, although the absence of a rash points more to ehrlichiosis.

The patient did not smoke cigarettes but had used a JUUL^© vaporizer daily for the prior 2 years. Her last use was 1 week prior to admission. She used tetrahydrocannabinol (THC) pods purchased online in the vaporizer on a few occasions 1month prior but had not used THC since that time. She denied alcohol or other drug use.

Until recently, this important detail about vaping use would have been passed over without much consideration. Though reports of acute lung injury from vaping were published as early as 2017, it first came to national attention in August 2019 when the Centers for Disease Control and Prevention posted a Health Advisory about severe lung injury associated with e-cigarette use. Of note, this advisory and subsequent published case series outline that e-cigarette, or vaping, use-associated lung injury (EVALI) may present with more than just respiratory symptoms. Most patients have respiratory symptoms such as shortness of breath, cough, or pleurisy, but many have gastrointestinal symptoms which may include abdominal pain, nausea, vomiting, and diarrhea.¹ Constitutional symptoms, including fever, chills, or weight loss, may also predominate.² In some cases, the gastrointestinal symptoms precede the pulmonary symptoms. This patient’s symptoms warrant consideration of EVALI starting with a chest x-ray (CXR), which is usually abnormal in this disease.²

Physical examination revealed that the patient was alert, diaphoretic, and in mild respiratory distress. Temperature was 103.6 °F, blood pressure 129/75 mm Hg, pulse 130 beats per minute, respiratory rate 20 per minute, and oxygen saturation 97% while breathing ambient air. Cardiac examination revealed tachycardia without murmurs, rubs, or gallops. Lung exam revealed scattered rhonchi over the left posterior lower chest without egophony or dullness to percussion. Findings from abdominal, skin, neurologic, lymph node, and musculoskeletal exams were unremarkable.

Her fever, tachycardia, and respiratory distress point to a pulmonary process such as pneumonia or EVALI, even though she does not have definitive physical exam evidence of pneumonia. She presents with systemic inflammatory response syndrome without significant hypoxia and with borderline tachypnea, which could be related to sepsis or lactic acidosis from a systemic infection other than pneumonia. Her symptom complex could also be compatible with severe influenza infection. The absence of rash makes RMSF less likely.

Results of a complete blood count demonstrated a white blood cell count of 12,600/µL with 87% neutrophils. Results of a metabolic panel were normal, and a urine pregnancy test was negative. The electrocardiogram revealed sinus tachycardia without other abnormalities. A CXR showed no evidence of acute cardiopulmonary abnormalities.

Her lab studies lack thrombocytopenia, which is often found in ehrlichiosis and RMSF. Leukopenia is also absent, which can be seen in Lyme disease and ehrlichiosis. The mild leukocytosis could be consistent with pneumonia, influenza, and EVALI and is not discriminating. The normal CXR goes against pneumonia or EVALI; however, 9% of patients with EVALI in one case series had a normal CXR, while computed tomography (CT) of the chest demonstrated bilateral ground-glass opacities.³ Chest CT is indicated in this case given the poor correlation of the CXR findings and this patient’s pronounced respiratory symptoms.

CT of the chest with contrast did not show a pulmonary embolism but revealed diffuse ground-glass opacities, predominantly in the dependent lower lobes (Figure 1).

Acute conditions with diffuse ground-glass opacities include mycoplasma, Pneumocystis jiroveci and viral pneumonias, pulmonary hemorrhage and edema, acute interstitial pneumonia, eosinophilic lung diseases, and hypersensitivity pneumonitis. Diffuse ground-glass opacities are also seen in almost all patients with EVALI. Though less likely, RMSF, babesiosis, and ehrlichiosis are not ruled out by these chest CT findings, since these disease entities can sometimes cause pulmonary manifestations, including pneumonia, pulmonary edema, and acute respiratory distress syndrome (ARDS).⁴

In addition to Legionella and pneumococcal urinary antigen tests, respiratory viral panel, and blood cultures, it would be judicious to obtain HIV, C-reactive protein, and erythrocyte sedimentation rate (ESR) testing; these last two tests are often markedly elevated in EVALI. The utility of bronchoalveolar lavage (BAL) in suspected EVALI cases is not clearly defined, but should be considered in this case to ensure that infectious etiologies are not missed.² Because of her potential environmental exposures, serologic testing for RMSF and ehrlichiosis should be sent.

Given the overlap in signs and symptoms of EVALI with various, potentially life-threatening infections, she should be empirically treated with antibiotics to cover for community-acquired pneumonia. Adding or even substituting doxycycline for a macrolide antibiotic in this regimen should be considered given that it would treat both RMSF and ehrlichiosis pending further test results. Delay in treating RMSF is associated with worse outcomes. If she is presenting during influenza season, she should also be treated with a neuraminidase inhibitor while awaiting influenza test results. Though the pathophysiology of EVALI is not entirely known, it appears to be inflammatory in nature. Most presumed cases have responded to corticosteroids, with improvement in oxygenation.² Therefore, treatment with corticosteroids may be warranted to improve oxygenation while ruling out infectious processes.

The patient was admitted to the general medicine wards and started on ceftriaxone and azithromycin for empiric treatment of community-acquired pneumonia. On hospital day 2, a respiratory viral panel returned negative. Procalcitonin, HIV, and blood cultures all returned negative. An ESR was elevated at 86 mm/h. The patient continued to have daily fevers and developed erythematous, blanching macules on the neck, chest, back, and arms, which were noted to occur during febrile periods. Ceftriaxone and azithromycin were discontinued, and doxycycline was started. By hospital day 4, the patient’s oxygen saturation worsened to 86% on ambient air. She continued to have fevers and her cough worsened, with occasional blood-streaked sputum. The patient was transferred to the intensive care unit for closer monitoring.

On hospital day 5, she required intubation for worsening hypoxia. Bronchoscopy was performed, which revealed small mucosal crypts along the left mainstem bronchus. A small amount of bleeding after transbronchial biopsy of the left lower lobe was noted, which resolved with occlusion using the bronchoscope. BAL was performed, which revealed red, cloudy aspirate with 1,100 white blood cells (85% neutrophils) and 22,400 red blood cells. No bacteria were identified.

The patient has developed hypoxic respiratory failure despite appropriate antibiotics and negative cultures, increasing the likelihood of a noninfectious etiology. Her rash is not typical for RMSF, which usually starts as a macular or petechial rash at the ankles and wrists, and spreads centrally to the trunk. Rash is not typically associated with EVALI, and in this case, may represent miliaria caused by her fever.

The mucosal crypts seen on bronchoscopy are nonspecific, likely indicating inflammation from vaping. The BAL otherwise suggests diffuse alveolar hemorrhage (DAH), although sequential BAL aliquots are needed to confirm this diagnosis. DAH is usually caused by pulmonary capillaritis from vasculitis, Goodpasture disease, rheumatic diseases, or diffuse alveolar damage from toxins, infections, rheumatic diseases, or interstitial or organizing pneumonias. Diffuse alveolar damage is the pathologic finding of ARDS, which can be seen in severe cases of many of the conditions discussed, including EVALI, ehrlichiosis, babesiosis, sepsis, and community-acquired pneumonia.⁴

The BAL is most consistent with EVALI, which often shows elevated neutrophils. DAH due to vaping has also been reported.⁵ In patients with EVALI, varied pathologic findings of acute lung injury have been reported, including diffuse alveolar damage.⁶ At this point, laboratory evaluation for rheumatologic diseases and vasculitis should be obtained, and lung biopsy results reviewed. Given her clinical deterioration, treatment with intravenous corticosteroids for presumed EVALI is warranted.

Urine Legionella and Streptococcal pneumoniae antigen tests were negative. The patient was started on methylprednisolone 40 mg intravenously every 8 hours. Further testing included antinuclear antibodies, which was positive at 1:320, with a dense, fine speckled pattern. Perinuclear antineutrophilic cytoplasmic autoantibody, cytoplasmic antineutrophilic cytoplasmic autoantibody, myeloperoxidase, proteinase 3, double-stranded DNA, and glomerular basement membrane IgG were all negative. Transbronchial lung biopsy revealed severe acute lung injury consistent with diffuse alveolar damage. The pulmonary interstitium was mildly expanded by edema, with a moderate number of eosinophilic hyaline membranes. There were no eosinophils or evidence of hemorrhage, granulomas, or giant cells. These changes, within this clinical context, were diagnostic for EVALI.

The patient was intubated for 4 days and completed a course of empiric antibiotics as well as a 10-day course of prednisone. She was discharged on hospital day 17 on 2 L continuous oxygen via nasal cannula. Two days after discharge, she developed worsening dyspnea and chest pain and was readmitted with worsening ground-glass opacities, left upper lobe and right- sided pneumothoraces, and subcutaneous emphysema (Figure 2). She was treated with continuous oxygen to maintain oxygen saturation at 100% and eventually discharged home 3 days later on 3 L continuous oxygen. She attended pulmonary rehabilitation and was weaned off oxygen 2 months later, with marked improvement in aeration of both lungs (Figure 3). She continued to abstain from tobacco and THC products.

The first electronic cigarette (e-cigarette) device was developed in 2003 by a Chinese pharmacist and introduced to the American market in 2007.⁷ E-cigarettes produce an inhalable aerosol by heating a liquid containing a variety of chemicals, nicotine, and flavors, with or without other additives. Originally promoted as a safer nontobacco and cessation device by producers, e-cigarette sales grew at an annual rate of 115% between 2009 and 2012.⁸ E-cigarettes can also be used to deliver THC, the psychoactive component of cannabis.

Since the advent of e-cigarettes, their safety has been a topic of concern. In August 2019, the CDC announced 215 possible cases of severe pulmonary disease associated with the use of e-cigarette products that were reported by 25 state health departments.¹ By February 2020, EVALI had affected more than 2,800 patients hospitalized across the United States.⁹

The presenting symptoms of EVALI are varied and nonspecific. The largest EVALI case series, published by Layden et al in 2020, included 98 patients who had a median duration of 6 days of symptoms prior to presentation.³ Respiratory symptoms occurred in 97% of patients, including shortness of breath, any chest pain, pleuritic chest pain, cough, and hemoptysis.³ Presentations also included a variety of gastrointestinal (77%) and constitutional (100%) symptoms, which most commonly included nausea, vomiting, and fever.³ Additional case series have supported a specific pattern of presentation, most commonly including pleuritic chest pain, nonproductive cough, or shortness of breath occurring days to weeks prior to presentation. Associated fatigue, fever, and tachycardia may be present, as well as nausea, vomiting, diarrhea and abdominal pain, and in some cases, these have preceded respiratory symptoms.^3,10,11

The vital signs and physical examination, laboratory, and imaging results associated with EVALI are also fairly nonspecific. The most common reason for hospitalization in EVALI is hypoxia, which can progress to acute respiratory failure requiring supplemental oxygen or, as in this case, mechanical ventilation. The most common laboratory finding is leukocytosis greater than 11,000/µL, with more than 80% neutrophils and an ESR greater than 30 mm/hr. In the Layden et al case series, 83% of patients had an abnormal CXR. All patients who underwent CT scan of the chest had bilateral ground-glass opacities, often with subpleural sparing.³ A minority of patients were found to have a pneumothorax, generally a late finding.^3,12 Accordingly, the CDC now defines confirmed EVALI as use of e-cigarettes during the 90 days before symptom onset with the presence of pulmonary infiltrates (opacities on CXR or ground-glass opacities on chest CT), negative results on testing for all clinically indicated respiratory infections including respiratory viral panel and influenza PCR, and no alternative plausible diagnoses.¹³

The presumed etiology of EVALI is chemical exposure because no consistent infectious etiology has been identified.⁶ No consistent e-cigarette product, substance, or additive has been identified in all cases, nor has one product been directly linked to EVALI. However, the CDC recently announced that vitamin E acetate in vaping products appears to be associated with EVALI.⁹ In December 2019, Blount et al identified vitamin E acetate in BAL fluid samples from 48 of 51 EVALI patients.¹⁴ Additionally, while no other toxins were identified, 94% of samples contained THC or its metabolites or patients had reported vaping THC within 90 days preceding illness.¹⁴

The most effective treatment strategy for EVALI is still unknown. It is recommended to treat with empiric antibiotics for at least 48 hours (and antivirals during influenza season) if the history is unclear or if the patient is intubated or has severe hypoxemia.² If antibiotic and/or antiviral therapies do not lead to clinical improvement, corticosteroids should be added, as they lead to improved oxygenation in many patients.² Kalininskiy et al recommend initial administration of methylprednisolone 40 mg every 8 hours, with transition to oral prednisone to complete a 2-week course.² Given rates of rehospitalization (2.7%) and death (2%) in EVALI, the CDC advises that patients should be clinically stable for 24 to 48 hours prior to discharge; that follow-up visits should be arranged within 48 hours of discharge; and that cases of EVALI should be reported to the state and local health departments.¹⁵ As seen in the case presented here, with time and continued abstinence from e-cigarette use, the pulmonary effects of EVALI can improve, but long-term outcomes remain unclear. Clinicians must now consider EVALI in patients presenting with respiratory, constitutional, and gastrointestinal complaints when a history of e-cigarette use is present.

• EVALI presents most commonly with a combination of respiratory, gastrointestinal, and constitutional symptoms. including shortness of breath, cough, nausea, vomiting, and fever.
• When considering EVALI, evaluate and treat for potential infectious causes of disease first.
• Corticosteroids are the mainstay of therapy in EVALI, leading to improvement in oxygenation in many patients.
• Most of the reported cases of EVALI have occurred in patients who have vaped THC-containing products.

A 23-year-old woman presented to the emergency department complaining of “feeling terrible” for the past week. She described subjective fevers, chills, nonproductive cough, myalgias, and nausea. Her symptoms worsened on the day of presentation, with drenching night sweats, worsening myalgias, and generalized fatigue. She was unable to tolerate oral intake due to persistent nausea and had one episode of emesis.

While the initial constellation of symptoms suggests a viral syndrome, its progression over a week raises concern for something more ominous. Of her relatively nonspecific symptoms, prominent myalgias accompanied by a febrile illness may be most helpful. Fever, myalgias, and nonproductive cough are typical of seasonal influenza, although the presence of nausea and vomiting is atypical in adults. (Though this patient presented for care prior to the coronavirus disease 2019 [COVID-19] pandemic, depending on the timing of this presentation, COVID-19 should be considered.) Acute viral myositis can complicate many viral illnesses, such as influenza, coxsackie, and Epstein-Barr virus infections. Other infectious causes of myositis include systemic bacterial infections, spirochete diseases, and other viral infections, including dengue fever. Myalgias can also be a prominent feature of noninfectious systemic inflammatory conditions, such as systemic lupus erythematosus, rheumatoid arthritis, polymyositis, and systemic vasculitis. Night sweats, while concerning, can be present in myriad conditions, and are not usually a discriminating symptom.

Her past medical history included depression, nephrolithiasis, frequent urinary tract infections, bladder spasms, and recurrent genital herpes simplex virus infection. Her medications included bupropion, microgestin, mirabegron, and valacyclovir. Her father had emphysema.

The patient was employed as a physical therapy assistant in a geriatric care center. Two weeks prior to presentation, she traveled from her home in North Carolina to visit a friend in Atlanta, Georgia. Shortly after the patient returned home, her friend in Atlanta became ill and was treated empirically for Legionella infection because of a recent outbreak in the area. One week prior to presentation, the patient and her boyfriend went on a day hike in the Smoky Mountains in North Carolina, but the patient did not recall any insect or tick bites. Her boyfriend had not been ill.

This history elucidates several potentially relevant medication and environmental exposures. Although bupropion can cause myalgias, neither it nor the other medications she is taking are likely to cause her constellation of symptoms. Her travel history to Atlanta suggests possible, though unconfirmed, exposure to Legionella pneumophila. Notably, she would have had to be exposed to the same source as her friend, since transmission of Legionella occurs via contaminated water and soil, not by human-to-human contact. Legionella infection typically causes a pneumonic process as described here, but her prominent myalgias would not be typical.

Her hike in the Smoky Mountains could have exposed her to several vector-borne diseases. Mosquito-borne dengue in North Carolina is extremely rare, but West Nile virus and eastern equine virus are found within that region. West Nile virus could cause a similar illness, although the cough and lack of neurologic symptoms would be unusual. Eastern equine virus can also cause similar symptoms but is quite rare.

Tick-borne illnesses that should be considered for this region include Lyme disease, Rocky Mountain spotted fever (RMSF), ehrlichiosis, and babesiosis. These tend to present with nonspecific symptoms, but myalgias and fever are consistent features. Lyme disease this close to tick exposure usually presents with the characteristic erythema migrans rash, present in 80% of cases, with or without an influenza-like illness. Approximately 80% of patients do not recall a tick bite, even though a tick must be attached for 36 to 48 hours to transmit the spirochete. RMSF often presents with fever and myalgias, with arthralgias and headache, which are lacking in this case. The common, characteristic rash of blanching erythematous macules that convert to petechiae, starting at the ankles and wrists and spreading to the trunk, is often absent at presentation, showing up at days 3 to 5 in most patients.

Ehrlichiosis presents with an influenza-like illness, but up to half of patients also have nausea and cough. It can also present with a macular and petechial rash in a minority of patients. Lastly, babesiosis presents with an influenza-like illness and less often with cough or nausea. At this juncture, RMSF and ehrlichiosis are possibilities given the hiking history and symptoms, although the absence of a rash points more to ehrlichiosis.

The patient did not smoke cigarettes but had used a JUUL^© vaporizer daily for the prior 2 years. Her last use was 1 week prior to admission. She used tetrahydrocannabinol (THC) pods purchased online in the vaporizer on a few occasions 1month prior but had not used THC since that time. She denied alcohol or other drug use.

Until recently, this important detail about vaping use would have been passed over without much consideration. Though reports of acute lung injury from vaping were published as early as 2017, it first came to national attention in August 2019 when the Centers for Disease Control and Prevention posted a Health Advisory about severe lung injury associated with e-cigarette use. Of note, this advisory and subsequent published case series outline that e-cigarette, or vaping, use-associated lung injury (EVALI) may present with more than just respiratory symptoms. Most patients have respiratory symptoms such as shortness of breath, cough, or pleurisy, but many have gastrointestinal symptoms which may include abdominal pain, nausea, vomiting, and diarrhea.¹ Constitutional symptoms, including fever, chills, or weight loss, may also predominate.² In some cases, the gastrointestinal symptoms precede the pulmonary symptoms. This patient’s symptoms warrant consideration of EVALI starting with a chest x-ray (CXR), which is usually abnormal in this disease.²

Physical examination revealed that the patient was alert, diaphoretic, and in mild respiratory distress. Temperature was 103.6 °F, blood pressure 129/75 mm Hg, pulse 130 beats per minute, respiratory rate 20 per minute, and oxygen saturation 97% while breathing ambient air. Cardiac examination revealed tachycardia without murmurs, rubs, or gallops. Lung exam revealed scattered rhonchi over the left posterior lower chest without egophony or dullness to percussion. Findings from abdominal, skin, neurologic, lymph node, and musculoskeletal exams were unremarkable.

Her fever, tachycardia, and respiratory distress point to a pulmonary process such as pneumonia or EVALI, even though she does not have definitive physical exam evidence of pneumonia. She presents with systemic inflammatory response syndrome without significant hypoxia and with borderline tachypnea, which could be related to sepsis or lactic acidosis from a systemic infection other than pneumonia. Her symptom complex could also be compatible with severe influenza infection. The absence of rash makes RMSF less likely.

Results of a complete blood count demonstrated a white blood cell count of 12,600/µL with 87% neutrophils. Results of a metabolic panel were normal, and a urine pregnancy test was negative. The electrocardiogram revealed sinus tachycardia without other abnormalities. A CXR showed no evidence of acute cardiopulmonary abnormalities.

Her lab studies lack thrombocytopenia, which is often found in ehrlichiosis and RMSF. Leukopenia is also absent, which can be seen in Lyme disease and ehrlichiosis. The mild leukocytosis could be consistent with pneumonia, influenza, and EVALI and is not discriminating. The normal CXR goes against pneumonia or EVALI; however, 9% of patients with EVALI in one case series had a normal CXR, while computed tomography (CT) of the chest demonstrated bilateral ground-glass opacities.³ Chest CT is indicated in this case given the poor correlation of the CXR findings and this patient’s pronounced respiratory symptoms.

CT of the chest with contrast did not show a pulmonary embolism but revealed diffuse ground-glass opacities, predominantly in the dependent lower lobes (Figure 1).

Acute conditions with diffuse ground-glass opacities include mycoplasma, Pneumocystis jiroveci and viral pneumonias, pulmonary hemorrhage and edema, acute interstitial pneumonia, eosinophilic lung diseases, and hypersensitivity pneumonitis. Diffuse ground-glass opacities are also seen in almost all patients with EVALI. Though less likely, RMSF, babesiosis, and ehrlichiosis are not ruled out by these chest CT findings, since these disease entities can sometimes cause pulmonary manifestations, including pneumonia, pulmonary edema, and acute respiratory distress syndrome (ARDS).⁴

In addition to Legionella and pneumococcal urinary antigen tests, respiratory viral panel, and blood cultures, it would be judicious to obtain HIV, C-reactive protein, and erythrocyte sedimentation rate (ESR) testing; these last two tests are often markedly elevated in EVALI. The utility of bronchoalveolar lavage (BAL) in suspected EVALI cases is not clearly defined, but should be considered in this case to ensure that infectious etiologies are not missed.² Because of her potential environmental exposures, serologic testing for RMSF and ehrlichiosis should be sent.

Given the overlap in signs and symptoms of EVALI with various, potentially life-threatening infections, she should be empirically treated with antibiotics to cover for community-acquired pneumonia. Adding or even substituting doxycycline for a macrolide antibiotic in this regimen should be considered given that it would treat both RMSF and ehrlichiosis pending further test results. Delay in treating RMSF is associated with worse outcomes. If she is presenting during influenza season, she should also be treated with a neuraminidase inhibitor while awaiting influenza test results. Though the pathophysiology of EVALI is not entirely known, it appears to be inflammatory in nature. Most presumed cases have responded to corticosteroids, with improvement in oxygenation.² Therefore, treatment with corticosteroids may be warranted to improve oxygenation while ruling out infectious processes.

The patient was admitted to the general medicine wards and started on ceftriaxone and azithromycin for empiric treatment of community-acquired pneumonia. On hospital day 2, a respiratory viral panel returned negative. Procalcitonin, HIV, and blood cultures all returned negative. An ESR was elevated at 86 mm/h. The patient continued to have daily fevers and developed erythematous, blanching macules on the neck, chest, back, and arms, which were noted to occur during febrile periods. Ceftriaxone and azithromycin were discontinued, and doxycycline was started. By hospital day 4, the patient’s oxygen saturation worsened to 86% on ambient air. She continued to have fevers and her cough worsened, with occasional blood-streaked sputum. The patient was transferred to the intensive care unit for closer monitoring.

On hospital day 5, she required intubation for worsening hypoxia. Bronchoscopy was performed, which revealed small mucosal crypts along the left mainstem bronchus. A small amount of bleeding after transbronchial biopsy of the left lower lobe was noted, which resolved with occlusion using the bronchoscope. BAL was performed, which revealed red, cloudy aspirate with 1,100 white blood cells (85% neutrophils) and 22,400 red blood cells. No bacteria were identified.

The patient has developed hypoxic respiratory failure despite appropriate antibiotics and negative cultures, increasing the likelihood of a noninfectious etiology. Her rash is not typical for RMSF, which usually starts as a macular or petechial rash at the ankles and wrists, and spreads centrally to the trunk. Rash is not typically associated with EVALI, and in this case, may represent miliaria caused by her fever.

The mucosal crypts seen on bronchoscopy are nonspecific, likely indicating inflammation from vaping. The BAL otherwise suggests diffuse alveolar hemorrhage (DAH), although sequential BAL aliquots are needed to confirm this diagnosis. DAH is usually caused by pulmonary capillaritis from vasculitis, Goodpasture disease, rheumatic diseases, or diffuse alveolar damage from toxins, infections, rheumatic diseases, or interstitial or organizing pneumonias. Diffuse alveolar damage is the pathologic finding of ARDS, which can be seen in severe cases of many of the conditions discussed, including EVALI, ehrlichiosis, babesiosis, sepsis, and community-acquired pneumonia.⁴

The BAL is most consistent with EVALI, which often shows elevated neutrophils. DAH due to vaping has also been reported.⁵ In patients with EVALI, varied pathologic findings of acute lung injury have been reported, including diffuse alveolar damage.⁶ At this point, laboratory evaluation for rheumatologic diseases and vasculitis should be obtained, and lung biopsy results reviewed. Given her clinical deterioration, treatment with intravenous corticosteroids for presumed EVALI is warranted.

Urine Legionella and Streptococcal pneumoniae antigen tests were negative. The patient was started on methylprednisolone 40 mg intravenously every 8 hours. Further testing included antinuclear antibodies, which was positive at 1:320, with a dense, fine speckled pattern. Perinuclear antineutrophilic cytoplasmic autoantibody, cytoplasmic antineutrophilic cytoplasmic autoantibody, myeloperoxidase, proteinase 3, double-stranded DNA, and glomerular basement membrane IgG were all negative. Transbronchial lung biopsy revealed severe acute lung injury consistent with diffuse alveolar damage. The pulmonary interstitium was mildly expanded by edema, with a moderate number of eosinophilic hyaline membranes. There were no eosinophils or evidence of hemorrhage, granulomas, or giant cells. These changes, within this clinical context, were diagnostic for EVALI.

The patient was intubated for 4 days and completed a course of empiric antibiotics as well as a 10-day course of prednisone. She was discharged on hospital day 17 on 2 L continuous oxygen via nasal cannula. Two days after discharge, she developed worsening dyspnea and chest pain and was readmitted with worsening ground-glass opacities, left upper lobe and right- sided pneumothoraces, and subcutaneous emphysema (Figure 2). She was treated with continuous oxygen to maintain oxygen saturation at 100% and eventually discharged home 3 days later on 3 L continuous oxygen. She attended pulmonary rehabilitation and was weaned off oxygen 2 months later, with marked improvement in aeration of both lungs (Figure 3). She continued to abstain from tobacco and THC products.

The first electronic cigarette (e-cigarette) device was developed in 2003 by a Chinese pharmacist and introduced to the American market in 2007.⁷ E-cigarettes produce an inhalable aerosol by heating a liquid containing a variety of chemicals, nicotine, and flavors, with or without other additives. Originally promoted as a safer nontobacco and cessation device by producers, e-cigarette sales grew at an annual rate of 115% between 2009 and 2012.⁸ E-cigarettes can also be used to deliver THC, the psychoactive component of cannabis.

Since the advent of e-cigarettes, their safety has been a topic of concern. In August 2019, the CDC announced 215 possible cases of severe pulmonary disease associated with the use of e-cigarette products that were reported by 25 state health departments.¹ By February 2020, EVALI had affected more than 2,800 patients hospitalized across the United States.⁹

The presenting symptoms of EVALI are varied and nonspecific. The largest EVALI case series, published by Layden et al in 2020, included 98 patients who had a median duration of 6 days of symptoms prior to presentation.³ Respiratory symptoms occurred in 97% of patients, including shortness of breath, any chest pain, pleuritic chest pain, cough, and hemoptysis.³ Presentations also included a variety of gastrointestinal (77%) and constitutional (100%) symptoms, which most commonly included nausea, vomiting, and fever.³ Additional case series have supported a specific pattern of presentation, most commonly including pleuritic chest pain, nonproductive cough, or shortness of breath occurring days to weeks prior to presentation. Associated fatigue, fever, and tachycardia may be present, as well as nausea, vomiting, diarrhea and abdominal pain, and in some cases, these have preceded respiratory symptoms.^3,10,11

The vital signs and physical examination, laboratory, and imaging results associated with EVALI are also fairly nonspecific. The most common reason for hospitalization in EVALI is hypoxia, which can progress to acute respiratory failure requiring supplemental oxygen or, as in this case, mechanical ventilation. The most common laboratory finding is leukocytosis greater than 11,000/µL, with more than 80% neutrophils and an ESR greater than 30 mm/hr. In the Layden et al case series, 83% of patients had an abnormal CXR. All patients who underwent CT scan of the chest had bilateral ground-glass opacities, often with subpleural sparing.³ A minority of patients were found to have a pneumothorax, generally a late finding.^3,12 Accordingly, the CDC now defines confirmed EVALI as use of e-cigarettes during the 90 days before symptom onset with the presence of pulmonary infiltrates (opacities on CXR or ground-glass opacities on chest CT), negative results on testing for all clinically indicated respiratory infections including respiratory viral panel and influenza PCR, and no alternative plausible diagnoses.¹³

The presumed etiology of EVALI is chemical exposure because no consistent infectious etiology has been identified.⁶ No consistent e-cigarette product, substance, or additive has been identified in all cases, nor has one product been directly linked to EVALI. However, the CDC recently announced that vitamin E acetate in vaping products appears to be associated with EVALI.⁹ In December 2019, Blount et al identified vitamin E acetate in BAL fluid samples from 48 of 51 EVALI patients.¹⁴ Additionally, while no other toxins were identified, 94% of samples contained THC or its metabolites or patients had reported vaping THC within 90 days preceding illness.¹⁴

The most effective treatment strategy for EVALI is still unknown. It is recommended to treat with empiric antibiotics for at least 48 hours (and antivirals during influenza season) if the history is unclear or if the patient is intubated or has severe hypoxemia.² If antibiotic and/or antiviral therapies do not lead to clinical improvement, corticosteroids should be added, as they lead to improved oxygenation in many patients.² Kalininskiy et al recommend initial administration of methylprednisolone 40 mg every 8 hours, with transition to oral prednisone to complete a 2-week course.² Given rates of rehospitalization (2.7%) and death (2%) in EVALI, the CDC advises that patients should be clinically stable for 24 to 48 hours prior to discharge; that follow-up visits should be arranged within 48 hours of discharge; and that cases of EVALI should be reported to the state and local health departments.¹⁵ As seen in the case presented here, with time and continued abstinence from e-cigarette use, the pulmonary effects of EVALI can improve, but long-term outcomes remain unclear. Clinicians must now consider EVALI in patients presenting with respiratory, constitutional, and gastrointestinal complaints when a history of e-cigarette use is present.

• EVALI presents most commonly with a combination of respiratory, gastrointestinal, and constitutional symptoms. including shortness of breath, cough, nausea, vomiting, and fever.
• When considering EVALI, evaluate and treat for potential infectious causes of disease first.
• Corticosteroids are the mainstay of therapy in EVALI, leading to improvement in oxygenation in many patients.
• Most of the reported cases of EVALI have occurred in patients who have vaped THC-containing products.

Potential catastrophic surges in coronavirus disease 2019 (COVID-19) are leading to more patients requiring intensive care unit beds than are available, prompting hospitals to prepare to activate crisis standards of care (CSC).^1,2 These guidelines manage the sobering process of determining which gravely ill patients will have access to limited ventilators, critical care specialists, and other essential hospital personnel. As a member of the CSC triage team at Brigham and Women’s Hospital, Boston, Massachusetts, during the initial surge,¹ I was taught how to follow procedures that assign each patient a priority score that ranged from 1 to 8, with lower scores representing higher priority. Scoring decisions were largely based on current status of organ systems and major medical illnesses (predictive of short-term and longer-term survival, respectively), consistent with the objective of maximizing lives and life-years saved.^1,3-7 Other parameters included improving the priority score of a pregnant woman with a viable fetus and breaking ties in favor of younger patients who had not lived through life’s major stages.^4,7 One issue that elicited sharp disagreement among my colleagues was whether healthcare providers (HCPs; eg, physicians, nurses) should be treated any differently than other individuals.

I believe that HCPs should receive treatment priority during a pandemic because the community has a special obligation to those workers willing to risk serious illness by providing care to potentially infected patients.

The most common argument for prioritizing HCPs has been made on utilitarian grounds: save individuals who can save others.^3,4,6 Such an approach is not founded on the claim that HCPs have higher intrinsic worth, but is based on the instrumental value of HCPs to keep others alive.^4,6 An abiding concern for human life demands systems to ensure individuals with clinical expertise are protected so that they can use their skills to maximize the number of lives saved. A similar case has been made to justify prioritizing HCPs for early access to vaccines during a pandemic.⁵ To underscore these issues, imagine a scenario in which, because of serious illness among HCPs, there were not enough workers with requisite expertise to care for the rest of the community in which a virus was rapidly spreading. Prioritizing HCPs could mitigate this sequence of events by preventing them from becoming infected through early access to vaccinations or promoting their recovery from the illness, which might allow them to return to work caring for others.

Although the utilitarian argument has merit, my primary reason for advocating the prioritization of HCPs reflects a different ethical framework that emphasizes the reciprocal obligations between HCPs and the community. Obligations of physicians have been framed in terms of the commitments made to their self-chosen profession and the putative social contract that has been constructed with the community.^8-10 These principles are well articulated in the American Medical Association’s (AMA’s) Code of Medical Ethics, which states, “Because of their commitment to care for the sick and injured, individual physicians have an obligation to provide urgent medical care during disasters…even in the face of greater than usual risks to their own safety, health, or life.”^10,11 Although the AMA qualified its position by indicating that this obligation is not unconditional, it still formulated exceptions within the overarching structure of professional duty, allowing physicians to “balance immediate benefits to individual patients with ability to care for patients in the future.”^11,12

If one accepts that HCPs have a professional obligation to take care of sick members of the community, even in perilous situations, what, if any, reciprocal obligation does the community have to its HCPs? Reciprocity is a fundamental ethical principle,¹³ serving as a foundation for the Golden Rule, which is a component of almost every ethical tradition.¹⁴ At its core, reciprocity asks us to treat other people as we would want to be treated. It requires endeavoring to take the perspective of others. Within this framework, a strategy for generating a just policy about treatment prioritization is to develop it under the assumption of not knowing which role one would end up playing in a situation. It is critical that if the positions of the individuals involved were reversed, the same rules and obligations would be accepted as fair.¹³ I suggest that if members of the community put themselves in the shoes of HCPs who are willing to risk exposure to a potentially deadly virus, they would acknowledge the legitimate expectation of HCPs to receive prioritized care if they became ill from the infection.

In most cases, reciprocity is not construed as requiring an identical exchange, but a fair one in which, for instance, sacrifice is returned in kind. Obligations can be viewed as debts that we either owe or are entitled to receive.¹⁵ In the current context, reciprocal obligations are derived from the relationship between HCPs and the community in which they serve. HCPs have a special set of obligations to carry out their work with a high degree of professionalism. If circumstances demand they take on substantial risk for their community, the community, in turn, has a special obligation to take care of them.

To highlight this perspective, imagine HCPs who become ill with COVID-19 and make claims for treatment priority despite having been unwilling to work with patients who are sick with COVID-19. We would consider such claims to be unjust because our moral intuition suggests that individuals are owed a debt for the actual risks they have taken, not for the potential ones they have avoided. A corollary of this view is that HCPs who have demonstrated a willingness to risk their lives contracting COVID-19 have a legitimate claim for prioritization.

Acknowledgment of the community’s special obligation to HCPs does not negate competing claims for prioritization, such as trying to save the most lives or accounting for a patient’s pregnancy status and stage of life. Rather, there is a need for CSC guidelines to also include recognition of the special obligations owed HCPs by improving their priority score in the calculus used to triage care. Operationalizing the process would need to be worked out. One possibility would be for HCPs directly caring for patients ill from COVID-19 to have their priority score improve by 2 points, and HCPs directly caring for patients without known disease (but who could still be infectious) to benefit by 1 point. At a minimum, recognition of the risks taken should serve as a tiebreaker in favor of these workers.

If we acknowledge that during a pandemic, the community has a special obligation to HCPs because of the risks they are taking to serve others, by the same logic, this commitment should be extended to any personnel linked to the healthcare system (eg, employees in environmental services) or frontline workers providing essential services (eg, grocery store workers) who are taking similar risks that involve exposure to potentially infected individuals. Conversely, HCPs who are working exclusively from home via telemedicine should not receive treatment priority. An approach that extends treatment prioritization to other relevant workers mitigates concerns raised about prioritizing scarce critical care resources to an already advantaged class of individuals (ie, HCPs) as well as the negative optics of a committee of “deciders” in a hospital who are privileging care to their own members.¹²

Reciprocity, a critical component of our notion of justice, should be incorporated into CSC guidelines. The community’s reciprocity to HCPs and frontline workers needs to be commensurate with the sacrifice made by these groups. Although public demonstrations of gratitude may be much appreciated, such displays alone are not adequate for honoring the community’s special obligations. If, during a pandemic, HCPs or frontline workers deliver direct care or services to members of the community, despite serious risk to their own lives, the community has a reciprocal obligation to these individuals to prioritize their access to critical care. HCPs and frontline workers should be prioritized not because their lives have higher intrinsic worth or solely as a reflection of their instrumental value to the community, but out of recognition of the special debt owed them. This is not an unconditional obligation, but one that should be built into the complex, multifaceted decision-making process^4,6,16 underlying the allocation of scarce medical resources in a pandemic.

The author deeply appreciates the thoughtful comments on the essay from William Snyder, PhD, Melissa Frumin, MD, Brittany McFeeley, BS, Lise Bliss, MBA, and especially Seth Gales, MD, and remains grateful for the guidance and support he received early in his academic career from his first mentors, Carol Gilligan, PhD, and Michael Walzer, PhD.

Potential catastrophic surges in coronavirus disease 2019 (COVID-19) are leading to more patients requiring intensive care unit beds than are available, prompting hospitals to prepare to activate crisis standards of care (CSC).^1,2 These guidelines manage the sobering process of determining which gravely ill patients will have access to limited ventilators, critical care specialists, and other essential hospital personnel. As a member of the CSC triage team at Brigham and Women’s Hospital, Boston, Massachusetts, during the initial surge,¹ I was taught how to follow procedures that assign each patient a priority score that ranged from 1 to 8, with lower scores representing higher priority. Scoring decisions were largely based on current status of organ systems and major medical illnesses (predictive of short-term and longer-term survival, respectively), consistent with the objective of maximizing lives and life-years saved.^1,3-7 Other parameters included improving the priority score of a pregnant woman with a viable fetus and breaking ties in favor of younger patients who had not lived through life’s major stages.^4,7 One issue that elicited sharp disagreement among my colleagues was whether healthcare providers (HCPs; eg, physicians, nurses) should be treated any differently than other individuals.

I believe that HCPs should receive treatment priority during a pandemic because the community has a special obligation to those workers willing to risk serious illness by providing care to potentially infected patients.

The most common argument for prioritizing HCPs has been made on utilitarian grounds: save individuals who can save others.^3,4,6 Such an approach is not founded on the claim that HCPs have higher intrinsic worth, but is based on the instrumental value of HCPs to keep others alive.^4,6 An abiding concern for human life demands systems to ensure individuals with clinical expertise are protected so that they can use their skills to maximize the number of lives saved. A similar case has been made to justify prioritizing HCPs for early access to vaccines during a pandemic.⁵ To underscore these issues, imagine a scenario in which, because of serious illness among HCPs, there were not enough workers with requisite expertise to care for the rest of the community in which a virus was rapidly spreading. Prioritizing HCPs could mitigate this sequence of events by preventing them from becoming infected through early access to vaccinations or promoting their recovery from the illness, which might allow them to return to work caring for others.

Although the utilitarian argument has merit, my primary reason for advocating the prioritization of HCPs reflects a different ethical framework that emphasizes the reciprocal obligations between HCPs and the community. Obligations of physicians have been framed in terms of the commitments made to their self-chosen profession and the putative social contract that has been constructed with the community.^8-10 These principles are well articulated in the American Medical Association’s (AMA’s) Code of Medical Ethics, which states, “Because of their commitment to care for the sick and injured, individual physicians have an obligation to provide urgent medical care during disasters…even in the face of greater than usual risks to their own safety, health, or life.”^10,11 Although the AMA qualified its position by indicating that this obligation is not unconditional, it still formulated exceptions within the overarching structure of professional duty, allowing physicians to “balance immediate benefits to individual patients with ability to care for patients in the future.”^11,12

If one accepts that HCPs have a professional obligation to take care of sick members of the community, even in perilous situations, what, if any, reciprocal obligation does the community have to its HCPs? Reciprocity is a fundamental ethical principle,¹³ serving as a foundation for the Golden Rule, which is a component of almost every ethical tradition.¹⁴ At its core, reciprocity asks us to treat other people as we would want to be treated. It requires endeavoring to take the perspective of others. Within this framework, a strategy for generating a just policy about treatment prioritization is to develop it under the assumption of not knowing which role one would end up playing in a situation. It is critical that if the positions of the individuals involved were reversed, the same rules and obligations would be accepted as fair.¹³ I suggest that if members of the community put themselves in the shoes of HCPs who are willing to risk exposure to a potentially deadly virus, they would acknowledge the legitimate expectation of HCPs to receive prioritized care if they became ill from the infection.

In most cases, reciprocity is not construed as requiring an identical exchange, but a fair one in which, for instance, sacrifice is returned in kind. Obligations can be viewed as debts that we either owe or are entitled to receive.¹⁵ In the current context, reciprocal obligations are derived from the relationship between HCPs and the community in which they serve. HCPs have a special set of obligations to carry out their work with a high degree of professionalism. If circumstances demand they take on substantial risk for their community, the community, in turn, has a special obligation to take care of them.

To highlight this perspective, imagine HCPs who become ill with COVID-19 and make claims for treatment priority despite having been unwilling to work with patients who are sick with COVID-19. We would consider such claims to be unjust because our moral intuition suggests that individuals are owed a debt for the actual risks they have taken, not for the potential ones they have avoided. A corollary of this view is that HCPs who have demonstrated a willingness to risk their lives contracting COVID-19 have a legitimate claim for prioritization.

Acknowledgment of the community’s special obligation to HCPs does not negate competing claims for prioritization, such as trying to save the most lives or accounting for a patient’s pregnancy status and stage of life. Rather, there is a need for CSC guidelines to also include recognition of the special obligations owed HCPs by improving their priority score in the calculus used to triage care. Operationalizing the process would need to be worked out. One possibility would be for HCPs directly caring for patients ill from COVID-19 to have their priority score improve by 2 points, and HCPs directly caring for patients without known disease (but who could still be infectious) to benefit by 1 point. At a minimum, recognition of the risks taken should serve as a tiebreaker in favor of these workers.

If we acknowledge that during a pandemic, the community has a special obligation to HCPs because of the risks they are taking to serve others, by the same logic, this commitment should be extended to any personnel linked to the healthcare system (eg, employees in environmental services) or frontline workers providing essential services (eg, grocery store workers) who are taking similar risks that involve exposure to potentially infected individuals. Conversely, HCPs who are working exclusively from home via telemedicine should not receive treatment priority. An approach that extends treatment prioritization to other relevant workers mitigates concerns raised about prioritizing scarce critical care resources to an already advantaged class of individuals (ie, HCPs) as well as the negative optics of a committee of “deciders” in a hospital who are privileging care to their own members.¹²

Reciprocity, a critical component of our notion of justice, should be incorporated into CSC guidelines. The community’s reciprocity to HCPs and frontline workers needs to be commensurate with the sacrifice made by these groups. Although public demonstrations of gratitude may be much appreciated, such displays alone are not adequate for honoring the community’s special obligations. If, during a pandemic, HCPs or frontline workers deliver direct care or services to members of the community, despite serious risk to their own lives, the community has a reciprocal obligation to these individuals to prioritize their access to critical care. HCPs and frontline workers should be prioritized not because their lives have higher intrinsic worth or solely as a reflection of their instrumental value to the community, but out of recognition of the special debt owed them. This is not an unconditional obligation, but one that should be built into the complex, multifaceted decision-making process^4,6,16 underlying the allocation of scarce medical resources in a pandemic.

The author deeply appreciates the thoughtful comments on the essay from William Snyder, PhD, Melissa Frumin, MD, Brittany McFeeley, BS, Lise Bliss, MBA, and especially Seth Gales, MD, and remains grateful for the guidance and support he received early in his academic career from his first mentors, Carol Gilligan, PhD, and Michael Walzer, PhD.

Potential catastrophic surges in coronavirus disease 2019 (COVID-19) are leading to more patients requiring intensive care unit beds than are available, prompting hospitals to prepare to activate crisis standards of care (CSC).^1,2 These guidelines manage the sobering process of determining which gravely ill patients will have access to limited ventilators, critical care specialists, and other essential hospital personnel. As a member of the CSC triage team at Brigham and Women’s Hospital, Boston, Massachusetts, during the initial surge,¹ I was taught how to follow procedures that assign each patient a priority score that ranged from 1 to 8, with lower scores representing higher priority. Scoring decisions were largely based on current status of organ systems and major medical illnesses (predictive of short-term and longer-term survival, respectively), consistent with the objective of maximizing lives and life-years saved.^1,3-7 Other parameters included improving the priority score of a pregnant woman with a viable fetus and breaking ties in favor of younger patients who had not lived through life’s major stages.^4,7 One issue that elicited sharp disagreement among my colleagues was whether healthcare providers (HCPs; eg, physicians, nurses) should be treated any differently than other individuals.

I believe that HCPs should receive treatment priority during a pandemic because the community has a special obligation to those workers willing to risk serious illness by providing care to potentially infected patients.

The most common argument for prioritizing HCPs has been made on utilitarian grounds: save individuals who can save others.^3,4,6 Such an approach is not founded on the claim that HCPs have higher intrinsic worth, but is based on the instrumental value of HCPs to keep others alive.^4,6 An abiding concern for human life demands systems to ensure individuals with clinical expertise are protected so that they can use their skills to maximize the number of lives saved. A similar case has been made to justify prioritizing HCPs for early access to vaccines during a pandemic.⁵ To underscore these issues, imagine a scenario in which, because of serious illness among HCPs, there were not enough workers with requisite expertise to care for the rest of the community in which a virus was rapidly spreading. Prioritizing HCPs could mitigate this sequence of events by preventing them from becoming infected through early access to vaccinations or promoting their recovery from the illness, which might allow them to return to work caring for others.

Although the utilitarian argument has merit, my primary reason for advocating the prioritization of HCPs reflects a different ethical framework that emphasizes the reciprocal obligations between HCPs and the community. Obligations of physicians have been framed in terms of the commitments made to their self-chosen profession and the putative social contract that has been constructed with the community.^8-10 These principles are well articulated in the American Medical Association’s (AMA’s) Code of Medical Ethics, which states, “Because of their commitment to care for the sick and injured, individual physicians have an obligation to provide urgent medical care during disasters…even in the face of greater than usual risks to their own safety, health, or life.”^10,11 Although the AMA qualified its position by indicating that this obligation is not unconditional, it still formulated exceptions within the overarching structure of professional duty, allowing physicians to “balance immediate benefits to individual patients with ability to care for patients in the future.”^11,12

If one accepts that HCPs have a professional obligation to take care of sick members of the community, even in perilous situations, what, if any, reciprocal obligation does the community have to its HCPs? Reciprocity is a fundamental ethical principle,¹³ serving as a foundation for the Golden Rule, which is a component of almost every ethical tradition.¹⁴ At its core, reciprocity asks us to treat other people as we would want to be treated. It requires endeavoring to take the perspective of others. Within this framework, a strategy for generating a just policy about treatment prioritization is to develop it under the assumption of not knowing which role one would end up playing in a situation. It is critical that if the positions of the individuals involved were reversed, the same rules and obligations would be accepted as fair.¹³ I suggest that if members of the community put themselves in the shoes of HCPs who are willing to risk exposure to a potentially deadly virus, they would acknowledge the legitimate expectation of HCPs to receive prioritized care if they became ill from the infection.

In most cases, reciprocity is not construed as requiring an identical exchange, but a fair one in which, for instance, sacrifice is returned in kind. Obligations can be viewed as debts that we either owe or are entitled to receive.¹⁵ In the current context, reciprocal obligations are derived from the relationship between HCPs and the community in which they serve. HCPs have a special set of obligations to carry out their work with a high degree of professionalism. If circumstances demand they take on substantial risk for their community, the community, in turn, has a special obligation to take care of them.

To highlight this perspective, imagine HCPs who become ill with COVID-19 and make claims for treatment priority despite having been unwilling to work with patients who are sick with COVID-19. We would consider such claims to be unjust because our moral intuition suggests that individuals are owed a debt for the actual risks they have taken, not for the potential ones they have avoided. A corollary of this view is that HCPs who have demonstrated a willingness to risk their lives contracting COVID-19 have a legitimate claim for prioritization.

Acknowledgment of the community’s special obligation to HCPs does not negate competing claims for prioritization, such as trying to save the most lives or accounting for a patient’s pregnancy status and stage of life. Rather, there is a need for CSC guidelines to also include recognition of the special obligations owed HCPs by improving their priority score in the calculus used to triage care. Operationalizing the process would need to be worked out. One possibility would be for HCPs directly caring for patients ill from COVID-19 to have their priority score improve by 2 points, and HCPs directly caring for patients without known disease (but who could still be infectious) to benefit by 1 point. At a minimum, recognition of the risks taken should serve as a tiebreaker in favor of these workers.

If we acknowledge that during a pandemic, the community has a special obligation to HCPs because of the risks they are taking to serve others, by the same logic, this commitment should be extended to any personnel linked to the healthcare system (eg, employees in environmental services) or frontline workers providing essential services (eg, grocery store workers) who are taking similar risks that involve exposure to potentially infected individuals. Conversely, HCPs who are working exclusively from home via telemedicine should not receive treatment priority. An approach that extends treatment prioritization to other relevant workers mitigates concerns raised about prioritizing scarce critical care resources to an already advantaged class of individuals (ie, HCPs) as well as the negative optics of a committee of “deciders” in a hospital who are privileging care to their own members.¹²

Reciprocity, a critical component of our notion of justice, should be incorporated into CSC guidelines. The community’s reciprocity to HCPs and frontline workers needs to be commensurate with the sacrifice made by these groups. Although public demonstrations of gratitude may be much appreciated, such displays alone are not adequate for honoring the community’s special obligations. If, during a pandemic, HCPs or frontline workers deliver direct care or services to members of the community, despite serious risk to their own lives, the community has a reciprocal obligation to these individuals to prioritize their access to critical care. HCPs and frontline workers should be prioritized not because their lives have higher intrinsic worth or solely as a reflection of their instrumental value to the community, but out of recognition of the special debt owed them. This is not an unconditional obligation, but one that should be built into the complex, multifaceted decision-making process^4,6,16 underlying the allocation of scarce medical resources in a pandemic.

The author deeply appreciates the thoughtful comments on the essay from William Snyder, PhD, Melissa Frumin, MD, Brittany McFeeley, BS, Lise Bliss, MBA, and especially Seth Gales, MD, and remains grateful for the guidance and support he received early in his academic career from his first mentors, Carol Gilligan, PhD, and Michael Walzer, PhD.

The impact of the coronavirus disease 2019 (COVID-19) pandemic has been far reaching and devastating. As the pandemic reaches its 1-year mark, there have been more cases and deaths than most of us can comprehend: nearly 28 million cases and 497,000 deaths in the United States¹ and more than 111 million cases and 2.4 million deaths globally.² Frontline healthcare workers (HCWs) have struggled to provide compassionate care in the face of heavy workloads and risks to themselves and their loved ones. Sadly, more than 1,700 US HCWs have died from COVID-19.³ The pandemic has also taken a heavy emotional and psychological toll: HCWs have died by suicide, and others are leaving the profession in which they invested so much and formerly loved. Caring for ill colleagues and dying patients whose family members cannot visit has been particularly difficult. It is, therefore, understandable that some HCWs have called for their prioritization if it becomes necessary to implement crisis standards of care. Although Daffner’s⁴ reciprocity argument—HCWs should receive priority because of the risks that they have voluntarily accepted—has some appeal, it disregards several important considerations. First, it fails to consider the changing dynamics of viral transmission during the pandemic or alternative ways in which the duty of reciprocity may be fulfilled that do not involve prioritizing HCWs over others. Second, this position is both over- and underinclusive in ways that make it difficult to implement. Third, and most important, the inordinate attention to the prioritization of HCWs ignores the issues the pandemic raises regarding racism and inequity.

Although the reciprocity argument has some conceptual merit, there are several different ways that the duty of reciprocity can be fulfilled. One fundamental obligation of government agencies and healthcare systems is providing a safe work environment, including adequate personal protective equipment (PPE) and physical distancing. Before we understood the extent of the pandemic, modes of transmission, and effective preventative measures, hospital transmission was significant. For example, a single-center case series at Zhongan Hospital of Wuhan University, China, from January 1, 2020, to January 28, 2020, found that 29% (40 of 138) of hospitalized patients with COVID-19 were health professionals who were presumed to have been infected by patients.⁵ There were also significant shortages of PPE, and a number of frontline HCWs reported being dismissed for calling attention to unsafe conditions. Although professionals have an obligation to expose themselves to risk, they are not obligated to expose themselves to inordinate risk. Prioritizing HCWs in ventilator triage may have been justified during the initial surge.

The use of surgical masks by all employees and patients has substantially reduced hospital transmission. A study at Duke Health, Raleigh, North Carolina, of HCWs who tested positive for SARS-CoV-2 between March 15, 2020, and June 6, 2020, found 22% of cases were healthcare acquired, 38% were community acquired, and 40% were of unknown acquisition route. Of the healthcare-acquired cases, 30% were thought to be secondary to direct patient care and 70% to exposure to another worker. The cumulative incidence rate of healthcare-acquired infections among workers decreased significantly 1 week after universal masking was implemented on March 31, 2020. The cumulative incidence rates of community-acquired cases and those with unknown acquisition routes continued to mirror incidence rates in the community.⁶ There is substantially less justification for prioritizing HCWs during the current phase of the pandemic; reciprocity does not justify granting HCWs infected via community spread greater priority than non-HCWs similarly infected.

There are other means of reciprocating that do not involve prioritization. COVID-19 has exacted an immense toll on the mental well-being of frontline HCWs. They should be provided robust, comprehensive, and accessible mental health services. Additionally, reciprocity can be expressed by providing alternative housing options for HCWs who are concerned about infecting their family members, especially family members at higher risk of morbidity or mortality from COVID-19. Many HCWs have also died from COVID-19^3; providing life insurance would recognize the sacrifice of HCWs and support their survivors. None of these interventions would require prioritizing HCWs over others.

As Daffner⁴ acknowledges, the category of “healthcare provider” is both over- and underinclusive. Healthcare providers are exposed to variable risks. Some physicians, for example, are no longer involved in direct patient care. It is unclear how triage teams will identify frontline HCWs or validate claims to being a frontline HCW, especially for individuals not employed by the hospital at which they are seeking care. Hence, triage protocols prioritizing healthcare providers are likely to be substantially overinclusive, which raises significant issues of fairness.

Moreover, the category “healthcare provider” is also underinclusive. Many essential, nonclinical hospital employees expose themselves to risk, including custodial and food service staff. As Daffner⁴ recognizes, there are also many other occupations outside of healthcare in which individuals voluntarily expose themselves to risks for the benefit of others, including police officers, firefighters, and clerks in grocery stores. We would add that workers in the food-supply system, transportation, and education face similar risks.⁷ Identifying the types of jobs that should confer priority and validating an individual’s employment also makes implementation difficult and risks injustice.

The COVID-19 pandemic and the murder of Black people by police have brought substantial attention to racism and racial inequities in the United States. We must, however, move from merely acknowledging existing inequities to dismantling structures that perpetuate them. The prioritization of HCWs may further privilege those who already have substantial advantages. This is especially true for physicians. For example, although state and federal laws pose limitations, physicians have historically extended one another professional courtesy by providing free or discounted services. Furthermore, HCWs and their family members are more likely to receive VIP treatment. For instance, when taken to the emergency department, children of physicians are less likely to have medical students and residents involved in their care and more likely to see attending physicians and consultants.⁸

In contrast, other categories of essential workers do not have such advantages. These workers are more likely to be members of marginalized racial and ethnic minority groups, have substantially lower wages, have less access to PPE, and work in more crowded conditions, and are less likely to have paid sick leave compared with HCWs.⁷ These workers are also more likely to lack access to quality healthcare. In fact, many safety net hospitals that provide care to marginalized communities have faced significant financial hardships as a result of the pandemic, and without additional support, some may close. Prioritizing HCWs will likely widen the gaps in health, economic, and social status among these groups.

With respect to allocation criteria, Black, Latinx, and Native American communities have more severe morbidity and mortality from COVID-19 as a result of racism and its interaction with other social determinants of health. Members of marginalized communities of color have a higher likelihood of becoming infected with COVID-19, a higher prevalence of comorbidities, and less access to treatment.⁷ Before her untimely death, Dr Susan Moore, a Black family physician, painfully described the racism to which she was subjected while being treated for COVID-19.⁹ The economic devastation caused by the pandemic, including unemployment, evictions, and food insecurity, compounds the impact of social determinants of health and disproportionately affects minority communities. Purely race- and ethnicity-based approaches to allocation to redress these inequities have potential limitations and obstacles, such as omission of other social determinants of health and legal challenges.⁷ While currently proposed for allocation of medications or vaccines, alternatives include using the Centers for Disease Control and Prevention’s Social Vulnerability Index⁸ or the Area Deprivation Index¹⁰ as a priority criterion. Most importantly, healthcare systems should more broadly demonstrate themselves trustworthy and assure that marginalized communities of color have access to quality healthcare services.

The United States has failed to adequately control the COVID-19 pandemic, and increasing numbers of admissions and staffing shortages have renewed concerns that hospitals will need to implement crisis standards of care. Daffner⁴ argues that healthcare providers should be prioritized in the allocation of critical care based on reciprocity. In the current phase of the pandemic, HCWs are more likely to be infected by one another or in the community than by patients. There are also other ways that hospitals can discharge this duty that do not require prioritizing HCWs over patients. The category of HCW is both over- and underinclusive, and Daffner⁴ has not shown that prioritization can be implemented fairly. Finally, inordinate attention has been paid to this topic. Much more attention should be focused on how to redress the ways in which the pandemic has exacerbated existing racial and ethnic inequities.

The impact of the coronavirus disease 2019 (COVID-19) pandemic has been far reaching and devastating. As the pandemic reaches its 1-year mark, there have been more cases and deaths than most of us can comprehend: nearly 28 million cases and 497,000 deaths in the United States¹ and more than 111 million cases and 2.4 million deaths globally.² Frontline healthcare workers (HCWs) have struggled to provide compassionate care in the face of heavy workloads and risks to themselves and their loved ones. Sadly, more than 1,700 US HCWs have died from COVID-19.³ The pandemic has also taken a heavy emotional and psychological toll: HCWs have died by suicide, and others are leaving the profession in which they invested so much and formerly loved. Caring for ill colleagues and dying patients whose family members cannot visit has been particularly difficult. It is, therefore, understandable that some HCWs have called for their prioritization if it becomes necessary to implement crisis standards of care. Although Daffner’s⁴ reciprocity argument—HCWs should receive priority because of the risks that they have voluntarily accepted—has some appeal, it disregards several important considerations. First, it fails to consider the changing dynamics of viral transmission during the pandemic or alternative ways in which the duty of reciprocity may be fulfilled that do not involve prioritizing HCWs over others. Second, this position is both over- and underinclusive in ways that make it difficult to implement. Third, and most important, the inordinate attention to the prioritization of HCWs ignores the issues the pandemic raises regarding racism and inequity.

Although the reciprocity argument has some conceptual merit, there are several different ways that the duty of reciprocity can be fulfilled. One fundamental obligation of government agencies and healthcare systems is providing a safe work environment, including adequate personal protective equipment (PPE) and physical distancing. Before we understood the extent of the pandemic, modes of transmission, and effective preventative measures, hospital transmission was significant. For example, a single-center case series at Zhongan Hospital of Wuhan University, China, from January 1, 2020, to January 28, 2020, found that 29% (40 of 138) of hospitalized patients with COVID-19 were health professionals who were presumed to have been infected by patients.⁵ There were also significant shortages of PPE, and a number of frontline HCWs reported being dismissed for calling attention to unsafe conditions. Although professionals have an obligation to expose themselves to risk, they are not obligated to expose themselves to inordinate risk. Prioritizing HCWs in ventilator triage may have been justified during the initial surge.

The use of surgical masks by all employees and patients has substantially reduced hospital transmission. A study at Duke Health, Raleigh, North Carolina, of HCWs who tested positive for SARS-CoV-2 between March 15, 2020, and June 6, 2020, found 22% of cases were healthcare acquired, 38% were community acquired, and 40% were of unknown acquisition route. Of the healthcare-acquired cases, 30% were thought to be secondary to direct patient care and 70% to exposure to another worker. The cumulative incidence rate of healthcare-acquired infections among workers decreased significantly 1 week after universal masking was implemented on March 31, 2020. The cumulative incidence rates of community-acquired cases and those with unknown acquisition routes continued to mirror incidence rates in the community.⁶ There is substantially less justification for prioritizing HCWs during the current phase of the pandemic; reciprocity does not justify granting HCWs infected via community spread greater priority than non-HCWs similarly infected.

There are other means of reciprocating that do not involve prioritization. COVID-19 has exacted an immense toll on the mental well-being of frontline HCWs. They should be provided robust, comprehensive, and accessible mental health services. Additionally, reciprocity can be expressed by providing alternative housing options for HCWs who are concerned about infecting their family members, especially family members at higher risk of morbidity or mortality from COVID-19. Many HCWs have also died from COVID-19^3; providing life insurance would recognize the sacrifice of HCWs and support their survivors. None of these interventions would require prioritizing HCWs over others.

As Daffner⁴ acknowledges, the category of “healthcare provider” is both over- and underinclusive. Healthcare providers are exposed to variable risks. Some physicians, for example, are no longer involved in direct patient care. It is unclear how triage teams will identify frontline HCWs or validate claims to being a frontline HCW, especially for individuals not employed by the hospital at which they are seeking care. Hence, triage protocols prioritizing healthcare providers are likely to be substantially overinclusive, which raises significant issues of fairness.

Moreover, the category “healthcare provider” is also underinclusive. Many essential, nonclinical hospital employees expose themselves to risk, including custodial and food service staff. As Daffner⁴ recognizes, there are also many other occupations outside of healthcare in which individuals voluntarily expose themselves to risks for the benefit of others, including police officers, firefighters, and clerks in grocery stores. We would add that workers in the food-supply system, transportation, and education face similar risks.⁷ Identifying the types of jobs that should confer priority and validating an individual’s employment also makes implementation difficult and risks injustice.

The COVID-19 pandemic and the murder of Black people by police have brought substantial attention to racism and racial inequities in the United States. We must, however, move from merely acknowledging existing inequities to dismantling structures that perpetuate them. The prioritization of HCWs may further privilege those who already have substantial advantages. This is especially true for physicians. For example, although state and federal laws pose limitations, physicians have historically extended one another professional courtesy by providing free or discounted services. Furthermore, HCWs and their family members are more likely to receive VIP treatment. For instance, when taken to the emergency department, children of physicians are less likely to have medical students and residents involved in their care and more likely to see attending physicians and consultants.⁸

In contrast, other categories of essential workers do not have such advantages. These workers are more likely to be members of marginalized racial and ethnic minority groups, have substantially lower wages, have less access to PPE, and work in more crowded conditions, and are less likely to have paid sick leave compared with HCWs.⁷ These workers are also more likely to lack access to quality healthcare. In fact, many safety net hospitals that provide care to marginalized communities have faced significant financial hardships as a result of the pandemic, and without additional support, some may close. Prioritizing HCWs will likely widen the gaps in health, economic, and social status among these groups.

With respect to allocation criteria, Black, Latinx, and Native American communities have more severe morbidity and mortality from COVID-19 as a result of racism and its interaction with other social determinants of health. Members of marginalized communities of color have a higher likelihood of becoming infected with COVID-19, a higher prevalence of comorbidities, and less access to treatment.⁷ Before her untimely death, Dr Susan Moore, a Black family physician, painfully described the racism to which she was subjected while being treated for COVID-19.⁹ The economic devastation caused by the pandemic, including unemployment, evictions, and food insecurity, compounds the impact of social determinants of health and disproportionately affects minority communities. Purely race- and ethnicity-based approaches to allocation to redress these inequities have potential limitations and obstacles, such as omission of other social determinants of health and legal challenges.⁷ While currently proposed for allocation of medications or vaccines, alternatives include using the Centers for Disease Control and Prevention’s Social Vulnerability Index⁸ or the Area Deprivation Index¹⁰ as a priority criterion. Most importantly, healthcare systems should more broadly demonstrate themselves trustworthy and assure that marginalized communities of color have access to quality healthcare services.

The United States has failed to adequately control the COVID-19 pandemic, and increasing numbers of admissions and staffing shortages have renewed concerns that hospitals will need to implement crisis standards of care. Daffner⁴ argues that healthcare providers should be prioritized in the allocation of critical care based on reciprocity. In the current phase of the pandemic, HCWs are more likely to be infected by one another or in the community than by patients. There are also other ways that hospitals can discharge this duty that do not require prioritizing HCWs over patients. The category of HCW is both over- and underinclusive, and Daffner⁴ has not shown that prioritization can be implemented fairly. Finally, inordinate attention has been paid to this topic. Much more attention should be focused on how to redress the ways in which the pandemic has exacerbated existing racial and ethnic inequities.

The impact of the coronavirus disease 2019 (COVID-19) pandemic has been far reaching and devastating. As the pandemic reaches its 1-year mark, there have been more cases and deaths than most of us can comprehend: nearly 28 million cases and 497,000 deaths in the United States¹ and more than 111 million cases and 2.4 million deaths globally.² Frontline healthcare workers (HCWs) have struggled to provide compassionate care in the face of heavy workloads and risks to themselves and their loved ones. Sadly, more than 1,700 US HCWs have died from COVID-19.³ The pandemic has also taken a heavy emotional and psychological toll: HCWs have died by suicide, and others are leaving the profession in which they invested so much and formerly loved. Caring for ill colleagues and dying patients whose family members cannot visit has been particularly difficult. It is, therefore, understandable that some HCWs have called for their prioritization if it becomes necessary to implement crisis standards of care. Although Daffner’s⁴ reciprocity argument—HCWs should receive priority because of the risks that they have voluntarily accepted—has some appeal, it disregards several important considerations. First, it fails to consider the changing dynamics of viral transmission during the pandemic or alternative ways in which the duty of reciprocity may be fulfilled that do not involve prioritizing HCWs over others. Second, this position is both over- and underinclusive in ways that make it difficult to implement. Third, and most important, the inordinate attention to the prioritization of HCWs ignores the issues the pandemic raises regarding racism and inequity.

Although the reciprocity argument has some conceptual merit, there are several different ways that the duty of reciprocity can be fulfilled. One fundamental obligation of government agencies and healthcare systems is providing a safe work environment, including adequate personal protective equipment (PPE) and physical distancing. Before we understood the extent of the pandemic, modes of transmission, and effective preventative measures, hospital transmission was significant. For example, a single-center case series at Zhongan Hospital of Wuhan University, China, from January 1, 2020, to January 28, 2020, found that 29% (40 of 138) of hospitalized patients with COVID-19 were health professionals who were presumed to have been infected by patients.⁵ There were also significant shortages of PPE, and a number of frontline HCWs reported being dismissed for calling attention to unsafe conditions. Although professionals have an obligation to expose themselves to risk, they are not obligated to expose themselves to inordinate risk. Prioritizing HCWs in ventilator triage may have been justified during the initial surge.

The use of surgical masks by all employees and patients has substantially reduced hospital transmission. A study at Duke Health, Raleigh, North Carolina, of HCWs who tested positive for SARS-CoV-2 between March 15, 2020, and June 6, 2020, found 22% of cases were healthcare acquired, 38% were community acquired, and 40% were of unknown acquisition route. Of the healthcare-acquired cases, 30% were thought to be secondary to direct patient care and 70% to exposure to another worker. The cumulative incidence rate of healthcare-acquired infections among workers decreased significantly 1 week after universal masking was implemented on March 31, 2020. The cumulative incidence rates of community-acquired cases and those with unknown acquisition routes continued to mirror incidence rates in the community.⁶ There is substantially less justification for prioritizing HCWs during the current phase of the pandemic; reciprocity does not justify granting HCWs infected via community spread greater priority than non-HCWs similarly infected.

There are other means of reciprocating that do not involve prioritization. COVID-19 has exacted an immense toll on the mental well-being of frontline HCWs. They should be provided robust, comprehensive, and accessible mental health services. Additionally, reciprocity can be expressed by providing alternative housing options for HCWs who are concerned about infecting their family members, especially family members at higher risk of morbidity or mortality from COVID-19. Many HCWs have also died from COVID-19^3; providing life insurance would recognize the sacrifice of HCWs and support their survivors. None of these interventions would require prioritizing HCWs over others.

As Daffner⁴ acknowledges, the category of “healthcare provider” is both over- and underinclusive. Healthcare providers are exposed to variable risks. Some physicians, for example, are no longer involved in direct patient care. It is unclear how triage teams will identify frontline HCWs or validate claims to being a frontline HCW, especially for individuals not employed by the hospital at which they are seeking care. Hence, triage protocols prioritizing healthcare providers are likely to be substantially overinclusive, which raises significant issues of fairness.

Moreover, the category “healthcare provider” is also underinclusive. Many essential, nonclinical hospital employees expose themselves to risk, including custodial and food service staff. As Daffner⁴ recognizes, there are also many other occupations outside of healthcare in which individuals voluntarily expose themselves to risks for the benefit of others, including police officers, firefighters, and clerks in grocery stores. We would add that workers in the food-supply system, transportation, and education face similar risks.⁷ Identifying the types of jobs that should confer priority and validating an individual’s employment also makes implementation difficult and risks injustice.

The COVID-19 pandemic and the murder of Black people by police have brought substantial attention to racism and racial inequities in the United States. We must, however, move from merely acknowledging existing inequities to dismantling structures that perpetuate them. The prioritization of HCWs may further privilege those who already have substantial advantages. This is especially true for physicians. For example, although state and federal laws pose limitations, physicians have historically extended one another professional courtesy by providing free or discounted services. Furthermore, HCWs and their family members are more likely to receive VIP treatment. For instance, when taken to the emergency department, children of physicians are less likely to have medical students and residents involved in their care and more likely to see attending physicians and consultants.⁸

In contrast, other categories of essential workers do not have such advantages. These workers are more likely to be members of marginalized racial and ethnic minority groups, have substantially lower wages, have less access to PPE, and work in more crowded conditions, and are less likely to have paid sick leave compared with HCWs.⁷ These workers are also more likely to lack access to quality healthcare. In fact, many safety net hospitals that provide care to marginalized communities have faced significant financial hardships as a result of the pandemic, and without additional support, some may close. Prioritizing HCWs will likely widen the gaps in health, economic, and social status among these groups.

With respect to allocation criteria, Black, Latinx, and Native American communities have more severe morbidity and mortality from COVID-19 as a result of racism and its interaction with other social determinants of health. Members of marginalized communities of color have a higher likelihood of becoming infected with COVID-19, a higher prevalence of comorbidities, and less access to treatment.⁷ Before her untimely death, Dr Susan Moore, a Black family physician, painfully described the racism to which she was subjected while being treated for COVID-19.⁹ The economic devastation caused by the pandemic, including unemployment, evictions, and food insecurity, compounds the impact of social determinants of health and disproportionately affects minority communities. Purely race- and ethnicity-based approaches to allocation to redress these inequities have potential limitations and obstacles, such as omission of other social determinants of health and legal challenges.⁷ While currently proposed for allocation of medications or vaccines, alternatives include using the Centers for Disease Control and Prevention’s Social Vulnerability Index⁸ or the Area Deprivation Index¹⁰ as a priority criterion. Most importantly, healthcare systems should more broadly demonstrate themselves trustworthy and assure that marginalized communities of color have access to quality healthcare services.

The United States has failed to adequately control the COVID-19 pandemic, and increasing numbers of admissions and staffing shortages have renewed concerns that hospitals will need to implement crisis standards of care. Daffner⁴ argues that healthcare providers should be prioritized in the allocation of critical care based on reciprocity. In the current phase of the pandemic, HCWs are more likely to be infected by one another or in the community than by patients. There are also other ways that hospitals can discharge this duty that do not require prioritizing HCWs over patients. The category of HCW is both over- and underinclusive, and Daffner⁴ has not shown that prioritization can be implemented fairly. Finally, inordinate attention has been paid to this topic. Much more attention should be focused on how to redress the ways in which the pandemic has exacerbated existing racial and ethnic inequities.

In their thoughtful response to the thesis that healthcare workers (HCWs) should be prioritized for scarce resources during a pandemic,¹ Antommaria and Unaka offer compelling reasons for opposing this position.² Common ground can be found in our shared recognition that the community has a reciprocal obligation to HCWs because of their willingness to accept the increased risk of being exposed to serious illness in caring for patients. We disagree on the most appropriate way to honor this obligation and whether HCWs currently have a greater risk of infection than others.

Antommaria and Unaka² indicate that “prioritizing HCWs …may have been justified during the initial surge” of coronavirus disease 2019 (COVID-19), when risk was excessive. They suggest that, with universal masking and other measures, infection rates among HCWs now mirror those in the community. However, this assessment is questionable. Personal protective equipment is still inadequate in numerous healthcare settings,^3,4 and many reports, including one by the National Academies, indicate that the threat to HCWs remains higher.⁵ In the absence of certainty, I favor erring on the side of continuing to recognize the special obligation to HCWs. Fortunately, COVID-19 vaccines should further reduce the danger of infection, and my article provides justification for prioritizing HCWs to receive them.

Antommaria and Unaka² seem to support special obligations to HCWs based on reciprocity, but suggest alternatives to critical care prioritization, such as mental health services and life insurance. In my view, mental health care should be universal and not a means of recognizing the sacrifice of HCWs. Providing life insurance for HCWs reflects a tacit acknowledgment of the increased threat they face. However, given governmental delays approving basic COVID-19 relief, it is unlikely that resources will be appropriated for life insurance, which has not occurred since Antommaria et al made this suggestion in 2011.⁶

Although there may be challenges to identifying and verifying frontline HCWs at risk for exposure to COVID-19, there are always gaps between the principles underlying policies and the way they are implemented. For example, according to guidelines from the Centers for Disease Control and Prevention,⁷ the first wave of individuals to receive COVID-19 vaccinations should include “frontline essential workers.” Defining and identifying this group of individuals provoke similar concerns to those raised by Antommaria and Unaka² about my proposal.

I concur that the narrow category of HCWs fails to include nonclinical and other frontline workers who are at a higher risk of being exposed to COVID-19. My article addresses this issue by suggesting the community has a similar set of obligations to these workers.¹ Nonclinical hospital workers are disproportionately non-White and have substantially lower median incomes than the average US wage earner.⁴ Moreover, among HCWs, people of color account for a disproportionate number of COVID-19 cases and deaths.⁴ Inclusion of at-risk nonclinical and other frontline workers in treatment prioritization is consistent with concerns about fairness that animate Antommaria and Unaka’s article.²

The importance of directing attention to the pandemic’s exacerbation of racial and ethnic inequalities, as highlighted by Antommaria and Unaka,² does not preclude also carefully examining whether special obligations are owed to HCWs and frontline workers. Thoughtful discussions about weighty ethical questions do not represent a zero-sum game, and, as in the current case, the issues raised during such deliberations often have much broader implications. Of note, social justice can be framed in terms of reciprocity, and efforts to confront societal inequities can reflect the special obligations owed Black Americans to address our long history of systemic racism.

In summary, fairness includes accounting for reciprocity and the duties resulting from it. Special obligations are owed HCWs and frontline workers until they are no longer at higher risk for infection. Hypothetical offers of life insurance or mental health benefits are inadequate ways to demonstrate reciprocity. The challenge of identifying HCWs and other frontline workers ought not preclude efforts to do so. HCWs and frontline workers should not automatically move to the head of the line to receive limited critical care resources. However, recognition of their willingness to risk serious infection should be included in the multidimensional calculus for triaging critical care.

In their thoughtful response to the thesis that healthcare workers (HCWs) should be prioritized for scarce resources during a pandemic,¹ Antommaria and Unaka offer compelling reasons for opposing this position.² Common ground can be found in our shared recognition that the community has a reciprocal obligation to HCWs because of their willingness to accept the increased risk of being exposed to serious illness in caring for patients. We disagree on the most appropriate way to honor this obligation and whether HCWs currently have a greater risk of infection than others.

Antommaria and Unaka² indicate that “prioritizing HCWs …may have been justified during the initial surge” of coronavirus disease 2019 (COVID-19), when risk was excessive. They suggest that, with universal masking and other measures, infection rates among HCWs now mirror those in the community. However, this assessment is questionable. Personal protective equipment is still inadequate in numerous healthcare settings,^3,4 and many reports, including one by the National Academies, indicate that the threat to HCWs remains higher.⁵ In the absence of certainty, I favor erring on the side of continuing to recognize the special obligation to HCWs. Fortunately, COVID-19 vaccines should further reduce the danger of infection, and my article provides justification for prioritizing HCWs to receive them.

Antommaria and Unaka² seem to support special obligations to HCWs based on reciprocity, but suggest alternatives to critical care prioritization, such as mental health services and life insurance. In my view, mental health care should be universal and not a means of recognizing the sacrifice of HCWs. Providing life insurance for HCWs reflects a tacit acknowledgment of the increased threat they face. However, given governmental delays approving basic COVID-19 relief, it is unlikely that resources will be appropriated for life insurance, which has not occurred since Antommaria et al made this suggestion in 2011.⁶

Although there may be challenges to identifying and verifying frontline HCWs at risk for exposure to COVID-19, there are always gaps between the principles underlying policies and the way they are implemented. For example, according to guidelines from the Centers for Disease Control and Prevention,⁷ the first wave of individuals to receive COVID-19 vaccinations should include “frontline essential workers.” Defining and identifying this group of individuals provoke similar concerns to those raised by Antommaria and Unaka² about my proposal.

I concur that the narrow category of HCWs fails to include nonclinical and other frontline workers who are at a higher risk of being exposed to COVID-19. My article addresses this issue by suggesting the community has a similar set of obligations to these workers.¹ Nonclinical hospital workers are disproportionately non-White and have substantially lower median incomes than the average US wage earner.⁴ Moreover, among HCWs, people of color account for a disproportionate number of COVID-19 cases and deaths.⁴ Inclusion of at-risk nonclinical and other frontline workers in treatment prioritization is consistent with concerns about fairness that animate Antommaria and Unaka’s article.²

The importance of directing attention to the pandemic’s exacerbation of racial and ethnic inequalities, as highlighted by Antommaria and Unaka,² does not preclude also carefully examining whether special obligations are owed to HCWs and frontline workers. Thoughtful discussions about weighty ethical questions do not represent a zero-sum game, and, as in the current case, the issues raised during such deliberations often have much broader implications. Of note, social justice can be framed in terms of reciprocity, and efforts to confront societal inequities can reflect the special obligations owed Black Americans to address our long history of systemic racism.

In summary, fairness includes accounting for reciprocity and the duties resulting from it. Special obligations are owed HCWs and frontline workers until they are no longer at higher risk for infection. Hypothetical offers of life insurance or mental health benefits are inadequate ways to demonstrate reciprocity. The challenge of identifying HCWs and other frontline workers ought not preclude efforts to do so. HCWs and frontline workers should not automatically move to the head of the line to receive limited critical care resources. However, recognition of their willingness to risk serious infection should be included in the multidimensional calculus for triaging critical care.

In their thoughtful response to the thesis that healthcare workers (HCWs) should be prioritized for scarce resources during a pandemic,¹ Antommaria and Unaka offer compelling reasons for opposing this position.² Common ground can be found in our shared recognition that the community has a reciprocal obligation to HCWs because of their willingness to accept the increased risk of being exposed to serious illness in caring for patients. We disagree on the most appropriate way to honor this obligation and whether HCWs currently have a greater risk of infection than others.

Antommaria and Unaka² indicate that “prioritizing HCWs …may have been justified during the initial surge” of coronavirus disease 2019 (COVID-19), when risk was excessive. They suggest that, with universal masking and other measures, infection rates among HCWs now mirror those in the community. However, this assessment is questionable. Personal protective equipment is still inadequate in numerous healthcare settings,^3,4 and many reports, including one by the National Academies, indicate that the threat to HCWs remains higher.⁵ In the absence of certainty, I favor erring on the side of continuing to recognize the special obligation to HCWs. Fortunately, COVID-19 vaccines should further reduce the danger of infection, and my article provides justification for prioritizing HCWs to receive them.

Antommaria and Unaka² seem to support special obligations to HCWs based on reciprocity, but suggest alternatives to critical care prioritization, such as mental health services and life insurance. In my view, mental health care should be universal and not a means of recognizing the sacrifice of HCWs. Providing life insurance for HCWs reflects a tacit acknowledgment of the increased threat they face. However, given governmental delays approving basic COVID-19 relief, it is unlikely that resources will be appropriated for life insurance, which has not occurred since Antommaria et al made this suggestion in 2011.⁶

Although there may be challenges to identifying and verifying frontline HCWs at risk for exposure to COVID-19, there are always gaps between the principles underlying policies and the way they are implemented. For example, according to guidelines from the Centers for Disease Control and Prevention,⁷ the first wave of individuals to receive COVID-19 vaccinations should include “frontline essential workers.” Defining and identifying this group of individuals provoke similar concerns to those raised by Antommaria and Unaka² about my proposal.

I concur that the narrow category of HCWs fails to include nonclinical and other frontline workers who are at a higher risk of being exposed to COVID-19. My article addresses this issue by suggesting the community has a similar set of obligations to these workers.¹ Nonclinical hospital workers are disproportionately non-White and have substantially lower median incomes than the average US wage earner.⁴ Moreover, among HCWs, people of color account for a disproportionate number of COVID-19 cases and deaths.⁴ Inclusion of at-risk nonclinical and other frontline workers in treatment prioritization is consistent with concerns about fairness that animate Antommaria and Unaka’s article.²

The importance of directing attention to the pandemic’s exacerbation of racial and ethnic inequalities, as highlighted by Antommaria and Unaka,² does not preclude also carefully examining whether special obligations are owed to HCWs and frontline workers. Thoughtful discussions about weighty ethical questions do not represent a zero-sum game, and, as in the current case, the issues raised during such deliberations often have much broader implications. Of note, social justice can be framed in terms of reciprocity, and efforts to confront societal inequities can reflect the special obligations owed Black Americans to address our long history of systemic racism.

In summary, fairness includes accounting for reciprocity and the duties resulting from it. Special obligations are owed HCWs and frontline workers until they are no longer at higher risk for infection. Hypothetical offers of life insurance or mental health benefits are inadequate ways to demonstrate reciprocity. The challenge of identifying HCWs and other frontline workers ought not preclude efforts to do so. HCWs and frontline workers should not automatically move to the head of the line to receive limited critical care resources. However, recognition of their willingness to risk serious infection should be included in the multidimensional calculus for triaging critical care.