Hospital Medicine

From Hassenfeld Children’s Hospital at NYU Langone Health, New York, NY (Dr Gallagher), T1D Exchange, Boston, MA (Saketh Rompicherla; Drs Ebekozien, Noor, Odugbesan, and Mungmode; Nicole Rioles, Emma Ospelt), University of Mississippi School of Population Health, Jackson, MS (Dr. Ebekozien), Icahn School of Medicine at Mount Sinai, New York, NY (Drs. Wilkes, O’Malley, and Rapaport), Weill Cornell Medicine, New York, NY (Drs. Antal and Feuer), NYU Long Island School of Medicine, Mineola, NY (Dr. Gabriel), NYU Langone Health, New York, NY (Dr. Golden), Barbara Davis Center, Aurora, CO (Dr. Alonso), Texas Children’s Hospital/Baylor College of Medicine, Houston, TX (Dr. Lyons), Stanford University, Stanford, CA (Dr. Prahalad), Children Mercy Kansas City, MO (Dr. Clements), Indiana University School of Medicine, IN (Dr. Neyman), Rady Children’s Hospital, University of California, San Diego, CA (Dr. Demeterco-Berggren).

Background: Patient outcomes of COVID-19 have improved throughout the pandemic. However, because it is not known whether outcomes of COVID-19 in the type 1 diabetes (T1D) population improved over time, we investigated differences in COVID-19 outcomes for patients with T1D in the United States.

Methods: We analyzed data collected via a registry of patients with T1D and COVID-19 from 56 sites between April 2020 and January 2021. We grouped cases into first surge (April 9, 2020, to July 31, 2020, n = 188) and late surge (August 1, 2020, to January 31, 2021, n = 410), and then compared outcomes between both groups using descriptive statistics and logistic regression models.

Results: Adverse outcomes were more frequent during the first surge, including diabetic ketoacidosis (32% vs 15%, P < .001), severe hypoglycemia (4% vs 1%, P = .04), and hospitalization (52% vs 22%, P < .001). Patients in the first surge were older (28 [SD,18.8] years vs 18.0 [SD, 11.1] years, P < .001), had higher median hemoglobin A1c levels (9.3 [interquartile range {IQR}, 4.0] vs 8.4 (IQR, 2.8), P < .001), and were more likely to use public insurance (107 [57%] vs 154 [38%], P < .001). The odds of hospitalization for adults in the first surge were 5 times higher compared to the late surge (odds ratio, 5.01; 95% CI, 2.11-12.63).

Conclusion: Patients with T1D who presented with COVID-19 during the first surge had a higher proportion of adverse outcomes than those who presented in a later surge.

Keywords: TD1, diabetic ketoacidosis, hypoglycemia.

After the World Health Organization declared the disease caused by the novel coronavirus SARS-CoV-2, COVID-19, a pandemic on March 11, 2020, the Centers for Disease Control and Prevention identified patients with diabetes as high risk for severe illness.^1-7 The case-fatality rate for COVID-19 has significantly improved over the past 2 years. Public health measures, less severe COVID-19 variants, increased access to testing, and new treatments for COVID-19 have contributed to improved outcomes.

The T1D Exchange has previously published findings on COVID-19 outcomes for patients with type 1 diabetes (T1D) using data from the T1D COVID-19 Surveillance Registry.^8-12 Given improved outcomes in COVID-19 in the general population, we sought to determine if outcomes for cases of COVID-19 reported to this registry changed over time.

Methods

This study was coordinated by the T1D Exchange and approved as nonhuman subject research by the Western Institutional Review Board. All participating centers also obtained local institutional review board approval. No identifiable patient information was collected as part of this noninterventional, cross-sectional study.

The T1D Exchange Multi-center COVID-19 Surveillance Study collected data from endocrinology clinics that completed a retrospective chart review and submitted information to T1D Exchange via an online questionnaire for all patients with T1D at their sites who tested positive for COVID-19.^13,14 The questionnaire was administered using the Qualtrics survey platform (www.qualtrics.com version XM) and contained 33 pre-coded and free-text response fields to collect patient and clinical attributes.

Each participating center identified 1 team member for reporting to avoid duplicate case submission. Each submitted case was reviewed for potential errors and incomplete information. The coordinating center verified the number of cases per site for data quality assurance.

Quantitative data were represented as mean (standard deviation) or median (interquartile range). Categorical data were described as the number (percentage) of patients. Summary statistics, including frequency and percentage for categorical variables, were calculated for all patient-related and clinical characteristics. The date August 1, 2021, was selected as the end of the first surge based on a review of national COVID-19 surges.

We used the Fisher’s exact test to assess associations between hospitalization and demographics, HbA1c, diabetes duration, symptoms, and adverse outcomes. In addition, multivariate logistic regression was used to calculate odds ratios (OR). Logistic regression models were used to determine the association between time of surge and hospitalization separately for both the pediatric and adult populations. Each model was adjusted for potential sociodemographic confounders, specifically age, sex, race, insurance, and HbA1c.

All tests were 2-sided, with type 1 error set at 5%. Fisher’s exact test and logistic regression were performed using statistical software R, version 3.6.2 (R Foundation for Statistical Computing).

Results

The characteristics of COVID-19 cases in patients with T1D that were reported early in the pandemic, before August 1, 2020 (first surge), compared with those of cases reported on and after August 1, 2020 (later surges) are shown in Table 1.

Patients with T1D who presented with COVID-19 during the first surge as compared to the later surges were older (mean age 28 [SD, 18.0] years vs 18.8 [SD, 11.1] years; P < .001) and had a longer duration of diabetes (P < .001). The first-surge group also had more patients with >20 years’ diabetes duration (20% vs 9%, P < .001). Obesity, hypertension, and chronic kidney disease were also more commonly reported in first-surge cases (all P < .001).

There was a significant difference in race and ethnicity reported in the first surge vs the later surge cases, with fewer patients identifying as non-Hispanic White (39% vs, 63%, P < .001) and more patients identifying as non-Hispanic Black (29% vs 12%, P < .001). The groups also differed significantly in terms of insurance type, with more people on public insurance in the first-surge group (57% vs 38%, P < .001). In addition, median HbA1c was higher (9.3% vs 8.4%, P < .001) and continuous glucose monitor and insulin pump use were less common (P = .02 and <.001, respectively) in the early surge.

All symptoms and adverse outcomes were reported more often in the first surge, including diabetic ketoacidosis (DKA; 32% vs 15%; P < .001) and severe hypoglycemia (4% vs 1%, P = .04). Hospitalization (52% vs 13%, P < .001) and ICU admission (24% vs 9%, P < .001) were reported more often in the first-surge group.

Regression Analyses

Table 2 shows the results of logistic regression analyses for hospitalization in the pediatric (≤19 years of age) and adult (>19 years of age) groups, along with the odds of hospitalization during the first vs late surge among COVID-positive people with T1D. Adult patients who tested positive in the first surge were about 5 times more likely to be hospitalized than adults who tested positive for infection in the late surge after adjusting for age, insurance type, sex, race, and HbA1c levels. Pediatric patients also had an increased odds for hospitalization during the first surge, but this increase was not statistically significant.

Discussion

Our analysis of COVID-19 cases in patients with T1D reported by diabetes providers across the United States found that adverse outcomes were more prevalent early in the pandemic. There may be a number of reasons for this difference in outcomes between patients who presented in the first surge vs a later surge. First, because testing for COVID-19 was extremely limited and reserved for hospitalized patients early in the pandemic, the first-surge patients with confirmed COVID-19 likely represent a skewed population of higher-acuity patients. This may also explain the relative paucity of cases in younger patients reported early in the pandemic. Second, worse outcomes in the early surge may also have been associated with overwhelmed hospitals in New York City at the start of the outbreak. According to Cummings et al, the abrupt surge of critically ill patients hospitalized with severe acute respiratory distress syndrome initially outpaced their capacity to provide prone-positioning ventilation, which has been expanded since then.¹⁵ While there was very little hypertension, cardiovascular disease, or kidney disease reported in the pediatric groups, there was a higher prevalence of obesity in the pediatric group from the mid-Atlantic region. Obesity has been associated with a worse prognosis for COVID-19 illness in children.¹⁶ Finally, there were 5 deaths reported in this study, all of which were reported during the first surge. Older age and increased rates of cardiovascular disease and chronic kidney disease in the first surge cases likely contributed to worse outcomes for adults in mid-Atlantic region relative to the other regions. Minority race and the use of public insurance, risk factors for more severe outcomes in all regions, were also more common in cases reported from the mid-Atlantic region.

This study has several limitations. First, it is a cross-sectional study that relies upon voluntary provider reports. Second, availability of COVID-19 testing was limited in all regions in spring 2020. Third, different regions of the country experienced subsequent surges at different times within the reported timeframes in this analysis. Fourth, this report time period does not include the impact of the newer COVID-19 variants. Finally, trends in COVID-19 outcomes were affected by the evolution of care that developed throughout 2020.

Conclusion

Adult patients with T1D and COVID-19 who reported during the first surge had about 5 times higher hospitalization odds than those who presented in a later surge.

Corresponding author: Osagie Ebekozien, MD, MPH, 11 Avenue de Lafayette, Boston, MA 02111; oebekozien@t1dexchange.org

Disclosures: Dr Ebekozien reports receiving research grants from Medtronic Diabetes, Eli Lilly, and Dexcom, and receiving honoraria from Medtronic Diabetes.

From Hassenfeld Children’s Hospital at NYU Langone Health, New York, NY (Dr Gallagher), T1D Exchange, Boston, MA (Saketh Rompicherla; Drs Ebekozien, Noor, Odugbesan, and Mungmode; Nicole Rioles, Emma Ospelt), University of Mississippi School of Population Health, Jackson, MS (Dr. Ebekozien), Icahn School of Medicine at Mount Sinai, New York, NY (Drs. Wilkes, O’Malley, and Rapaport), Weill Cornell Medicine, New York, NY (Drs. Antal and Feuer), NYU Long Island School of Medicine, Mineola, NY (Dr. Gabriel), NYU Langone Health, New York, NY (Dr. Golden), Barbara Davis Center, Aurora, CO (Dr. Alonso), Texas Children’s Hospital/Baylor College of Medicine, Houston, TX (Dr. Lyons), Stanford University, Stanford, CA (Dr. Prahalad), Children Mercy Kansas City, MO (Dr. Clements), Indiana University School of Medicine, IN (Dr. Neyman), Rady Children’s Hospital, University of California, San Diego, CA (Dr. Demeterco-Berggren).

Background: Patient outcomes of COVID-19 have improved throughout the pandemic. However, because it is not known whether outcomes of COVID-19 in the type 1 diabetes (T1D) population improved over time, we investigated differences in COVID-19 outcomes for patients with T1D in the United States.

Methods: We analyzed data collected via a registry of patients with T1D and COVID-19 from 56 sites between April 2020 and January 2021. We grouped cases into first surge (April 9, 2020, to July 31, 2020, n = 188) and late surge (August 1, 2020, to January 31, 2021, n = 410), and then compared outcomes between both groups using descriptive statistics and logistic regression models.

Results: Adverse outcomes were more frequent during the first surge, including diabetic ketoacidosis (32% vs 15%, P < .001), severe hypoglycemia (4% vs 1%, P = .04), and hospitalization (52% vs 22%, P < .001). Patients in the first surge were older (28 [SD,18.8] years vs 18.0 [SD, 11.1] years, P < .001), had higher median hemoglobin A1c levels (9.3 [interquartile range {IQR}, 4.0] vs 8.4 (IQR, 2.8), P < .001), and were more likely to use public insurance (107 [57%] vs 154 [38%], P < .001). The odds of hospitalization for adults in the first surge were 5 times higher compared to the late surge (odds ratio, 5.01; 95% CI, 2.11-12.63).

Conclusion: Patients with T1D who presented with COVID-19 during the first surge had a higher proportion of adverse outcomes than those who presented in a later surge.

Keywords: TD1, diabetic ketoacidosis, hypoglycemia.

After the World Health Organization declared the disease caused by the novel coronavirus SARS-CoV-2, COVID-19, a pandemic on March 11, 2020, the Centers for Disease Control and Prevention identified patients with diabetes as high risk for severe illness.^1-7 The case-fatality rate for COVID-19 has significantly improved over the past 2 years. Public health measures, less severe COVID-19 variants, increased access to testing, and new treatments for COVID-19 have contributed to improved outcomes.

The T1D Exchange has previously published findings on COVID-19 outcomes for patients with type 1 diabetes (T1D) using data from the T1D COVID-19 Surveillance Registry.^8-12 Given improved outcomes in COVID-19 in the general population, we sought to determine if outcomes for cases of COVID-19 reported to this registry changed over time.

Methods

This study was coordinated by the T1D Exchange and approved as nonhuman subject research by the Western Institutional Review Board. All participating centers also obtained local institutional review board approval. No identifiable patient information was collected as part of this noninterventional, cross-sectional study.

The T1D Exchange Multi-center COVID-19 Surveillance Study collected data from endocrinology clinics that completed a retrospective chart review and submitted information to T1D Exchange via an online questionnaire for all patients with T1D at their sites who tested positive for COVID-19.^13,14 The questionnaire was administered using the Qualtrics survey platform (www.qualtrics.com version XM) and contained 33 pre-coded and free-text response fields to collect patient and clinical attributes.

Each participating center identified 1 team member for reporting to avoid duplicate case submission. Each submitted case was reviewed for potential errors and incomplete information. The coordinating center verified the number of cases per site for data quality assurance.

Quantitative data were represented as mean (standard deviation) or median (interquartile range). Categorical data were described as the number (percentage) of patients. Summary statistics, including frequency and percentage for categorical variables, were calculated for all patient-related and clinical characteristics. The date August 1, 2021, was selected as the end of the first surge based on a review of national COVID-19 surges.

We used the Fisher’s exact test to assess associations between hospitalization and demographics, HbA1c, diabetes duration, symptoms, and adverse outcomes. In addition, multivariate logistic regression was used to calculate odds ratios (OR). Logistic regression models were used to determine the association between time of surge and hospitalization separately for both the pediatric and adult populations. Each model was adjusted for potential sociodemographic confounders, specifically age, sex, race, insurance, and HbA1c.

All tests were 2-sided, with type 1 error set at 5%. Fisher’s exact test and logistic regression were performed using statistical software R, version 3.6.2 (R Foundation for Statistical Computing).

Results

The characteristics of COVID-19 cases in patients with T1D that were reported early in the pandemic, before August 1, 2020 (first surge), compared with those of cases reported on and after August 1, 2020 (later surges) are shown in Table 1.

Patients with T1D who presented with COVID-19 during the first surge as compared to the later surges were older (mean age 28 [SD, 18.0] years vs 18.8 [SD, 11.1] years; P < .001) and had a longer duration of diabetes (P < .001). The first-surge group also had more patients with >20 years’ diabetes duration (20% vs 9%, P < .001). Obesity, hypertension, and chronic kidney disease were also more commonly reported in first-surge cases (all P < .001).

There was a significant difference in race and ethnicity reported in the first surge vs the later surge cases, with fewer patients identifying as non-Hispanic White (39% vs, 63%, P < .001) and more patients identifying as non-Hispanic Black (29% vs 12%, P < .001). The groups also differed significantly in terms of insurance type, with more people on public insurance in the first-surge group (57% vs 38%, P < .001). In addition, median HbA1c was higher (9.3% vs 8.4%, P < .001) and continuous glucose monitor and insulin pump use were less common (P = .02 and <.001, respectively) in the early surge.

All symptoms and adverse outcomes were reported more often in the first surge, including diabetic ketoacidosis (DKA; 32% vs 15%; P < .001) and severe hypoglycemia (4% vs 1%, P = .04). Hospitalization (52% vs 13%, P < .001) and ICU admission (24% vs 9%, P < .001) were reported more often in the first-surge group.

Regression Analyses

Table 2 shows the results of logistic regression analyses for hospitalization in the pediatric (≤19 years of age) and adult (>19 years of age) groups, along with the odds of hospitalization during the first vs late surge among COVID-positive people with T1D. Adult patients who tested positive in the first surge were about 5 times more likely to be hospitalized than adults who tested positive for infection in the late surge after adjusting for age, insurance type, sex, race, and HbA1c levels. Pediatric patients also had an increased odds for hospitalization during the first surge, but this increase was not statistically significant.

Discussion

Our analysis of COVID-19 cases in patients with T1D reported by diabetes providers across the United States found that adverse outcomes were more prevalent early in the pandemic. There may be a number of reasons for this difference in outcomes between patients who presented in the first surge vs a later surge. First, because testing for COVID-19 was extremely limited and reserved for hospitalized patients early in the pandemic, the first-surge patients with confirmed COVID-19 likely represent a skewed population of higher-acuity patients. This may also explain the relative paucity of cases in younger patients reported early in the pandemic. Second, worse outcomes in the early surge may also have been associated with overwhelmed hospitals in New York City at the start of the outbreak. According to Cummings et al, the abrupt surge of critically ill patients hospitalized with severe acute respiratory distress syndrome initially outpaced their capacity to provide prone-positioning ventilation, which has been expanded since then.¹⁵ While there was very little hypertension, cardiovascular disease, or kidney disease reported in the pediatric groups, there was a higher prevalence of obesity in the pediatric group from the mid-Atlantic region. Obesity has been associated with a worse prognosis for COVID-19 illness in children.¹⁶ Finally, there were 5 deaths reported in this study, all of which were reported during the first surge. Older age and increased rates of cardiovascular disease and chronic kidney disease in the first surge cases likely contributed to worse outcomes for adults in mid-Atlantic region relative to the other regions. Minority race and the use of public insurance, risk factors for more severe outcomes in all regions, were also more common in cases reported from the mid-Atlantic region.

This study has several limitations. First, it is a cross-sectional study that relies upon voluntary provider reports. Second, availability of COVID-19 testing was limited in all regions in spring 2020. Third, different regions of the country experienced subsequent surges at different times within the reported timeframes in this analysis. Fourth, this report time period does not include the impact of the newer COVID-19 variants. Finally, trends in COVID-19 outcomes were affected by the evolution of care that developed throughout 2020.

Conclusion

Adult patients with T1D and COVID-19 who reported during the first surge had about 5 times higher hospitalization odds than those who presented in a later surge.

Corresponding author: Osagie Ebekozien, MD, MPH, 11 Avenue de Lafayette, Boston, MA 02111; oebekozien@t1dexchange.org

Disclosures: Dr Ebekozien reports receiving research grants from Medtronic Diabetes, Eli Lilly, and Dexcom, and receiving honoraria from Medtronic Diabetes.

From Hassenfeld Children’s Hospital at NYU Langone Health, New York, NY (Dr Gallagher), T1D Exchange, Boston, MA (Saketh Rompicherla; Drs Ebekozien, Noor, Odugbesan, and Mungmode; Nicole Rioles, Emma Ospelt), University of Mississippi School of Population Health, Jackson, MS (Dr. Ebekozien), Icahn School of Medicine at Mount Sinai, New York, NY (Drs. Wilkes, O’Malley, and Rapaport), Weill Cornell Medicine, New York, NY (Drs. Antal and Feuer), NYU Long Island School of Medicine, Mineola, NY (Dr. Gabriel), NYU Langone Health, New York, NY (Dr. Golden), Barbara Davis Center, Aurora, CO (Dr. Alonso), Texas Children’s Hospital/Baylor College of Medicine, Houston, TX (Dr. Lyons), Stanford University, Stanford, CA (Dr. Prahalad), Children Mercy Kansas City, MO (Dr. Clements), Indiana University School of Medicine, IN (Dr. Neyman), Rady Children’s Hospital, University of California, San Diego, CA (Dr. Demeterco-Berggren).

Background: Patient outcomes of COVID-19 have improved throughout the pandemic. However, because it is not known whether outcomes of COVID-19 in the type 1 diabetes (T1D) population improved over time, we investigated differences in COVID-19 outcomes for patients with T1D in the United States.

Methods: We analyzed data collected via a registry of patients with T1D and COVID-19 from 56 sites between April 2020 and January 2021. We grouped cases into first surge (April 9, 2020, to July 31, 2020, n = 188) and late surge (August 1, 2020, to January 31, 2021, n = 410), and then compared outcomes between both groups using descriptive statistics and logistic regression models.

Results: Adverse outcomes were more frequent during the first surge, including diabetic ketoacidosis (32% vs 15%, P < .001), severe hypoglycemia (4% vs 1%, P = .04), and hospitalization (52% vs 22%, P < .001). Patients in the first surge were older (28 [SD,18.8] years vs 18.0 [SD, 11.1] years, P < .001), had higher median hemoglobin A1c levels (9.3 [interquartile range {IQR}, 4.0] vs 8.4 (IQR, 2.8), P < .001), and were more likely to use public insurance (107 [57%] vs 154 [38%], P < .001). The odds of hospitalization for adults in the first surge were 5 times higher compared to the late surge (odds ratio, 5.01; 95% CI, 2.11-12.63).

Conclusion: Patients with T1D who presented with COVID-19 during the first surge had a higher proportion of adverse outcomes than those who presented in a later surge.

Keywords: TD1, diabetic ketoacidosis, hypoglycemia.

After the World Health Organization declared the disease caused by the novel coronavirus SARS-CoV-2, COVID-19, a pandemic on March 11, 2020, the Centers for Disease Control and Prevention identified patients with diabetes as high risk for severe illness.^1-7 The case-fatality rate for COVID-19 has significantly improved over the past 2 years. Public health measures, less severe COVID-19 variants, increased access to testing, and new treatments for COVID-19 have contributed to improved outcomes.

The T1D Exchange has previously published findings on COVID-19 outcomes for patients with type 1 diabetes (T1D) using data from the T1D COVID-19 Surveillance Registry.^8-12 Given improved outcomes in COVID-19 in the general population, we sought to determine if outcomes for cases of COVID-19 reported to this registry changed over time.

Methods

This study was coordinated by the T1D Exchange and approved as nonhuman subject research by the Western Institutional Review Board. All participating centers also obtained local institutional review board approval. No identifiable patient information was collected as part of this noninterventional, cross-sectional study.

The T1D Exchange Multi-center COVID-19 Surveillance Study collected data from endocrinology clinics that completed a retrospective chart review and submitted information to T1D Exchange via an online questionnaire for all patients with T1D at their sites who tested positive for COVID-19.^13,14 The questionnaire was administered using the Qualtrics survey platform (www.qualtrics.com version XM) and contained 33 pre-coded and free-text response fields to collect patient and clinical attributes.

Each participating center identified 1 team member for reporting to avoid duplicate case submission. Each submitted case was reviewed for potential errors and incomplete information. The coordinating center verified the number of cases per site for data quality assurance.

Quantitative data were represented as mean (standard deviation) or median (interquartile range). Categorical data were described as the number (percentage) of patients. Summary statistics, including frequency and percentage for categorical variables, were calculated for all patient-related and clinical characteristics. The date August 1, 2021, was selected as the end of the first surge based on a review of national COVID-19 surges.

We used the Fisher’s exact test to assess associations between hospitalization and demographics, HbA1c, diabetes duration, symptoms, and adverse outcomes. In addition, multivariate logistic regression was used to calculate odds ratios (OR). Logistic regression models were used to determine the association between time of surge and hospitalization separately for both the pediatric and adult populations. Each model was adjusted for potential sociodemographic confounders, specifically age, sex, race, insurance, and HbA1c.

All tests were 2-sided, with type 1 error set at 5%. Fisher’s exact test and logistic regression were performed using statistical software R, version 3.6.2 (R Foundation for Statistical Computing).

Results

The characteristics of COVID-19 cases in patients with T1D that were reported early in the pandemic, before August 1, 2020 (first surge), compared with those of cases reported on and after August 1, 2020 (later surges) are shown in Table 1.

Patients with T1D who presented with COVID-19 during the first surge as compared to the later surges were older (mean age 28 [SD, 18.0] years vs 18.8 [SD, 11.1] years; P < .001) and had a longer duration of diabetes (P < .001). The first-surge group also had more patients with >20 years’ diabetes duration (20% vs 9%, P < .001). Obesity, hypertension, and chronic kidney disease were also more commonly reported in first-surge cases (all P < .001).

There was a significant difference in race and ethnicity reported in the first surge vs the later surge cases, with fewer patients identifying as non-Hispanic White (39% vs, 63%, P < .001) and more patients identifying as non-Hispanic Black (29% vs 12%, P < .001). The groups also differed significantly in terms of insurance type, with more people on public insurance in the first-surge group (57% vs 38%, P < .001). In addition, median HbA1c was higher (9.3% vs 8.4%, P < .001) and continuous glucose monitor and insulin pump use were less common (P = .02 and <.001, respectively) in the early surge.

All symptoms and adverse outcomes were reported more often in the first surge, including diabetic ketoacidosis (DKA; 32% vs 15%; P < .001) and severe hypoglycemia (4% vs 1%, P = .04). Hospitalization (52% vs 13%, P < .001) and ICU admission (24% vs 9%, P < .001) were reported more often in the first-surge group.

Regression Analyses

Table 2 shows the results of logistic regression analyses for hospitalization in the pediatric (≤19 years of age) and adult (>19 years of age) groups, along with the odds of hospitalization during the first vs late surge among COVID-positive people with T1D. Adult patients who tested positive in the first surge were about 5 times more likely to be hospitalized than adults who tested positive for infection in the late surge after adjusting for age, insurance type, sex, race, and HbA1c levels. Pediatric patients also had an increased odds for hospitalization during the first surge, but this increase was not statistically significant.

Discussion

Our analysis of COVID-19 cases in patients with T1D reported by diabetes providers across the United States found that adverse outcomes were more prevalent early in the pandemic. There may be a number of reasons for this difference in outcomes between patients who presented in the first surge vs a later surge. First, because testing for COVID-19 was extremely limited and reserved for hospitalized patients early in the pandemic, the first-surge patients with confirmed COVID-19 likely represent a skewed population of higher-acuity patients. This may also explain the relative paucity of cases in younger patients reported early in the pandemic. Second, worse outcomes in the early surge may also have been associated with overwhelmed hospitals in New York City at the start of the outbreak. According to Cummings et al, the abrupt surge of critically ill patients hospitalized with severe acute respiratory distress syndrome initially outpaced their capacity to provide prone-positioning ventilation, which has been expanded since then.¹⁵ While there was very little hypertension, cardiovascular disease, or kidney disease reported in the pediatric groups, there was a higher prevalence of obesity in the pediatric group from the mid-Atlantic region. Obesity has been associated with a worse prognosis for COVID-19 illness in children.¹⁶ Finally, there were 5 deaths reported in this study, all of which were reported during the first surge. Older age and increased rates of cardiovascular disease and chronic kidney disease in the first surge cases likely contributed to worse outcomes for adults in mid-Atlantic region relative to the other regions. Minority race and the use of public insurance, risk factors for more severe outcomes in all regions, were also more common in cases reported from the mid-Atlantic region.

This study has several limitations. First, it is a cross-sectional study that relies upon voluntary provider reports. Second, availability of COVID-19 testing was limited in all regions in spring 2020. Third, different regions of the country experienced subsequent surges at different times within the reported timeframes in this analysis. Fourth, this report time period does not include the impact of the newer COVID-19 variants. Finally, trends in COVID-19 outcomes were affected by the evolution of care that developed throughout 2020.

Conclusion

Adult patients with T1D and COVID-19 who reported during the first surge had about 5 times higher hospitalization odds than those who presented in a later surge.

Corresponding author: Osagie Ebekozien, MD, MPH, 11 Avenue de Lafayette, Boston, MA 02111; oebekozien@t1dexchange.org

Disclosures: Dr Ebekozien reports receiving research grants from Medtronic Diabetes, Eli Lilly, and Dexcom, and receiving honoraria from Medtronic Diabetes.

From the Department of Emergency Medicine, Santa Croce e Carle Hospital, Cuneo, Italy (Drs. Abram, Tosello, Emanuele Bernardi, Allione, Cavalot, Dutto, Corsini, Martini, Sciolla, Sara Bernardi, and Lauria). From the School of Emergency Medicine, University of Turin, Turin, Italy (Drs. Paglietta and Giamello).

Objective: This retrospective and prospective cohort study was designed to describe the characteristics, treatments, and outcomes of patients with SARS-CoV-2 infection (COVID-19) admitted to subintensive care units (SICU) and to identify the variables associated with outcomes. SICUs have been extremely stressed during the pandemic, but most data regarding critically ill COVID-19 patients come from intensive care units (ICUs). Studies about COVID-19 patients in SICUs are lacking.

Setting and participants: The study included 88 COVID-19 patients admitted to our SICU in Cuneo, Italy, between March and May 2020.

Measurements: Clinical and ventilatory data were collected, and patients were divided by outcome. Multivariable logistic regression analysis examined the variables associated with negative outcomes (transfer to the ICU, palliation, or death in a SICU).

Results: A total of 60 patients (68%) had a positive outcome, and 28 patients (32%) had a negative outcome; 69 patients (78%) underwent continuous positive airway pressure (CPAP). Pronation (n = 37 [42%]) had been more frequently adopted in patients who had a positive outcome vs a negative outcome (n = 30 [50%] vs n = 7 [25%]; P = .048), and the median (interquartile range) Pao₂/Fio₂ ratio after 6 hours of prone positioning was lower in patients who had a negative outcome vs a positive outcome (144 [140-168] vs 249 [195-268], P = .006). Independent predictors of a negative outcome were diabetes (odds ratio [OR], 8.22; 95% CI, 1.50-44.70; P = .015), higher D-dimer (OR, 1.28; 95% CI, 1.04-1.57; P = .019), higher lactate dehydrogenase level (OR, 1.003; 95% CI, 1.000-1.006; P = .039), and lower lymphocytes count (OR, 0.996; 95% CI, 0.993-0.999; P = .004).

Conclusion: SICUs have a fundamental role in the treatment of critically ill patients with COVID-19, who require long-term CPAP and pronation cycles. Diabetes, lymphopenia, and high D-dimer and LDH levels are associated with negative outcomes.

Keywords: emergency medicine, noninvasive ventilation, prone position, continuous positive airway pressure.

The COVID-19 pandemic has led to large increases in hospital admissions. Subintensive care units (SICUs) are among the wards most under pressure worldwide,¹ dealing with the increased number of critically ill patients who need noninvasive ventilation, as well as serving as the best alternative to overfilled intensive care units (ICUs). In Italy, SICUs are playing a fundamental role in the management of COVID-19 patients, providing early treatment of respiratory failure by continuous noninvasive ventilation in order to reduce the need for intubation.^2-5 Nevertheless, the great majority of available data about critically ill COVID-19 patients comes from ICUs. Full studies about outcomes of patients in SICUs are lacking and need to be conducted.

We sought to evaluate the characteristics and outcomes of patients admitted to our SICU for COVID-19 to describe the treatments they needed and their impact on prognosis, and to identify the variables associated with patient outcomes.

Methods

Study Design

This cohort study used data from patients who were admitted in the very first weeks of the pandemic. Data were collected retrospectively as well as prospectively, since the ethical committee approved our project. The quality and quantity of data in the 2 groups were comparable.

Data were collected from electronic and written medical records gathered during the patient’s entire stay in our SICU. Data were entered in a database with limited and controlled access. This study complied with the Declaration of Helsinki and was approved by the local ethics committees (ID: MEDURG10).

Study Population

We studied 88 consecutive patients admitted to the SICU of the Santa Croce e Carle Teaching Hospital, Cuneo, Italy, for COVID-19, from March 8 to May 1, 2020. The diagnosis was based on acute respiratory failure associated with SARS-CoV-2 RNA detection on nasopharyngeal swab or tracheal aspirate and/or typical COVID-19 features on a pulmonary computed tomography (CT) scan.⁶ Exclusion criteria were age younger than 18 years and patient denial of permission to use their data for research purposes (the great majority of patients could actively give consent; for patients who were too sick to do so, family members were asked whether they were aware of any reason why the patient would deny consent).

 

 

Clinical Data

The past medical history and recent symptoms description were obtained by manually reviewing medical records. Epidemiological exposure was defined as contact with SARS-CoV-2–positive people or staying in an epidemic outbreak area. Initial vital parameters, venous blood tests, arterial blood gas analysis, chest x-ray, as well as the result of the nasopharyngeal swab were gathered from the emergency department (ED) examination. (Additional swabs could be requested when the first one was negative but clinical suspicion for COVID-19 was high.) Upon admission to the SICU, a standardized panel of blood tests was performed, which was repeated the next day and then every 48 hours. Arterial blood gas analysis was performed when clinically indicated, at least twice a day, or following a scheduled time in patients undergoing pronation. Charlson Comorbidity Index⁷ and MuLBSTA score⁸ were calculated based on the collected data.

Imaging

Chest ultrasonography was performed in the ED at the time of hospitalization and once a day in the SICU. Pulmonary high-resolution computed tomography (HRCT) was performed when clinically indicated or when the results of nasopharyngeal swabs and/or x-ray results were discordant with COVID-19 clinical suspicion. Contrast CT was performed when pulmonary embolism was suspected.

Medical Therapy

Hydroxychloroquine, antiviral agents, tocilizumab, and ruxolitinib were used in the early phase of the pandemic, then were dismissed after evidence of no efficacy.^9-11 Steroids and low-molecular-weight heparin were used afterward. Enoxaparin was used at the standard prophylactic dosage, and 70% of the anticoagulant dosage was also adopted in patients with moderate-to-severe COVID-19 and D-dimer values >3 times the normal value.^12-14 Antibiotics were given when a bacterial superinfection was suspected.

Oxygen and Ventilatory Therapy

Oxygen support or noninvasive ventilation were started based on patients’ respiratory efficacy, estimated by respiratory rate and the ratio of partial pressure of arterial oxygen and fraction of inspired oxygen (P/F ratio).^15,16 Oxygen support was delivered through nasal cannula, Venturi mask, or reservoir mask. Noninvasive ventilation was performed by continuous positive airway pressure (CPAP) when the P/F ratio was <250 or the respiratory rate was >25 breaths per minute, using the helmet interface.^5,17 Prone positioning during CPAP^18-20 was adopted in patients meeting the acute respiratory distress syndrome (ARDS) criteria²¹ and having persistence of respiratory distress and P/F <300 after a 1-hour trial of CPAP.

The prone position was maintained based on patient tolerance. P/F ratio was measured before pronation (T0), after 1 hour of prone position (T1), before resupination (T2), and 6 hours after resupination (T3). With the same timing, the patient was asked to rate their comfort in each position, from 0 (lack of comfort) to 10 (optimal comfort). Delta P/F was defined as the difference between P/F at T3 and basal P/F at T0.

Outcomes

Positive outcomes were defined as patient discharge from the SICU or transfer to a lower-intensity care ward for treatment continuation. Negative outcomes were defined as need for transfer to the ICU, transfer to another ward for palliation, or death in the SICU.

Statistical Analysis

Continuous data are reported as median and interquartile range (IQR); normal distribution of variables was tested using the Shapiro-Wilk test. Categorical variables were reported as absolute number and percentage. The Mann-Whitney test was used to compare continuous variables between groups, and chi-square test with continuity correction was used for categorical variables. The variables that were most significantly associated with a negative outcome on the univariate analysis were included in a stepwise logistic regression analysis, in order to identify independent predictors of patient outcome. Statistical analysis was performed using JASP (JASP Team) software.

 

 

Results

Study Population

Of the 88 patients included in the study, 70% were male; the median age was 66 years (IQR, 60-77). In most patients, the diagnosis of COVID-19 was derived from a positive SARS-CoV-2 nasopharyngeal swab. Six patients, however, maintained a negative swab at all determinations but had clinical and imaging features strongly suggesting COVID-19. No patients met the exclusion criteria. Most patients came from the ED (n = 58 [66%]) or general wards (n = 22 [25%]), while few were transferred from the ICU (n = 8 [9%]). The median length of stay in the SICU was 4 days (IQR, 2-7). An epidemiological link to affected persons or a known virus exposure was identifiable in 37 patients (42%).

Clinical, Laboratory, and Imaging Data

The clinical and anthropometric characteristics of patients are shown in Table 1. Hypertension and smoking habits were prevalent in our population, and the median Charlson Comorbidity Index was 3. Most patients experienced fever, dyspnea, and cough during the days before hospitalization.

Laboratory data showed a marked inflammatory milieu in all studied patients, both at baseline and after 24 and 72 hours. Lymphopenia was observed, along with a significant increase of lactate dehydrogenase (LDH), C-reactive protein (CPR), and D-dimer, and a mild increase of procalcitonin. N-terminal pro-brain natriuretic peptide (NT-proBNP) values were also increased, with normal troponin I values (Table 2).

Medical Therapy

Most patients (89%) received hydroxychloroquine, whereas steroids were used in one-third of the population (36%). Immunomodulators (tocilizumab and ruxolitinib) were restricted to 12 patients (14%). Empirical antiviral therapy was introduced in the first 41 patients (47%). Enoxaparin was the default agent for thromboembolism prophylaxis, and 6 patients (7%) received 70% of the anticoagulating dose.

Oxygen and Ventilatory Therapy

Basal median P/F ratio was 253 (IQR, 218-291), and respiratory rate at triage was 20 breaths/min (IQR, 16-28), underlining a moderate-to-severe respiratory insufficiency at presentation. A total of 69 patients (78%) underwent CPAP, with a median positive end-expiratory pressure (PEEP) of 10.0 cm H₂O (IQR, 7.5-10.0) and fraction of inspired oxygen (Fio₂) of 0.40 (IQR, 0.40-0.50). In 37 patients (42%) who received ongoing CPAP, prone positioning was adopted. In this subgroup, respiratory rate was not significantly different from baseline to resupination (24 vs 25 breaths/min). The median P/F improved from 197 (IQR, 154-236) at baseline to 217 (IQR, 180-262) after pronation (the duration of the prone position was variable, depending on patients’ tolerance: 1 to 6 hours or every pronation cycle). The median delta P/F ratio was 39.4 (IQR, –17.0 to 78.0).

Outcomes

A total of 28 patients (32%) had a negative outcome in the SICU: 8 patients (9%) died, having no clinical indication for higher-intensity care; 6 patients (7%) were transferred to general wards for palliation; and 14 patients (16%) needed an upgrade of cure intensity and were transferred to the ICU. Of these 14 patients, 9 died in the ICU. The total in-hospital mortality of COVID-19 patients, including patients transferred from the SICU to general wards in fair condition, was 27% (n = 24). Clinical, laboratory, and therapeutic characteristics between the 2 groups are shown in Table 4.

Patients who had a negative outcome were significantly older and had more comorbidities, as suggested by a significantly higher prevalence of diabetes and higher Charlson Comorbidity scores (reflecting the mortality risk based on age and comorbidities). The median MuLBSTA score, which estimates the 90-day mortality risk from viral pneumonia, was also higher in patients who had a negative outcome (9.33%). Symptom occurrence was not different in patients with a negative outcome (apart from cough, which was less frequent), but these patients underwent hospitalization earlier—since the appearance of their first COVID-19 symptoms—compared to patients who had a positive outcome. No difference was found in antihypertensive therapy with angiotensin-converting enzyme inhibitors or angiotensin-receptor blockers among outcome groups.

More pronounced laboratory abnormalities were found in patients who had a negative outcome, compared to patients who had a positive outcome: lower lymphocytes and higher C-reactive protein (CRP), procalcitonin, D-dimer, LDH, and NT-proBNP. We found no differences in the radiological distribution of pulmonary involvement in patients who had negative or positive outcomes, nor in the adopted medical treatment.

Data showed no difference in CPAP implementation in the 2 groups. However, prone positioning had been more frequently adopted in the group of patients who had a positive outcome, compared with patients who had a negative outcome. No differences of basal P/F were found in patients who had a negative or positive outcome, but the median P/F after 6 hours of prone position was significantly lower in patients who had a negative outcome. The delta P/F ratio did not differ in the 2 groups of patients.

Multivariate Analysis

A logistic regression model was created, including the variables significantly associated with outcomes in the univariate analysis (age, sex, history of diabetes, lymphocytes, CRP, procalcitonin, LDH, NT-proBNP, and D-dimer). In the multivariate analysis, independent predictors of a negative outcome were history of diabetes (odds ratio [OR], 8.22; 95% CI, 1.50-44.70; P =.015), high D-dimer values (OR, 1.28; CI, 1.04-1.57; P = .019), high LDH values (OR, 1.003; CI, 1.000-1.006; P = .039), and low lymphocytes count (OR, 0.996; CI, 0.993-0.999; P = .004).

Discussion

Role of Subintensive Units and Mortality

The novelty of our report is its attempt to investigate the specific group of COVID-19 patients admitted to a SICU. In Italy, SICUs receive acutely ill, spontaneously breathing patients who need (invasive) hemodynamic monitoring, vasoactive medication, renal replacement therapy, chest- tube placement, thrombolysis, and respiratory noninvasive support. The nurse-to-patient ratio is higher than for general wards (usually 1 nurse to every 4 or 5 patients), though lower than for ICUs. In northern Italy, a great number of COVID-19 patients have required this kind of high-intensity care during the pandemic: Noninvasive ventilation support had to be maintained for several days, pronation maneuvers required a high number of people 2 or 3 times a day, and strict monitoring had to be assured. The SICU setting allows patients to buy time as a bridge to progressive reduction of pulmonary involvement, sometimes preventing the need for intubation.

The high prevalence of negative outcomes in the SICU underlines the complexity of COVID-19 patients in this setting. In fact, published data about mortality for patients with severe COVID-19 pneumonia are similar to ours.^22,23

Clinical, Laboratory, and Imaging Data

Our analysis confirmed a high rate of comorbidities in COVID-19 patients²⁴ and their prognostic role with age.^25,26 A marked inflammatory milieu was a negative prognostic indicator, and associated concomitant bacterial superinfection could have led to a worse prognosis (procalcitonin was associated with negative outcomes).²⁷ The cardiovascular system was nevertheless stressed, as suggested by higher values of NT-proBNP in patients with negative outcomes, which could reflect sepsis-related systemic involvement.²⁸

It is known that the pulmonary damage caused by SARS-CoV-2 has a dynamic radiological and clinical course, with early areas of subsegmental consolidation, and bilateral ground-glass opacities predominating later in the course of the disease.²⁹ This could explain why in our population we found no specific radiological pattern leading to a worse outcome.

Medical Therapy

No specific pharmacological therapy was found to be associated with a positive outcome in our study, just like antiviral and immunomodulator therapies failed to demonstrate effectiveness in subsequent pandemic surges. The low statistical power of our study did not allow us to give insight into the effectiveness of steroids and heparin at any dosage.

PEEP Support and Prone Positioning

Continuous positive airway pressure was initiated in the majority of patients and maintained for several days. This was an absolute novelty, because we rarely had to keep patients in helmets for long. This was feasible thanks to the SICU’s high nurse-to-patient ratio and the possibility of providing monitored sedation. Patients who could no longer tolerate CPAP helmets or did not improve with CPAP support were evaluated with anesthetists for programming further management. No initial data on respiratory rate, level of hypoxemia, or oxygen support need (level of PEEP and Fio₂) could discriminate between outcomes.

Prone positioning during CPAP was implemented in 42% of our study population: P/F ratio amelioration after prone positioning was highly variable, ranging from very good P/F ratio improvements to few responses or no response. No significantly greater delta P/F ratio was seen after the first prone positioning cycle in patients who had a positive outcome, probably due to the small size of our population, but we observed a clear positive trend. Interestingly, patients showing a negative outcome had a lower percentage of long-term responses to prone positioning: 6 hours after resupination, they lost the benefit of prone positioning in terms of P/F ratio amelioration. Similarly, a greater number of patients tolerating prone positioning had a positive outcome. These data give insight on the possible benefits of prone positioning in a noninvasively supported cohort of patients, which has been mentioned in previous studies.^30,31

Outcomes and Variables Associated With Negative Outcomes

After correction for age and sex, we found in multiple regression analysis that higher D-dimer and LDH values, lymphopenia, and history of diabetes were independently associated with a worse outcome. Although our results had low statistical significance, we consider the trend of the obtained odds ratios important from a clinical point of view. These results could lead to greater attention being placed on COVID-19 patients who present with these characteristics upon their arrival to the ED because they have increased risk of death or intensive care need. Clinicians should consider SICU admission for these patients in order to guarantee closer monitoring and possibly more aggressive ventilatory treatments, earlier pronation, or earlier transfer to the ICU.

Limitations

The major limitation to our study is undoubtedly its statistical power, due to its relatively low patient population. Particularly, the small number of patients who underwent pronation did not allow speculation about the efficacy of this technique, although preliminary data seem promising. However, ours is among the first studies regarding patients with COVID-19 admitted to a SICU, and these preliminary data truthfully describe the Italian, and perhaps international, experience with the first surge of the pandemic.

Conclusions

Our data highlight the primary role of the SICU in COVID-19 in adequately treating critically ill patients who have high care needs different from intubation, and who require noninvasive ventilation for prolonged times as well as frequent pronation cycles. This setting of care may represent a valid, reliable, and effective option for critically ill respiratory patients. History of diabetes, lymphopenia, and high D-dimer and LDH values are independently associated with negative outcomes, and patients presenting with these characteristics should be strictly monitored.

Acknowledgments: The authors thank the Informatica System S.R.L., as well as Allessando Mendolia for the pro bono creation of the ISCovidCollect data collecting app.

Corresponding author: Sara Abram, MD, via Coppino, 12100 Cuneo, Italy; sara.abram84@gmail.com.

Disclosures: None.

From the Department of Emergency Medicine, Santa Croce e Carle Hospital, Cuneo, Italy (Drs. Abram, Tosello, Emanuele Bernardi, Allione, Cavalot, Dutto, Corsini, Martini, Sciolla, Sara Bernardi, and Lauria). From the School of Emergency Medicine, University of Turin, Turin, Italy (Drs. Paglietta and Giamello).

Objective: This retrospective and prospective cohort study was designed to describe the characteristics, treatments, and outcomes of patients with SARS-CoV-2 infection (COVID-19) admitted to subintensive care units (SICU) and to identify the variables associated with outcomes. SICUs have been extremely stressed during the pandemic, but most data regarding critically ill COVID-19 patients come from intensive care units (ICUs). Studies about COVID-19 patients in SICUs are lacking.

Setting and participants: The study included 88 COVID-19 patients admitted to our SICU in Cuneo, Italy, between March and May 2020.

Measurements: Clinical and ventilatory data were collected, and patients were divided by outcome. Multivariable logistic regression analysis examined the variables associated with negative outcomes (transfer to the ICU, palliation, or death in a SICU).

Results: A total of 60 patients (68%) had a positive outcome, and 28 patients (32%) had a negative outcome; 69 patients (78%) underwent continuous positive airway pressure (CPAP). Pronation (n = 37 [42%]) had been more frequently adopted in patients who had a positive outcome vs a negative outcome (n = 30 [50%] vs n = 7 [25%]; P = .048), and the median (interquartile range) Pao₂/Fio₂ ratio after 6 hours of prone positioning was lower in patients who had a negative outcome vs a positive outcome (144 [140-168] vs 249 [195-268], P = .006). Independent predictors of a negative outcome were diabetes (odds ratio [OR], 8.22; 95% CI, 1.50-44.70; P = .015), higher D-dimer (OR, 1.28; 95% CI, 1.04-1.57; P = .019), higher lactate dehydrogenase level (OR, 1.003; 95% CI, 1.000-1.006; P = .039), and lower lymphocytes count (OR, 0.996; 95% CI, 0.993-0.999; P = .004).

Conclusion: SICUs have a fundamental role in the treatment of critically ill patients with COVID-19, who require long-term CPAP and pronation cycles. Diabetes, lymphopenia, and high D-dimer and LDH levels are associated with negative outcomes.

Keywords: emergency medicine, noninvasive ventilation, prone position, continuous positive airway pressure.

The COVID-19 pandemic has led to large increases in hospital admissions. Subintensive care units (SICUs) are among the wards most under pressure worldwide,¹ dealing with the increased number of critically ill patients who need noninvasive ventilation, as well as serving as the best alternative to overfilled intensive care units (ICUs). In Italy, SICUs are playing a fundamental role in the management of COVID-19 patients, providing early treatment of respiratory failure by continuous noninvasive ventilation in order to reduce the need for intubation.^2-5 Nevertheless, the great majority of available data about critically ill COVID-19 patients comes from ICUs. Full studies about outcomes of patients in SICUs are lacking and need to be conducted.

We sought to evaluate the characteristics and outcomes of patients admitted to our SICU for COVID-19 to describe the treatments they needed and their impact on prognosis, and to identify the variables associated with patient outcomes.

Methods

Study Design

This cohort study used data from patients who were admitted in the very first weeks of the pandemic. Data were collected retrospectively as well as prospectively, since the ethical committee approved our project. The quality and quantity of data in the 2 groups were comparable.

Data were collected from electronic and written medical records gathered during the patient’s entire stay in our SICU. Data were entered in a database with limited and controlled access. This study complied with the Declaration of Helsinki and was approved by the local ethics committees (ID: MEDURG10).

Study Population

We studied 88 consecutive patients admitted to the SICU of the Santa Croce e Carle Teaching Hospital, Cuneo, Italy, for COVID-19, from March 8 to May 1, 2020. The diagnosis was based on acute respiratory failure associated with SARS-CoV-2 RNA detection on nasopharyngeal swab or tracheal aspirate and/or typical COVID-19 features on a pulmonary computed tomography (CT) scan.⁶ Exclusion criteria were age younger than 18 years and patient denial of permission to use their data for research purposes (the great majority of patients could actively give consent; for patients who were too sick to do so, family members were asked whether they were aware of any reason why the patient would deny consent).

 

 

Clinical Data

The past medical history and recent symptoms description were obtained by manually reviewing medical records. Epidemiological exposure was defined as contact with SARS-CoV-2–positive people or staying in an epidemic outbreak area. Initial vital parameters, venous blood tests, arterial blood gas analysis, chest x-ray, as well as the result of the nasopharyngeal swab were gathered from the emergency department (ED) examination. (Additional swabs could be requested when the first one was negative but clinical suspicion for COVID-19 was high.) Upon admission to the SICU, a standardized panel of blood tests was performed, which was repeated the next day and then every 48 hours. Arterial blood gas analysis was performed when clinically indicated, at least twice a day, or following a scheduled time in patients undergoing pronation. Charlson Comorbidity Index⁷ and MuLBSTA score⁸ were calculated based on the collected data.

Imaging

Chest ultrasonography was performed in the ED at the time of hospitalization and once a day in the SICU. Pulmonary high-resolution computed tomography (HRCT) was performed when clinically indicated or when the results of nasopharyngeal swabs and/or x-ray results were discordant with COVID-19 clinical suspicion. Contrast CT was performed when pulmonary embolism was suspected.

Medical Therapy

Hydroxychloroquine, antiviral agents, tocilizumab, and ruxolitinib were used in the early phase of the pandemic, then were dismissed after evidence of no efficacy.^9-11 Steroids and low-molecular-weight heparin were used afterward. Enoxaparin was used at the standard prophylactic dosage, and 70% of the anticoagulant dosage was also adopted in patients with moderate-to-severe COVID-19 and D-dimer values >3 times the normal value.^12-14 Antibiotics were given when a bacterial superinfection was suspected.

Oxygen and Ventilatory Therapy

Oxygen support or noninvasive ventilation were started based on patients’ respiratory efficacy, estimated by respiratory rate and the ratio of partial pressure of arterial oxygen and fraction of inspired oxygen (P/F ratio).^15,16 Oxygen support was delivered through nasal cannula, Venturi mask, or reservoir mask. Noninvasive ventilation was performed by continuous positive airway pressure (CPAP) when the P/F ratio was <250 or the respiratory rate was >25 breaths per minute, using the helmet interface.^5,17 Prone positioning during CPAP^18-20 was adopted in patients meeting the acute respiratory distress syndrome (ARDS) criteria²¹ and having persistence of respiratory distress and P/F <300 after a 1-hour trial of CPAP.

The prone position was maintained based on patient tolerance. P/F ratio was measured before pronation (T0), after 1 hour of prone position (T1), before resupination (T2), and 6 hours after resupination (T3). With the same timing, the patient was asked to rate their comfort in each position, from 0 (lack of comfort) to 10 (optimal comfort). Delta P/F was defined as the difference between P/F at T3 and basal P/F at T0.

Outcomes

Positive outcomes were defined as patient discharge from the SICU or transfer to a lower-intensity care ward for treatment continuation. Negative outcomes were defined as need for transfer to the ICU, transfer to another ward for palliation, or death in the SICU.

Statistical Analysis

Continuous data are reported as median and interquartile range (IQR); normal distribution of variables was tested using the Shapiro-Wilk test. Categorical variables were reported as absolute number and percentage. The Mann-Whitney test was used to compare continuous variables between groups, and chi-square test with continuity correction was used for categorical variables. The variables that were most significantly associated with a negative outcome on the univariate analysis were included in a stepwise logistic regression analysis, in order to identify independent predictors of patient outcome. Statistical analysis was performed using JASP (JASP Team) software.

 

 

Results

Study Population

Of the 88 patients included in the study, 70% were male; the median age was 66 years (IQR, 60-77). In most patients, the diagnosis of COVID-19 was derived from a positive SARS-CoV-2 nasopharyngeal swab. Six patients, however, maintained a negative swab at all determinations but had clinical and imaging features strongly suggesting COVID-19. No patients met the exclusion criteria. Most patients came from the ED (n = 58 [66%]) or general wards (n = 22 [25%]), while few were transferred from the ICU (n = 8 [9%]). The median length of stay in the SICU was 4 days (IQR, 2-7). An epidemiological link to affected persons or a known virus exposure was identifiable in 37 patients (42%).

Clinical, Laboratory, and Imaging Data

The clinical and anthropometric characteristics of patients are shown in Table 1. Hypertension and smoking habits were prevalent in our population, and the median Charlson Comorbidity Index was 3. Most patients experienced fever, dyspnea, and cough during the days before hospitalization.

Laboratory data showed a marked inflammatory milieu in all studied patients, both at baseline and after 24 and 72 hours. Lymphopenia was observed, along with a significant increase of lactate dehydrogenase (LDH), C-reactive protein (CPR), and D-dimer, and a mild increase of procalcitonin. N-terminal pro-brain natriuretic peptide (NT-proBNP) values were also increased, with normal troponin I values (Table 2).

Medical Therapy

Most patients (89%) received hydroxychloroquine, whereas steroids were used in one-third of the population (36%). Immunomodulators (tocilizumab and ruxolitinib) were restricted to 12 patients (14%). Empirical antiviral therapy was introduced in the first 41 patients (47%). Enoxaparin was the default agent for thromboembolism prophylaxis, and 6 patients (7%) received 70% of the anticoagulating dose.

Oxygen and Ventilatory Therapy

Basal median P/F ratio was 253 (IQR, 218-291), and respiratory rate at triage was 20 breaths/min (IQR, 16-28), underlining a moderate-to-severe respiratory insufficiency at presentation. A total of 69 patients (78%) underwent CPAP, with a median positive end-expiratory pressure (PEEP) of 10.0 cm H₂O (IQR, 7.5-10.0) and fraction of inspired oxygen (Fio₂) of 0.40 (IQR, 0.40-0.50). In 37 patients (42%) who received ongoing CPAP, prone positioning was adopted. In this subgroup, respiratory rate was not significantly different from baseline to resupination (24 vs 25 breaths/min). The median P/F improved from 197 (IQR, 154-236) at baseline to 217 (IQR, 180-262) after pronation (the duration of the prone position was variable, depending on patients’ tolerance: 1 to 6 hours or every pronation cycle). The median delta P/F ratio was 39.4 (IQR, –17.0 to 78.0).

Outcomes

A total of 28 patients (32%) had a negative outcome in the SICU: 8 patients (9%) died, having no clinical indication for higher-intensity care; 6 patients (7%) were transferred to general wards for palliation; and 14 patients (16%) needed an upgrade of cure intensity and were transferred to the ICU. Of these 14 patients, 9 died in the ICU. The total in-hospital mortality of COVID-19 patients, including patients transferred from the SICU to general wards in fair condition, was 27% (n = 24). Clinical, laboratory, and therapeutic characteristics between the 2 groups are shown in Table 4.

Patients who had a negative outcome were significantly older and had more comorbidities, as suggested by a significantly higher prevalence of diabetes and higher Charlson Comorbidity scores (reflecting the mortality risk based on age and comorbidities). The median MuLBSTA score, which estimates the 90-day mortality risk from viral pneumonia, was also higher in patients who had a negative outcome (9.33%). Symptom occurrence was not different in patients with a negative outcome (apart from cough, which was less frequent), but these patients underwent hospitalization earlier—since the appearance of their first COVID-19 symptoms—compared to patients who had a positive outcome. No difference was found in antihypertensive therapy with angiotensin-converting enzyme inhibitors or angiotensin-receptor blockers among outcome groups.

More pronounced laboratory abnormalities were found in patients who had a negative outcome, compared to patients who had a positive outcome: lower lymphocytes and higher C-reactive protein (CRP), procalcitonin, D-dimer, LDH, and NT-proBNP. We found no differences in the radiological distribution of pulmonary involvement in patients who had negative or positive outcomes, nor in the adopted medical treatment.

Data showed no difference in CPAP implementation in the 2 groups. However, prone positioning had been more frequently adopted in the group of patients who had a positive outcome, compared with patients who had a negative outcome. No differences of basal P/F were found in patients who had a negative or positive outcome, but the median P/F after 6 hours of prone position was significantly lower in patients who had a negative outcome. The delta P/F ratio did not differ in the 2 groups of patients.

Multivariate Analysis

A logistic regression model was created, including the variables significantly associated with outcomes in the univariate analysis (age, sex, history of diabetes, lymphocytes, CRP, procalcitonin, LDH, NT-proBNP, and D-dimer). In the multivariate analysis, independent predictors of a negative outcome were history of diabetes (odds ratio [OR], 8.22; 95% CI, 1.50-44.70; P =.015), high D-dimer values (OR, 1.28; CI, 1.04-1.57; P = .019), high LDH values (OR, 1.003; CI, 1.000-1.006; P = .039), and low lymphocytes count (OR, 0.996; CI, 0.993-0.999; P = .004).

Discussion

Role of Subintensive Units and Mortality

The novelty of our report is its attempt to investigate the specific group of COVID-19 patients admitted to a SICU. In Italy, SICUs receive acutely ill, spontaneously breathing patients who need (invasive) hemodynamic monitoring, vasoactive medication, renal replacement therapy, chest- tube placement, thrombolysis, and respiratory noninvasive support. The nurse-to-patient ratio is higher than for general wards (usually 1 nurse to every 4 or 5 patients), though lower than for ICUs. In northern Italy, a great number of COVID-19 patients have required this kind of high-intensity care during the pandemic: Noninvasive ventilation support had to be maintained for several days, pronation maneuvers required a high number of people 2 or 3 times a day, and strict monitoring had to be assured. The SICU setting allows patients to buy time as a bridge to progressive reduction of pulmonary involvement, sometimes preventing the need for intubation.

The high prevalence of negative outcomes in the SICU underlines the complexity of COVID-19 patients in this setting. In fact, published data about mortality for patients with severe COVID-19 pneumonia are similar to ours.^22,23

Clinical, Laboratory, and Imaging Data

Our analysis confirmed a high rate of comorbidities in COVID-19 patients²⁴ and their prognostic role with age.^25,26 A marked inflammatory milieu was a negative prognostic indicator, and associated concomitant bacterial superinfection could have led to a worse prognosis (procalcitonin was associated with negative outcomes).²⁷ The cardiovascular system was nevertheless stressed, as suggested by higher values of NT-proBNP in patients with negative outcomes, which could reflect sepsis-related systemic involvement.²⁸

It is known that the pulmonary damage caused by SARS-CoV-2 has a dynamic radiological and clinical course, with early areas of subsegmental consolidation, and bilateral ground-glass opacities predominating later in the course of the disease.²⁹ This could explain why in our population we found no specific radiological pattern leading to a worse outcome.

Medical Therapy

No specific pharmacological therapy was found to be associated with a positive outcome in our study, just like antiviral and immunomodulator therapies failed to demonstrate effectiveness in subsequent pandemic surges. The low statistical power of our study did not allow us to give insight into the effectiveness of steroids and heparin at any dosage.

PEEP Support and Prone Positioning

Continuous positive airway pressure was initiated in the majority of patients and maintained for several days. This was an absolute novelty, because we rarely had to keep patients in helmets for long. This was feasible thanks to the SICU’s high nurse-to-patient ratio and the possibility of providing monitored sedation. Patients who could no longer tolerate CPAP helmets or did not improve with CPAP support were evaluated with anesthetists for programming further management. No initial data on respiratory rate, level of hypoxemia, or oxygen support need (level of PEEP and Fio₂) could discriminate between outcomes.

Prone positioning during CPAP was implemented in 42% of our study population: P/F ratio amelioration after prone positioning was highly variable, ranging from very good P/F ratio improvements to few responses or no response. No significantly greater delta P/F ratio was seen after the first prone positioning cycle in patients who had a positive outcome, probably due to the small size of our population, but we observed a clear positive trend. Interestingly, patients showing a negative outcome had a lower percentage of long-term responses to prone positioning: 6 hours after resupination, they lost the benefit of prone positioning in terms of P/F ratio amelioration. Similarly, a greater number of patients tolerating prone positioning had a positive outcome. These data give insight on the possible benefits of prone positioning in a noninvasively supported cohort of patients, which has been mentioned in previous studies.^30,31

Outcomes and Variables Associated With Negative Outcomes

After correction for age and sex, we found in multiple regression analysis that higher D-dimer and LDH values, lymphopenia, and history of diabetes were independently associated with a worse outcome. Although our results had low statistical significance, we consider the trend of the obtained odds ratios important from a clinical point of view. These results could lead to greater attention being placed on COVID-19 patients who present with these characteristics upon their arrival to the ED because they have increased risk of death or intensive care need. Clinicians should consider SICU admission for these patients in order to guarantee closer monitoring and possibly more aggressive ventilatory treatments, earlier pronation, or earlier transfer to the ICU.

Limitations

The major limitation to our study is undoubtedly its statistical power, due to its relatively low patient population. Particularly, the small number of patients who underwent pronation did not allow speculation about the efficacy of this technique, although preliminary data seem promising. However, ours is among the first studies regarding patients with COVID-19 admitted to a SICU, and these preliminary data truthfully describe the Italian, and perhaps international, experience with the first surge of the pandemic.

Conclusions

Our data highlight the primary role of the SICU in COVID-19 in adequately treating critically ill patients who have high care needs different from intubation, and who require noninvasive ventilation for prolonged times as well as frequent pronation cycles. This setting of care may represent a valid, reliable, and effective option for critically ill respiratory patients. History of diabetes, lymphopenia, and high D-dimer and LDH values are independently associated with negative outcomes, and patients presenting with these characteristics should be strictly monitored.

Acknowledgments: The authors thank the Informatica System S.R.L., as well as Allessando Mendolia for the pro bono creation of the ISCovidCollect data collecting app.

Corresponding author: Sara Abram, MD, via Coppino, 12100 Cuneo, Italy; sara.abram84@gmail.com.

Disclosures: None.

From the Department of Emergency Medicine, Santa Croce e Carle Hospital, Cuneo, Italy (Drs. Abram, Tosello, Emanuele Bernardi, Allione, Cavalot, Dutto, Corsini, Martini, Sciolla, Sara Bernardi, and Lauria). From the School of Emergency Medicine, University of Turin, Turin, Italy (Drs. Paglietta and Giamello).

Objective: This retrospective and prospective cohort study was designed to describe the characteristics, treatments, and outcomes of patients with SARS-CoV-2 infection (COVID-19) admitted to subintensive care units (SICU) and to identify the variables associated with outcomes. SICUs have been extremely stressed during the pandemic, but most data regarding critically ill COVID-19 patients come from intensive care units (ICUs). Studies about COVID-19 patients in SICUs are lacking.

Setting and participants: The study included 88 COVID-19 patients admitted to our SICU in Cuneo, Italy, between March and May 2020.

Measurements: Clinical and ventilatory data were collected, and patients were divided by outcome. Multivariable logistic regression analysis examined the variables associated with negative outcomes (transfer to the ICU, palliation, or death in a SICU).

Results: A total of 60 patients (68%) had a positive outcome, and 28 patients (32%) had a negative outcome; 69 patients (78%) underwent continuous positive airway pressure (CPAP). Pronation (n = 37 [42%]) had been more frequently adopted in patients who had a positive outcome vs a negative outcome (n = 30 [50%] vs n = 7 [25%]; P = .048), and the median (interquartile range) Pao₂/Fio₂ ratio after 6 hours of prone positioning was lower in patients who had a negative outcome vs a positive outcome (144 [140-168] vs 249 [195-268], P = .006). Independent predictors of a negative outcome were diabetes (odds ratio [OR], 8.22; 95% CI, 1.50-44.70; P = .015), higher D-dimer (OR, 1.28; 95% CI, 1.04-1.57; P = .019), higher lactate dehydrogenase level (OR, 1.003; 95% CI, 1.000-1.006; P = .039), and lower lymphocytes count (OR, 0.996; 95% CI, 0.993-0.999; P = .004).

Conclusion: SICUs have a fundamental role in the treatment of critically ill patients with COVID-19, who require long-term CPAP and pronation cycles. Diabetes, lymphopenia, and high D-dimer and LDH levels are associated with negative outcomes.

Keywords: emergency medicine, noninvasive ventilation, prone position, continuous positive airway pressure.

The COVID-19 pandemic has led to large increases in hospital admissions. Subintensive care units (SICUs) are among the wards most under pressure worldwide,¹ dealing with the increased number of critically ill patients who need noninvasive ventilation, as well as serving as the best alternative to overfilled intensive care units (ICUs). In Italy, SICUs are playing a fundamental role in the management of COVID-19 patients, providing early treatment of respiratory failure by continuous noninvasive ventilation in order to reduce the need for intubation.^2-5 Nevertheless, the great majority of available data about critically ill COVID-19 patients comes from ICUs. Full studies about outcomes of patients in SICUs are lacking and need to be conducted.

We sought to evaluate the characteristics and outcomes of patients admitted to our SICU for COVID-19 to describe the treatments they needed and their impact on prognosis, and to identify the variables associated with patient outcomes.

Methods

Study Design

This cohort study used data from patients who were admitted in the very first weeks of the pandemic. Data were collected retrospectively as well as prospectively, since the ethical committee approved our project. The quality and quantity of data in the 2 groups were comparable.

Data were collected from electronic and written medical records gathered during the patient’s entire stay in our SICU. Data were entered in a database with limited and controlled access. This study complied with the Declaration of Helsinki and was approved by the local ethics committees (ID: MEDURG10).

Study Population

We studied 88 consecutive patients admitted to the SICU of the Santa Croce e Carle Teaching Hospital, Cuneo, Italy, for COVID-19, from March 8 to May 1, 2020. The diagnosis was based on acute respiratory failure associated with SARS-CoV-2 RNA detection on nasopharyngeal swab or tracheal aspirate and/or typical COVID-19 features on a pulmonary computed tomography (CT) scan.⁶ Exclusion criteria were age younger than 18 years and patient denial of permission to use their data for research purposes (the great majority of patients could actively give consent; for patients who were too sick to do so, family members were asked whether they were aware of any reason why the patient would deny consent).

 

 

Clinical Data

The past medical history and recent symptoms description were obtained by manually reviewing medical records. Epidemiological exposure was defined as contact with SARS-CoV-2–positive people or staying in an epidemic outbreak area. Initial vital parameters, venous blood tests, arterial blood gas analysis, chest x-ray, as well as the result of the nasopharyngeal swab were gathered from the emergency department (ED) examination. (Additional swabs could be requested when the first one was negative but clinical suspicion for COVID-19 was high.) Upon admission to the SICU, a standardized panel of blood tests was performed, which was repeated the next day and then every 48 hours. Arterial blood gas analysis was performed when clinically indicated, at least twice a day, or following a scheduled time in patients undergoing pronation. Charlson Comorbidity Index⁷ and MuLBSTA score⁸ were calculated based on the collected data.

Imaging

Chest ultrasonography was performed in the ED at the time of hospitalization and once a day in the SICU. Pulmonary high-resolution computed tomography (HRCT) was performed when clinically indicated or when the results of nasopharyngeal swabs and/or x-ray results were discordant with COVID-19 clinical suspicion. Contrast CT was performed when pulmonary embolism was suspected.

Medical Therapy

Hydroxychloroquine, antiviral agents, tocilizumab, and ruxolitinib were used in the early phase of the pandemic, then were dismissed after evidence of no efficacy.^9-11 Steroids and low-molecular-weight heparin were used afterward. Enoxaparin was used at the standard prophylactic dosage, and 70% of the anticoagulant dosage was also adopted in patients with moderate-to-severe COVID-19 and D-dimer values >3 times the normal value.^12-14 Antibiotics were given when a bacterial superinfection was suspected.

Oxygen and Ventilatory Therapy

Oxygen support or noninvasive ventilation were started based on patients’ respiratory efficacy, estimated by respiratory rate and the ratio of partial pressure of arterial oxygen and fraction of inspired oxygen (P/F ratio).^15,16 Oxygen support was delivered through nasal cannula, Venturi mask, or reservoir mask. Noninvasive ventilation was performed by continuous positive airway pressure (CPAP) when the P/F ratio was <250 or the respiratory rate was >25 breaths per minute, using the helmet interface.^5,17 Prone positioning during CPAP^18-20 was adopted in patients meeting the acute respiratory distress syndrome (ARDS) criteria²¹ and having persistence of respiratory distress and P/F <300 after a 1-hour trial of CPAP.

The prone position was maintained based on patient tolerance. P/F ratio was measured before pronation (T0), after 1 hour of prone position (T1), before resupination (T2), and 6 hours after resupination (T3). With the same timing, the patient was asked to rate their comfort in each position, from 0 (lack of comfort) to 10 (optimal comfort). Delta P/F was defined as the difference between P/F at T3 and basal P/F at T0.

Outcomes

Positive outcomes were defined as patient discharge from the SICU or transfer to a lower-intensity care ward for treatment continuation. Negative outcomes were defined as need for transfer to the ICU, transfer to another ward for palliation, or death in the SICU.

Statistical Analysis

Continuous data are reported as median and interquartile range (IQR); normal distribution of variables was tested using the Shapiro-Wilk test. Categorical variables were reported as absolute number and percentage. The Mann-Whitney test was used to compare continuous variables between groups, and chi-square test with continuity correction was used for categorical variables. The variables that were most significantly associated with a negative outcome on the univariate analysis were included in a stepwise logistic regression analysis, in order to identify independent predictors of patient outcome. Statistical analysis was performed using JASP (JASP Team) software.

 

 

Results

Study Population

Of the 88 patients included in the study, 70% were male; the median age was 66 years (IQR, 60-77). In most patients, the diagnosis of COVID-19 was derived from a positive SARS-CoV-2 nasopharyngeal swab. Six patients, however, maintained a negative swab at all determinations but had clinical and imaging features strongly suggesting COVID-19. No patients met the exclusion criteria. Most patients came from the ED (n = 58 [66%]) or general wards (n = 22 [25%]), while few were transferred from the ICU (n = 8 [9%]). The median length of stay in the SICU was 4 days (IQR, 2-7). An epidemiological link to affected persons or a known virus exposure was identifiable in 37 patients (42%).

Clinical, Laboratory, and Imaging Data

The clinical and anthropometric characteristics of patients are shown in Table 1. Hypertension and smoking habits were prevalent in our population, and the median Charlson Comorbidity Index was 3. Most patients experienced fever, dyspnea, and cough during the days before hospitalization.

Laboratory data showed a marked inflammatory milieu in all studied patients, both at baseline and after 24 and 72 hours. Lymphopenia was observed, along with a significant increase of lactate dehydrogenase (LDH), C-reactive protein (CPR), and D-dimer, and a mild increase of procalcitonin. N-terminal pro-brain natriuretic peptide (NT-proBNP) values were also increased, with normal troponin I values (Table 2).

Medical Therapy

Most patients (89%) received hydroxychloroquine, whereas steroids were used in one-third of the population (36%). Immunomodulators (tocilizumab and ruxolitinib) were restricted to 12 patients (14%). Empirical antiviral therapy was introduced in the first 41 patients (47%). Enoxaparin was the default agent for thromboembolism prophylaxis, and 6 patients (7%) received 70% of the anticoagulating dose.

Oxygen and Ventilatory Therapy

Basal median P/F ratio was 253 (IQR, 218-291), and respiratory rate at triage was 20 breaths/min (IQR, 16-28), underlining a moderate-to-severe respiratory insufficiency at presentation. A total of 69 patients (78%) underwent CPAP, with a median positive end-expiratory pressure (PEEP) of 10.0 cm H₂O (IQR, 7.5-10.0) and fraction of inspired oxygen (Fio₂) of 0.40 (IQR, 0.40-0.50). In 37 patients (42%) who received ongoing CPAP, prone positioning was adopted. In this subgroup, respiratory rate was not significantly different from baseline to resupination (24 vs 25 breaths/min). The median P/F improved from 197 (IQR, 154-236) at baseline to 217 (IQR, 180-262) after pronation (the duration of the prone position was variable, depending on patients’ tolerance: 1 to 6 hours or every pronation cycle). The median delta P/F ratio was 39.4 (IQR, –17.0 to 78.0).

Outcomes

A total of 28 patients (32%) had a negative outcome in the SICU: 8 patients (9%) died, having no clinical indication for higher-intensity care; 6 patients (7%) were transferred to general wards for palliation; and 14 patients (16%) needed an upgrade of cure intensity and were transferred to the ICU. Of these 14 patients, 9 died in the ICU. The total in-hospital mortality of COVID-19 patients, including patients transferred from the SICU to general wards in fair condition, was 27% (n = 24). Clinical, laboratory, and therapeutic characteristics between the 2 groups are shown in Table 4.

Patients who had a negative outcome were significantly older and had more comorbidities, as suggested by a significantly higher prevalence of diabetes and higher Charlson Comorbidity scores (reflecting the mortality risk based on age and comorbidities). The median MuLBSTA score, which estimates the 90-day mortality risk from viral pneumonia, was also higher in patients who had a negative outcome (9.33%). Symptom occurrence was not different in patients with a negative outcome (apart from cough, which was less frequent), but these patients underwent hospitalization earlier—since the appearance of their first COVID-19 symptoms—compared to patients who had a positive outcome. No difference was found in antihypertensive therapy with angiotensin-converting enzyme inhibitors or angiotensin-receptor blockers among outcome groups.

More pronounced laboratory abnormalities were found in patients who had a negative outcome, compared to patients who had a positive outcome: lower lymphocytes and higher C-reactive protein (CRP), procalcitonin, D-dimer, LDH, and NT-proBNP. We found no differences in the radiological distribution of pulmonary involvement in patients who had negative or positive outcomes, nor in the adopted medical treatment.

Data showed no difference in CPAP implementation in the 2 groups. However, prone positioning had been more frequently adopted in the group of patients who had a positive outcome, compared with patients who had a negative outcome. No differences of basal P/F were found in patients who had a negative or positive outcome, but the median P/F after 6 hours of prone position was significantly lower in patients who had a negative outcome. The delta P/F ratio did not differ in the 2 groups of patients.

Multivariate Analysis

A logistic regression model was created, including the variables significantly associated with outcomes in the univariate analysis (age, sex, history of diabetes, lymphocytes, CRP, procalcitonin, LDH, NT-proBNP, and D-dimer). In the multivariate analysis, independent predictors of a negative outcome were history of diabetes (odds ratio [OR], 8.22; 95% CI, 1.50-44.70; P =.015), high D-dimer values (OR, 1.28; CI, 1.04-1.57; P = .019), high LDH values (OR, 1.003; CI, 1.000-1.006; P = .039), and low lymphocytes count (OR, 0.996; CI, 0.993-0.999; P = .004).

Discussion

Role of Subintensive Units and Mortality

The novelty of our report is its attempt to investigate the specific group of COVID-19 patients admitted to a SICU. In Italy, SICUs receive acutely ill, spontaneously breathing patients who need (invasive) hemodynamic monitoring, vasoactive medication, renal replacement therapy, chest- tube placement, thrombolysis, and respiratory noninvasive support. The nurse-to-patient ratio is higher than for general wards (usually 1 nurse to every 4 or 5 patients), though lower than for ICUs. In northern Italy, a great number of COVID-19 patients have required this kind of high-intensity care during the pandemic: Noninvasive ventilation support had to be maintained for several days, pronation maneuvers required a high number of people 2 or 3 times a day, and strict monitoring had to be assured. The SICU setting allows patients to buy time as a bridge to progressive reduction of pulmonary involvement, sometimes preventing the need for intubation.

The high prevalence of negative outcomes in the SICU underlines the complexity of COVID-19 patients in this setting. In fact, published data about mortality for patients with severe COVID-19 pneumonia are similar to ours.^22,23

Clinical, Laboratory, and Imaging Data

Our analysis confirmed a high rate of comorbidities in COVID-19 patients²⁴ and their prognostic role with age.^25,26 A marked inflammatory milieu was a negative prognostic indicator, and associated concomitant bacterial superinfection could have led to a worse prognosis (procalcitonin was associated with negative outcomes).²⁷ The cardiovascular system was nevertheless stressed, as suggested by higher values of NT-proBNP in patients with negative outcomes, which could reflect sepsis-related systemic involvement.²⁸

It is known that the pulmonary damage caused by SARS-CoV-2 has a dynamic radiological and clinical course, with early areas of subsegmental consolidation, and bilateral ground-glass opacities predominating later in the course of the disease.²⁹ This could explain why in our population we found no specific radiological pattern leading to a worse outcome.

Medical Therapy

No specific pharmacological therapy was found to be associated with a positive outcome in our study, just like antiviral and immunomodulator therapies failed to demonstrate effectiveness in subsequent pandemic surges. The low statistical power of our study did not allow us to give insight into the effectiveness of steroids and heparin at any dosage.

PEEP Support and Prone Positioning

Continuous positive airway pressure was initiated in the majority of patients and maintained for several days. This was an absolute novelty, because we rarely had to keep patients in helmets for long. This was feasible thanks to the SICU’s high nurse-to-patient ratio and the possibility of providing monitored sedation. Patients who could no longer tolerate CPAP helmets or did not improve with CPAP support were evaluated with anesthetists for programming further management. No initial data on respiratory rate, level of hypoxemia, or oxygen support need (level of PEEP and Fio₂) could discriminate between outcomes.

Prone positioning during CPAP was implemented in 42% of our study population: P/F ratio amelioration after prone positioning was highly variable, ranging from very good P/F ratio improvements to few responses or no response. No significantly greater delta P/F ratio was seen after the first prone positioning cycle in patients who had a positive outcome, probably due to the small size of our population, but we observed a clear positive trend. Interestingly, patients showing a negative outcome had a lower percentage of long-term responses to prone positioning: 6 hours after resupination, they lost the benefit of prone positioning in terms of P/F ratio amelioration. Similarly, a greater number of patients tolerating prone positioning had a positive outcome. These data give insight on the possible benefits of prone positioning in a noninvasively supported cohort of patients, which has been mentioned in previous studies.^30,31

Outcomes and Variables Associated With Negative Outcomes

After correction for age and sex, we found in multiple regression analysis that higher D-dimer and LDH values, lymphopenia, and history of diabetes were independently associated with a worse outcome. Although our results had low statistical significance, we consider the trend of the obtained odds ratios important from a clinical point of view. These results could lead to greater attention being placed on COVID-19 patients who present with these characteristics upon their arrival to the ED because they have increased risk of death or intensive care need. Clinicians should consider SICU admission for these patients in order to guarantee closer monitoring and possibly more aggressive ventilatory treatments, earlier pronation, or earlier transfer to the ICU.

Limitations

The major limitation to our study is undoubtedly its statistical power, due to its relatively low patient population. Particularly, the small number of patients who underwent pronation did not allow speculation about the efficacy of this technique, although preliminary data seem promising. However, ours is among the first studies regarding patients with COVID-19 admitted to a SICU, and these preliminary data truthfully describe the Italian, and perhaps international, experience with the first surge of the pandemic.

Conclusions

Our data highlight the primary role of the SICU in COVID-19 in adequately treating critically ill patients who have high care needs different from intubation, and who require noninvasive ventilation for prolonged times as well as frequent pronation cycles. This setting of care may represent a valid, reliable, and effective option for critically ill respiratory patients. History of diabetes, lymphopenia, and high D-dimer and LDH values are independently associated with negative outcomes, and patients presenting with these characteristics should be strictly monitored.

Acknowledgments: The authors thank the Informatica System S.R.L., as well as Allessando Mendolia for the pro bono creation of the ISCovidCollect data collecting app.

Corresponding author: Sara Abram, MD, via Coppino, 12100 Cuneo, Italy; sara.abram84@gmail.com.

Disclosures: None.

Equitable Standards for All Patients in a Crisis

Health care delivered during a pandemic instantiates medicine’s perspectives on the value of human life in clinical scenarios where resource allocation is limited. The COVID-19 pandemic has fostered dialogue and debate around the ethical principles that underly such resource allocation, which generally balance (1) utilitarian optimization of resources, (2) equality or equity in health access, (3) the instrumental value of individuals as agents in society, and (4) prioritizing the “worst off” in their natural history of disease.^1,2 State legislatures and health systems have responded to the challeges posed by COVID-19 by considering both the scarcity of intensive care resources, such as mechanical ventilation and hemodialysis, and the clinical criteria to be used for determining which patients should receive said resources. These crisis guidelines have yielded several concerning themes vis-à-vis equitable distribution of health care resources, particularly when the disability status of patients is considered alongside life-expectancy or quality of life.³

Crisis standards of care (CSC) prioritize population-level health under a utilitarian paradigm, explicitly maximizing “life-years” within a population of patients rather than the life of any individual patient.⁴ Debated during initial COVID surges, these CSC guidelines have recently been enacted at the state level in several settings, including Alaska and Idaho.⁵ In a setting with scarce intensive care resources, balancing health equity in access to these resources against population-based survival metrics has been a challenge for commissions considering CSC.^6,7 This need for balance has further promoted systemic views of “disability,” raising concern for structural “ableism” and highlighting the need for greater “ability awareness” in clinicians’ continued professional learning.

Structural Ableism: Defining Perspectives to Address Health Equity

Ableism has been defined as “a system that places value on people’s bodies and minds, based on societally constructed ideas of normalcy, intelligence, excellence, and productivity…[and] leads to people and society determining who is valuable and worthy based on their appearance and/or their ability to satisfactorily [re]produce, excel, and ‘behave.’”⁸ Regarding CSC, concerns about systemic bias in guideline design were raised early by disability advocacy groups during comment periods.^9,10 More broadly, concerns about ableism sit alongside many deeply rooted societal perspectives of disabled individuals as pitiable or, conversely, heroic for having “overcome” their disability in some way. As a physician who sits in a manual wheelchair with paraplegia and mobility impairment, I have equally been subject to inappropriate bias and inappropriate praise for living in a wheelchair. I have also wondered, alongside my patients living with different levels of mobility or ability, why others often view us as “worse off.” Addressing directly whether disabled individuals are “worse off,” disability rights attorney and advocate Harriet McBryde Johnson has articulated a predominant sentiment among persons living with unique or different abilities:

Are we “worse off”? I don’t think so. Not in any meaningful way. There are too many variables. For those of us with congenital conditions, disability shapes all we are. Those disabled later in life adapt. We take constraints that no one would choose and build rich and satisfying lives within them. We enjoy pleasures other people enjoy and pleasures peculiarly our own. We have something the world needs.¹¹

Many physician colleagues have common, invisible diseases such as diabetes and heart disease; fewer colleagues share conditions that are as visible as my spinal cord injury, as readily apparent to patients upon my entry to their hospital rooms. This simultaneous and inescapable identity as both patient and provider has afforded me wonderful doctor-patient interactions, particularly with those patients who appreciate how my patient experience impacts my ability to partially understand theirs. However, this simultaneous identity as doctor and patient also informed my personal and professional concerns regarding structural ableism as I considered scoring my own acutely ill hospital medicine patients with CSC triage scores in April 2020.

As a practicing hospital medicine physician, I have been emboldened by the efforts of my fellow clinicians amid COVID-19; their efforts have reaffirmed all the reasons I pursued a career in medicine. However, when I heard my clinical colleagues’ first explanation of the Massachusetts CSC guidelines in April 2020, I raised my hand to ask whether the “life-years” to which the guidelines referred were quality-adjusted. My concern regarding the implicit use of quality-adjusted life years (QALY) or disability-adjusted life years in clinical decision-making and implementation of these guidelines was validated when no clinical leaders could address this question directly. Sitting on the CSC committee for my hospital during this time was an honor. However, it was disconcerting to hear many clinicians’ unease when estimating mean survival for common chronic diseases, ranging from end-stage renal disease to advanced heart failure. If my expert colleagues, clinical specialists in kidney and heart disease, could not confidently apply mean survival estimates to multimorbid hospital patients, then idiosyncratic clinical judgment was sure to have a heavy hand in any calculation of “life-years.” Thus, my primary concern was that clinicians using triage heuristics would be subject to bias, regardless of their intention, and negatively adjust for the quality of a disabled life in their CSC triage scoring. My secondary concern was that the CSC guidelines themselves included systemic bias against disabled individuals.

According to CSC schema, triage scores index heavily on Sequential Organ Failure Assessment (SOFA) scores to define short-term survival; SOFA scores are partially driven by the Glasgow Coma Scale (GCS). Following professional and public comment periods, CSC guidelines in Massachusetts were revised to, among other critical points of revision, change prognostic estimation via “life years” in favor of generic estimation of short-term survival (Table). I wondered, if I presented to an emergency department with severe COVID-19 and was scored with the GCS for the purpose of making a CSC ventilator triage decision, how would my complete paraplegia and lower-extremity motor impairment be accounted for by a clinician assessing “best motor response” in the GCS? The purpose of these scores is to act algorithmically, to guide clinicians whose cognitive load and time limitations may not allow for adjustment of these algorithms based on the individual patient in front of them. Individualization of clinical decisions is part of medicine’s art, but is difficult in the best of times and no easier during a crisis in care delivery. As CSC triage scores were amended and addended throughout 2020, I returned to the COVID wards, time and again wondering, “What have we learned about systemic bias and health inequity in the CSC process and the pandemic broadly, with specific regard to disability?”

Ability Awareness: Room for Our Improvement

Unfortunately, there is reason to believe that clinical judgment is impaired by structural ableism. In seminal work on this topic, Gerhart et al¹² demonstrated that clinicians considered spinal cord injury (SCI) survivors to have low self-perceptions of worthiness, overall negative attitudes, and low self-esteem as compared to able-bodied individuals. However, surveyed SCI survivors generally had similar self-perceptions of worth and positivity as compared to ”able-bodied” clinicians.¹² For providers who care for persons with disabilities, the majority (82.4%) have rated their disabled patients’ quality of life as worse.¹³ It is no wonder that patients with disabilities are more likely to feel that their doctor-patient relationship is impacted by lack of understanding, negative sentiment, or simple lack of listening.¹⁴ Generally, this poor doctor-patient relationship with disabled patients is exacerbated by poor exposure of medical trainees to disability education; only 34.2% of internal medicine residents recall any form of disability education in medical school, while only 52% of medical school deans report having disability educational content in their curricula.^15,16 There is a similar lack of disability representation in the population of medical trainees themselves. While approximately 20% of the American population lives with a disability, less than 2% of American medical students have a disability.^17-19

While representation of disabled populations in medical practice remains poor, disabled patients are generally less likely to receive age-appropriate prevention, appropriate access to care, and equal access to treatment.^20-22 “Diagnostic overshadowing” refers to clinicians’ attribution of nonspecific signs or symptoms to a patient’s chronic disability as opposed to acute illness.²³ This phenomenon has led to higher rates of preventable malignancy in disabled patients and misattribution of common somatic symptoms to intellectual disability.^24,25 With this disparity in place as status quo for health care delivery to disabled populations, it is no surprise that certain portions of the disabled population have accounted for disproportionate mortality due to COVID-19.^26,27Disability advocates have called for “nothing about us without us,” a phrase associated with the United Nations Convention on the Rights of Persons with Disabilities. Understanding the profound neurodiversity among several forms of sensory and cognitive disabilities, as well as the functional difference between cognitive disabilities, mobility impairment, and inability to meet one’s instrumental activities of daily living independently, others have proposed a unique approach to certain disabled populations in COVID care.²⁸ My own perspective is that definite progress may require a more general understanding of the prevalence of disability by clinicians, both via medical training and by directly addressing health equity for disabled populations in such calculations as the CSC. Systemic ableism is apparent in our most common clinical scoring systems, ranging from the GCS and Functional Assessment Staging Table to the Eastern Cooperative Oncology Group and Karnofsky Performance Status scales. I have reexamined these scoring systems in my own understanding given their general equation of ambulation with ability or normalcy. As a doctor in a manual wheelchair who values greatly my personal quality of life and professional contribution to patient care, I worry that these scoring systems inherently discount my own equitable access to care. Individualization of patients’ particular abilities in the context of these scales must occur alongside evidence-based, guideline-directed management via these scoring systems.

Conclusion: Future Orientation

Updated CSC guidelines have accounted for the unique considerations of disabled patients by effectively caveating their scoring algorithms, directing clinicians via disclaimers to uniquely consider their disabled patients in clinical judgement. This is a first step, but it is also one that erodes the value of algorithms, which generally obviate more deliberative thinking and individualization. For our patients who lack certain abilities, as CSC continue to be activated in several states, we have an opportunity to pursue more inherently equitable solutions before further suffering accrues.²⁹ By way of example, adaptations to scoring systems that leverage QALYs for value-based drug pricing indices have been proposed by organizations like the Institute for Clinical and Economic Review, which proposed the Equal-Value-of Life-Years-Gained framework to inform QALY-based arbitration of drug pricing.³⁰ This is not a perfect rubric but instead represents an attempt to balance consideration of drugs, as has been done with ventilators during the pandemic, as a scare and expensive resource while addressing the just concerns of advocacy groups in structural ableism.

Resource stewardship during a crisis should not discount those states of human life that are perceived to be less desirable, particularly if they are not experienced as less desirable but are experienced uniquely. Instead, we should consider equitably measuring our intervention to match a patient’s needs, as we would dose-adjust a medication for renal function or consider minimally invasive procedures for multimorbid patients. COVID-19 has reflected our profession’s ethical adaptation during crisis as resources have become scarce; there is no better time to define solutions for health equity. We should now be concerned equally by the influence our personal biases have on our clinical practice and by the way in which these crisis standards will influence patients’ perception of and trust in their care providers during periods of perceived plentiful resources in the future. Health care resources are always limited, allocated according to societal values; if we value health equity for people of all abilities, then we will consider these abilities equitably as we pursue new standards for health care delivery.

Corresponding author: Gregory D. Snyder, MD, MBA, 2014 Washington Street, Newton, MA 02462; gdsnyder@bwh.harvard.edu.

Disclosures: None.
 

Equitable Standards for All Patients in a Crisis

Health care delivered during a pandemic instantiates medicine’s perspectives on the value of human life in clinical scenarios where resource allocation is limited. The COVID-19 pandemic has fostered dialogue and debate around the ethical principles that underly such resource allocation, which generally balance (1) utilitarian optimization of resources, (2) equality or equity in health access, (3) the instrumental value of individuals as agents in society, and (4) prioritizing the “worst off” in their natural history of disease.^1,2 State legislatures and health systems have responded to the challeges posed by COVID-19 by considering both the scarcity of intensive care resources, such as mechanical ventilation and hemodialysis, and the clinical criteria to be used for determining which patients should receive said resources. These crisis guidelines have yielded several concerning themes vis-à-vis equitable distribution of health care resources, particularly when the disability status of patients is considered alongside life-expectancy or quality of life.³

Crisis standards of care (CSC) prioritize population-level health under a utilitarian paradigm, explicitly maximizing “life-years” within a population of patients rather than the life of any individual patient.⁴ Debated during initial COVID surges, these CSC guidelines have recently been enacted at the state level in several settings, including Alaska and Idaho.⁵ In a setting with scarce intensive care resources, balancing health equity in access to these resources against population-based survival metrics has been a challenge for commissions considering CSC.^6,7 This need for balance has further promoted systemic views of “disability,” raising concern for structural “ableism” and highlighting the need for greater “ability awareness” in clinicians’ continued professional learning.

Structural Ableism: Defining Perspectives to Address Health Equity

Ableism has been defined as “a system that places value on people’s bodies and minds, based on societally constructed ideas of normalcy, intelligence, excellence, and productivity…[and] leads to people and society determining who is valuable and worthy based on their appearance and/or their ability to satisfactorily [re]produce, excel, and ‘behave.’”⁸ Regarding CSC, concerns about systemic bias in guideline design were raised early by disability advocacy groups during comment periods.^9,10 More broadly, concerns about ableism sit alongside many deeply rooted societal perspectives of disabled individuals as pitiable or, conversely, heroic for having “overcome” their disability in some way. As a physician who sits in a manual wheelchair with paraplegia and mobility impairment, I have equally been subject to inappropriate bias and inappropriate praise for living in a wheelchair. I have also wondered, alongside my patients living with different levels of mobility or ability, why others often view us as “worse off.” Addressing directly whether disabled individuals are “worse off,” disability rights attorney and advocate Harriet McBryde Johnson has articulated a predominant sentiment among persons living with unique or different abilities:

Are we “worse off”? I don’t think so. Not in any meaningful way. There are too many variables. For those of us with congenital conditions, disability shapes all we are. Those disabled later in life adapt. We take constraints that no one would choose and build rich and satisfying lives within them. We enjoy pleasures other people enjoy and pleasures peculiarly our own. We have something the world needs.¹¹

Many physician colleagues have common, invisible diseases such as diabetes and heart disease; fewer colleagues share conditions that are as visible as my spinal cord injury, as readily apparent to patients upon my entry to their hospital rooms. This simultaneous and inescapable identity as both patient and provider has afforded me wonderful doctor-patient interactions, particularly with those patients who appreciate how my patient experience impacts my ability to partially understand theirs. However, this simultaneous identity as doctor and patient also informed my personal and professional concerns regarding structural ableism as I considered scoring my own acutely ill hospital medicine patients with CSC triage scores in April 2020.

As a practicing hospital medicine physician, I have been emboldened by the efforts of my fellow clinicians amid COVID-19; their efforts have reaffirmed all the reasons I pursued a career in medicine. However, when I heard my clinical colleagues’ first explanation of the Massachusetts CSC guidelines in April 2020, I raised my hand to ask whether the “life-years” to which the guidelines referred were quality-adjusted. My concern regarding the implicit use of quality-adjusted life years (QALY) or disability-adjusted life years in clinical decision-making and implementation of these guidelines was validated when no clinical leaders could address this question directly. Sitting on the CSC committee for my hospital during this time was an honor. However, it was disconcerting to hear many clinicians’ unease when estimating mean survival for common chronic diseases, ranging from end-stage renal disease to advanced heart failure. If my expert colleagues, clinical specialists in kidney and heart disease, could not confidently apply mean survival estimates to multimorbid hospital patients, then idiosyncratic clinical judgment was sure to have a heavy hand in any calculation of “life-years.” Thus, my primary concern was that clinicians using triage heuristics would be subject to bias, regardless of their intention, and negatively adjust for the quality of a disabled life in their CSC triage scoring. My secondary concern was that the CSC guidelines themselves included systemic bias against disabled individuals.

According to CSC schema, triage scores index heavily on Sequential Organ Failure Assessment (SOFA) scores to define short-term survival; SOFA scores are partially driven by the Glasgow Coma Scale (GCS). Following professional and public comment periods, CSC guidelines in Massachusetts were revised to, among other critical points of revision, change prognostic estimation via “life years” in favor of generic estimation of short-term survival (Table). I wondered, if I presented to an emergency department with severe COVID-19 and was scored with the GCS for the purpose of making a CSC ventilator triage decision, how would my complete paraplegia and lower-extremity motor impairment be accounted for by a clinician assessing “best motor response” in the GCS? The purpose of these scores is to act algorithmically, to guide clinicians whose cognitive load and time limitations may not allow for adjustment of these algorithms based on the individual patient in front of them. Individualization of clinical decisions is part of medicine’s art, but is difficult in the best of times and no easier during a crisis in care delivery. As CSC triage scores were amended and addended throughout 2020, I returned to the COVID wards, time and again wondering, “What have we learned about systemic bias and health inequity in the CSC process and the pandemic broadly, with specific regard to disability?”

Ability Awareness: Room for Our Improvement

Unfortunately, there is reason to believe that clinical judgment is impaired by structural ableism. In seminal work on this topic, Gerhart et al¹² demonstrated that clinicians considered spinal cord injury (SCI) survivors to have low self-perceptions of worthiness, overall negative attitudes, and low self-esteem as compared to able-bodied individuals. However, surveyed SCI survivors generally had similar self-perceptions of worth and positivity as compared to ”able-bodied” clinicians.¹² For providers who care for persons with disabilities, the majority (82.4%) have rated their disabled patients’ quality of life as worse.¹³ It is no wonder that patients with disabilities are more likely to feel that their doctor-patient relationship is impacted by lack of understanding, negative sentiment, or simple lack of listening.¹⁴ Generally, this poor doctor-patient relationship with disabled patients is exacerbated by poor exposure of medical trainees to disability education; only 34.2% of internal medicine residents recall any form of disability education in medical school, while only 52% of medical school deans report having disability educational content in their curricula.^15,16 There is a similar lack of disability representation in the population of medical trainees themselves. While approximately 20% of the American population lives with a disability, less than 2% of American medical students have a disability.^17-19

While representation of disabled populations in medical practice remains poor, disabled patients are generally less likely to receive age-appropriate prevention, appropriate access to care, and equal access to treatment.^20-22 “Diagnostic overshadowing” refers to clinicians’ attribution of nonspecific signs or symptoms to a patient’s chronic disability as opposed to acute illness.²³ This phenomenon has led to higher rates of preventable malignancy in disabled patients and misattribution of common somatic symptoms to intellectual disability.^24,25 With this disparity in place as status quo for health care delivery to disabled populations, it is no surprise that certain portions of the disabled population have accounted for disproportionate mortality due to COVID-19.^26,27Disability advocates have called for “nothing about us without us,” a phrase associated with the United Nations Convention on the Rights of Persons with Disabilities. Understanding the profound neurodiversity among several forms of sensory and cognitive disabilities, as well as the functional difference between cognitive disabilities, mobility impairment, and inability to meet one’s instrumental activities of daily living independently, others have proposed a unique approach to certain disabled populations in COVID care.²⁸ My own perspective is that definite progress may require a more general understanding of the prevalence of disability by clinicians, both via medical training and by directly addressing health equity for disabled populations in such calculations as the CSC. Systemic ableism is apparent in our most common clinical scoring systems, ranging from the GCS and Functional Assessment Staging Table to the Eastern Cooperative Oncology Group and Karnofsky Performance Status scales. I have reexamined these scoring systems in my own understanding given their general equation of ambulation with ability or normalcy. As a doctor in a manual wheelchair who values greatly my personal quality of life and professional contribution to patient care, I worry that these scoring systems inherently discount my own equitable access to care. Individualization of patients’ particular abilities in the context of these scales must occur alongside evidence-based, guideline-directed management via these scoring systems.

Conclusion: Future Orientation

Updated CSC guidelines have accounted for the unique considerations of disabled patients by effectively caveating their scoring algorithms, directing clinicians via disclaimers to uniquely consider their disabled patients in clinical judgement. This is a first step, but it is also one that erodes the value of algorithms, which generally obviate more deliberative thinking and individualization. For our patients who lack certain abilities, as CSC continue to be activated in several states, we have an opportunity to pursue more inherently equitable solutions before further suffering accrues.²⁹ By way of example, adaptations to scoring systems that leverage QALYs for value-based drug pricing indices have been proposed by organizations like the Institute for Clinical and Economic Review, which proposed the Equal-Value-of Life-Years-Gained framework to inform QALY-based arbitration of drug pricing.³⁰ This is not a perfect rubric but instead represents an attempt to balance consideration of drugs, as has been done with ventilators during the pandemic, as a scare and expensive resource while addressing the just concerns of advocacy groups in structural ableism.

Resource stewardship during a crisis should not discount those states of human life that are perceived to be less desirable, particularly if they are not experienced as less desirable but are experienced uniquely. Instead, we should consider equitably measuring our intervention to match a patient’s needs, as we would dose-adjust a medication for renal function or consider minimally invasive procedures for multimorbid patients. COVID-19 has reflected our profession’s ethical adaptation during crisis as resources have become scarce; there is no better time to define solutions for health equity. We should now be concerned equally by the influence our personal biases have on our clinical practice and by the way in which these crisis standards will influence patients’ perception of and trust in their care providers during periods of perceived plentiful resources in the future. Health care resources are always limited, allocated according to societal values; if we value health equity for people of all abilities, then we will consider these abilities equitably as we pursue new standards for health care delivery.

Corresponding author: Gregory D. Snyder, MD, MBA, 2014 Washington Street, Newton, MA 02462; gdsnyder@bwh.harvard.edu.

Disclosures: None.
 

Equitable Standards for All Patients in a Crisis

Health care delivered during a pandemic instantiates medicine’s perspectives on the value of human life in clinical scenarios where resource allocation is limited. The COVID-19 pandemic has fostered dialogue and debate around the ethical principles that underly such resource allocation, which generally balance (1) utilitarian optimization of resources, (2) equality or equity in health access, (3) the instrumental value of individuals as agents in society, and (4) prioritizing the “worst off” in their natural history of disease.^1,2 State legislatures and health systems have responded to the challeges posed by COVID-19 by considering both the scarcity of intensive care resources, such as mechanical ventilation and hemodialysis, and the clinical criteria to be used for determining which patients should receive said resources. These crisis guidelines have yielded several concerning themes vis-à-vis equitable distribution of health care resources, particularly when the disability status of patients is considered alongside life-expectancy or quality of life.³

Crisis standards of care (CSC) prioritize population-level health under a utilitarian paradigm, explicitly maximizing “life-years” within a population of patients rather than the life of any individual patient.⁴ Debated during initial COVID surges, these CSC guidelines have recently been enacted at the state level in several settings, including Alaska and Idaho.⁵ In a setting with scarce intensive care resources, balancing health equity in access to these resources against population-based survival metrics has been a challenge for commissions considering CSC.^6,7 This need for balance has further promoted systemic views of “disability,” raising concern for structural “ableism” and highlighting the need for greater “ability awareness” in clinicians’ continued professional learning.

Structural Ableism: Defining Perspectives to Address Health Equity

Ableism has been defined as “a system that places value on people’s bodies and minds, based on societally constructed ideas of normalcy, intelligence, excellence, and productivity…[and] leads to people and society determining who is valuable and worthy based on their appearance and/or their ability to satisfactorily [re]produce, excel, and ‘behave.’”⁸ Regarding CSC, concerns about systemic bias in guideline design were raised early by disability advocacy groups during comment periods.^9,10 More broadly, concerns about ableism sit alongside many deeply rooted societal perspectives of disabled individuals as pitiable or, conversely, heroic for having “overcome” their disability in some way. As a physician who sits in a manual wheelchair with paraplegia and mobility impairment, I have equally been subject to inappropriate bias and inappropriate praise for living in a wheelchair. I have also wondered, alongside my patients living with different levels of mobility or ability, why others often view us as “worse off.” Addressing directly whether disabled individuals are “worse off,” disability rights attorney and advocate Harriet McBryde Johnson has articulated a predominant sentiment among persons living with unique or different abilities:

Are we “worse off”? I don’t think so. Not in any meaningful way. There are too many variables. For those of us with congenital conditions, disability shapes all we are. Those disabled later in life adapt. We take constraints that no one would choose and build rich and satisfying lives within them. We enjoy pleasures other people enjoy and pleasures peculiarly our own. We have something the world needs.¹¹

Many physician colleagues have common, invisible diseases such as diabetes and heart disease; fewer colleagues share conditions that are as visible as my spinal cord injury, as readily apparent to patients upon my entry to their hospital rooms. This simultaneous and inescapable identity as both patient and provider has afforded me wonderful doctor-patient interactions, particularly with those patients who appreciate how my patient experience impacts my ability to partially understand theirs. However, this simultaneous identity as doctor and patient also informed my personal and professional concerns regarding structural ableism as I considered scoring my own acutely ill hospital medicine patients with CSC triage scores in April 2020.

As a practicing hospital medicine physician, I have been emboldened by the efforts of my fellow clinicians amid COVID-19; their efforts have reaffirmed all the reasons I pursued a career in medicine. However, when I heard my clinical colleagues’ first explanation of the Massachusetts CSC guidelines in April 2020, I raised my hand to ask whether the “life-years” to which the guidelines referred were quality-adjusted. My concern regarding the implicit use of quality-adjusted life years (QALY) or disability-adjusted life years in clinical decision-making and implementation of these guidelines was validated when no clinical leaders could address this question directly. Sitting on the CSC committee for my hospital during this time was an honor. However, it was disconcerting to hear many clinicians’ unease when estimating mean survival for common chronic diseases, ranging from end-stage renal disease to advanced heart failure. If my expert colleagues, clinical specialists in kidney and heart disease, could not confidently apply mean survival estimates to multimorbid hospital patients, then idiosyncratic clinical judgment was sure to have a heavy hand in any calculation of “life-years.” Thus, my primary concern was that clinicians using triage heuristics would be subject to bias, regardless of their intention, and negatively adjust for the quality of a disabled life in their CSC triage scoring. My secondary concern was that the CSC guidelines themselves included systemic bias against disabled individuals.

According to CSC schema, triage scores index heavily on Sequential Organ Failure Assessment (SOFA) scores to define short-term survival; SOFA scores are partially driven by the Glasgow Coma Scale (GCS). Following professional and public comment periods, CSC guidelines in Massachusetts were revised to, among other critical points of revision, change prognostic estimation via “life years” in favor of generic estimation of short-term survival (Table). I wondered, if I presented to an emergency department with severe COVID-19 and was scored with the GCS for the purpose of making a CSC ventilator triage decision, how would my complete paraplegia and lower-extremity motor impairment be accounted for by a clinician assessing “best motor response” in the GCS? The purpose of these scores is to act algorithmically, to guide clinicians whose cognitive load and time limitations may not allow for adjustment of these algorithms based on the individual patient in front of them. Individualization of clinical decisions is part of medicine’s art, but is difficult in the best of times and no easier during a crisis in care delivery. As CSC triage scores were amended and addended throughout 2020, I returned to the COVID wards, time and again wondering, “What have we learned about systemic bias and health inequity in the CSC process and the pandemic broadly, with specific regard to disability?”

Ability Awareness: Room for Our Improvement

Unfortunately, there is reason to believe that clinical judgment is impaired by structural ableism. In seminal work on this topic, Gerhart et al¹² demonstrated that clinicians considered spinal cord injury (SCI) survivors to have low self-perceptions of worthiness, overall negative attitudes, and low self-esteem as compared to able-bodied individuals. However, surveyed SCI survivors generally had similar self-perceptions of worth and positivity as compared to ”able-bodied” clinicians.¹² For providers who care for persons with disabilities, the majority (82.4%) have rated their disabled patients’ quality of life as worse.¹³ It is no wonder that patients with disabilities are more likely to feel that their doctor-patient relationship is impacted by lack of understanding, negative sentiment, or simple lack of listening.¹⁴ Generally, this poor doctor-patient relationship with disabled patients is exacerbated by poor exposure of medical trainees to disability education; only 34.2% of internal medicine residents recall any form of disability education in medical school, while only 52% of medical school deans report having disability educational content in their curricula.^15,16 There is a similar lack of disability representation in the population of medical trainees themselves. While approximately 20% of the American population lives with a disability, less than 2% of American medical students have a disability.^17-19

While representation of disabled populations in medical practice remains poor, disabled patients are generally less likely to receive age-appropriate prevention, appropriate access to care, and equal access to treatment.^20-22 “Diagnostic overshadowing” refers to clinicians’ attribution of nonspecific signs or symptoms to a patient’s chronic disability as opposed to acute illness.²³ This phenomenon has led to higher rates of preventable malignancy in disabled patients and misattribution of common somatic symptoms to intellectual disability.^24,25 With this disparity in place as status quo for health care delivery to disabled populations, it is no surprise that certain portions of the disabled population have accounted for disproportionate mortality due to COVID-19.^26,27Disability advocates have called for “nothing about us without us,” a phrase associated with the United Nations Convention on the Rights of Persons with Disabilities. Understanding the profound neurodiversity among several forms of sensory and cognitive disabilities, as well as the functional difference between cognitive disabilities, mobility impairment, and inability to meet one’s instrumental activities of daily living independently, others have proposed a unique approach to certain disabled populations in COVID care.²⁸ My own perspective is that definite progress may require a more general understanding of the prevalence of disability by clinicians, both via medical training and by directly addressing health equity for disabled populations in such calculations as the CSC. Systemic ableism is apparent in our most common clinical scoring systems, ranging from the GCS and Functional Assessment Staging Table to the Eastern Cooperative Oncology Group and Karnofsky Performance Status scales. I have reexamined these scoring systems in my own understanding given their general equation of ambulation with ability or normalcy. As a doctor in a manual wheelchair who values greatly my personal quality of life and professional contribution to patient care, I worry that these scoring systems inherently discount my own equitable access to care. Individualization of patients’ particular abilities in the context of these scales must occur alongside evidence-based, guideline-directed management via these scoring systems.

Conclusion: Future Orientation

Updated CSC guidelines have accounted for the unique considerations of disabled patients by effectively caveating their scoring algorithms, directing clinicians via disclaimers to uniquely consider their disabled patients in clinical judgement. This is a first step, but it is also one that erodes the value of algorithms, which generally obviate more deliberative thinking and individualization. For our patients who lack certain abilities, as CSC continue to be activated in several states, we have an opportunity to pursue more inherently equitable solutions before further suffering accrues.²⁹ By way of example, adaptations to scoring systems that leverage QALYs for value-based drug pricing indices have been proposed by organizations like the Institute for Clinical and Economic Review, which proposed the Equal-Value-of Life-Years-Gained framework to inform QALY-based arbitration of drug pricing.³⁰ This is not a perfect rubric but instead represents an attempt to balance consideration of drugs, as has been done with ventilators during the pandemic, as a scare and expensive resource while addressing the just concerns of advocacy groups in structural ableism.

Resource stewardship during a crisis should not discount those states of human life that are perceived to be less desirable, particularly if they are not experienced as less desirable but are experienced uniquely. Instead, we should consider equitably measuring our intervention to match a patient’s needs, as we would dose-adjust a medication for renal function or consider minimally invasive procedures for multimorbid patients. COVID-19 has reflected our profession’s ethical adaptation during crisis as resources have become scarce; there is no better time to define solutions for health equity. We should now be concerned equally by the influence our personal biases have on our clinical practice and by the way in which these crisis standards will influence patients’ perception of and trust in their care providers during periods of perceived plentiful resources in the future. Health care resources are always limited, allocated according to societal values; if we value health equity for people of all abilities, then we will consider these abilities equitably as we pursue new standards for health care delivery.

Corresponding author: Gregory D. Snyder, MD, MBA, 2014 Washington Street, Newton, MA 02462; gdsnyder@bwh.harvard.edu.

Disclosures: None.
 

Study Overview

Objective: To examine the effect of the intervention “Eat Walk Engage,” a program that is designed to more consistently deliver age-friendly principles of care to older individuals in acute medical and surgical wards.

Design: This cluster randomized trial to examine the effect of an intervention in acute medical and surgical wards on older adults was conducted in 8 acute medical and surgical wards in 4 public hospitals in Australia from 2016 to 2017. To be eligible to participate in this trial, wards had to have the following: a patient population with 50% of patients aged 65 years and older; perceived alignment with hospital priorities; and nurse manager agreement to participation. Randomization was stratified by hospital, resulting in 4 wards with the intervention (a general medicine ward, an orthopedic ward, a general surgery ward, and a respiratory medicine ward) and 4 control wards (2 general medicine wards, a respiratory medicine ward, and a general surgery ward). Participants were consecutive inpatients aged 65 years or older who were admitted to the ward for at least 3 consecutive days during the study time period. Exclusion criteria included terminal or critical illness, severe cognitive impairment without a surrogate decision-maker, non-English speaking, or previously enrolled in the trial. Of a total of 453 patients who were eligible from the intervention wards, 188 were excluded and 6 died, yielding 259 participants in the intervention group. There were 413 patients eligible from the control wards, with 139 excluded and 3 deaths, yielding 271 participants in the control group.

Intervention: The intervention, called “Eat Walk Engage,” was developed to target older adults at risk for hospital-associated complications of delirium, functional decline, pressure injuries, falls, and incontinence, and aimed to improve care practices, environment, and culture to support age-friendly principles. This ward-based program delivered a structured improvement intervention through a site facilitator who is a nurse or allied health professional. The site facilitator identified opportunities for improvement using structured assessments of context, patient-experience interviews, and audits of care processes, and engaged an interdisciplinary working group from the intervention wards to participate in an hour-per-month meeting to develop plans for iterative improvements. Each site developed their own intervention plan; examples of interventions include shifting priorities to enable staff to increase the proportion of patients sitting in a chair for meals; designating the patient lounge as a walking destination to increase the proportion of time patients spend mobile; and using orientation boards and small groups to engage older patients in meaningful activities.

Main outcome measures: Study outcome measures included hospital-associated complications for older people, which is a composite of hospital-associated delirium, hospital-associated disability, hospital-associated incontinence, and fall or pressure injury during hospitalization. Delirium was assessed using the 3-minute diagnostic interview for Confusion Assessment Method (3D-CAM); hospital-associated disability was defined as new disability at discharge compared to 2 weeks prior to hospitalization. The primary outcome was defined as incidence of any complications and hospital length of stay. Secondary outcomes included incidence of individual complications, hospital discharge to facility, mortality at 6 months, and readmission for any cause at 6 months.

Main results: Patient characteristics for the intervention and control groups, respectively, were: 47% women with a mean age of 75.9 years (SD, 7.3), and 53% women with a mean age of 78.0 years (SD, 8.2). For the primary outcome, 46.4% of participants in the intervention group experienced any hospital complications compared with 51.8% in the control group (odds ratio [OR], 1.07; 95% CI, 0.71-1.61). The incidence of delirium was lower in the intervention group as compared with the control group (15.9% vs 31.4%; OR, 0.53; 95% CI, 0.31-0.90), while there were no other differences in the incidence rates of other complications. There was also no difference in hospital length of stay; median length of stay in the intervention group was 6 days (interquartile range [IQR], 4-9 days) compared with 7 days in the control group (IQR, 5-10), with an estimated mean difference in length of stay of 0.16 days (95% CI, –0.43 to 0.78 days). There was also no significant difference in mortality or all-cause readmission at 6 months.

Conclusion: The intervention “Eat Walk Engage” did not reduce hospital-associated complications overall or hospital length of stay, but it did reduce the incidence of hospital-associated delirium.

 

 

Commentary

Older adults, often with reduced physiologic reserve, when admitted to the hospital with an acute illness may be vulnerable to potential hazards of hospitalization, such as complications from prolonged periods of immobility, pressure injury, and delirium.¹ Models of care in the inpatient setting to reduce these hazards, including the Acute Care for the Elderly model and the Mobile Acute Care for the Elderly Team model, have been examined in clinical trials.^2,3 Specifically, models of care to prevent and treat delirium have been developed and tested over the past decade.⁴ The effect of these models in improving function, reducing complications, and reducing delirium incidence has been well documented. The present study adds to the literature by testing a model that utilizes implementation science methods to take into account real-world settings. In contrast with prior models-of-care studies, the implementation of the intervention at each ward was not prescriptive, but rather was developed in each ward in an iterative manner with stakeholder input. The advantage of this approach is that engagement of stakeholders at each intervention ward obtains buy-in from staff, mobilizing staff in a way that a prescriptive model of care may not; this ultimately may lead to longer-lasting change. The iterative approach also allows for the intervention to be adapted to conditions and settings over time. Other studies have taken this approach of using implementation science to drive change.⁵ Although the intervention in the present study failed to improve the primary outcome, it did reduce the incidence of delirium, which is a significant outcome and one that may confer considerable benefits to older adults under the model’s care.

A limitation of the intervention’s nonprescriptive approach is that, because of the variation of the interventions across sites, it is difficult to discern what elements drove the clinical outcomes. In addition, it would be challenging to consider what aspects of the intervention did not work should refinement or changes be needed. How one may measure fidelity to the intervention or how well a site implements the intervention and its relationship with clinical outcomes will need to be examined further.

Application for Clinical Practice

Clinicians look to effective models of care to improve clinical outcomes for older adults in the hospital. The intervention described in this study offers a real-world approach that may need less upfront investment than other recently studied models, such as the Acute Care for the Elderly model, which requires structural and staffing enhancements. Clinicians and health system leaders may consider implementing this model to improve the care delivered to older adults in the hospital as it may help reduce the incidence of delirium among the older adults they serve.

–William W. Hung, MD, MPH

Disclosures: None.

 

Study Overview

Objective: To examine the effect of the intervention “Eat Walk Engage,” a program that is designed to more consistently deliver age-friendly principles of care to older individuals in acute medical and surgical wards.

Design: This cluster randomized trial to examine the effect of an intervention in acute medical and surgical wards on older adults was conducted in 8 acute medical and surgical wards in 4 public hospitals in Australia from 2016 to 2017. To be eligible to participate in this trial, wards had to have the following: a patient population with 50% of patients aged 65 years and older; perceived alignment with hospital priorities; and nurse manager agreement to participation. Randomization was stratified by hospital, resulting in 4 wards with the intervention (a general medicine ward, an orthopedic ward, a general surgery ward, and a respiratory medicine ward) and 4 control wards (2 general medicine wards, a respiratory medicine ward, and a general surgery ward). Participants were consecutive inpatients aged 65 years or older who were admitted to the ward for at least 3 consecutive days during the study time period. Exclusion criteria included terminal or critical illness, severe cognitive impairment without a surrogate decision-maker, non-English speaking, or previously enrolled in the trial. Of a total of 453 patients who were eligible from the intervention wards, 188 were excluded and 6 died, yielding 259 participants in the intervention group. There were 413 patients eligible from the control wards, with 139 excluded and 3 deaths, yielding 271 participants in the control group.

Intervention: The intervention, called “Eat Walk Engage,” was developed to target older adults at risk for hospital-associated complications of delirium, functional decline, pressure injuries, falls, and incontinence, and aimed to improve care practices, environment, and culture to support age-friendly principles. This ward-based program delivered a structured improvement intervention through a site facilitator who is a nurse or allied health professional. The site facilitator identified opportunities for improvement using structured assessments of context, patient-experience interviews, and audits of care processes, and engaged an interdisciplinary working group from the intervention wards to participate in an hour-per-month meeting to develop plans for iterative improvements. Each site developed their own intervention plan; examples of interventions include shifting priorities to enable staff to increase the proportion of patients sitting in a chair for meals; designating the patient lounge as a walking destination to increase the proportion of time patients spend mobile; and using orientation boards and small groups to engage older patients in meaningful activities.

Main outcome measures: Study outcome measures included hospital-associated complications for older people, which is a composite of hospital-associated delirium, hospital-associated disability, hospital-associated incontinence, and fall or pressure injury during hospitalization. Delirium was assessed using the 3-minute diagnostic interview for Confusion Assessment Method (3D-CAM); hospital-associated disability was defined as new disability at discharge compared to 2 weeks prior to hospitalization. The primary outcome was defined as incidence of any complications and hospital length of stay. Secondary outcomes included incidence of individual complications, hospital discharge to facility, mortality at 6 months, and readmission for any cause at 6 months.

Main results: Patient characteristics for the intervention and control groups, respectively, were: 47% women with a mean age of 75.9 years (SD, 7.3), and 53% women with a mean age of 78.0 years (SD, 8.2). For the primary outcome, 46.4% of participants in the intervention group experienced any hospital complications compared with 51.8% in the control group (odds ratio [OR], 1.07; 95% CI, 0.71-1.61). The incidence of delirium was lower in the intervention group as compared with the control group (15.9% vs 31.4%; OR, 0.53; 95% CI, 0.31-0.90), while there were no other differences in the incidence rates of other complications. There was also no difference in hospital length of stay; median length of stay in the intervention group was 6 days (interquartile range [IQR], 4-9 days) compared with 7 days in the control group (IQR, 5-10), with an estimated mean difference in length of stay of 0.16 days (95% CI, –0.43 to 0.78 days). There was also no significant difference in mortality or all-cause readmission at 6 months.

Conclusion: The intervention “Eat Walk Engage” did not reduce hospital-associated complications overall or hospital length of stay, but it did reduce the incidence of hospital-associated delirium.

 

 

Commentary

Older adults, often with reduced physiologic reserve, when admitted to the hospital with an acute illness may be vulnerable to potential hazards of hospitalization, such as complications from prolonged periods of immobility, pressure injury, and delirium.¹ Models of care in the inpatient setting to reduce these hazards, including the Acute Care for the Elderly model and the Mobile Acute Care for the Elderly Team model, have been examined in clinical trials.^2,3 Specifically, models of care to prevent and treat delirium have been developed and tested over the past decade.⁴ The effect of these models in improving function, reducing complications, and reducing delirium incidence has been well documented. The present study adds to the literature by testing a model that utilizes implementation science methods to take into account real-world settings. In contrast with prior models-of-care studies, the implementation of the intervention at each ward was not prescriptive, but rather was developed in each ward in an iterative manner with stakeholder input. The advantage of this approach is that engagement of stakeholders at each intervention ward obtains buy-in from staff, mobilizing staff in a way that a prescriptive model of care may not; this ultimately may lead to longer-lasting change. The iterative approach also allows for the intervention to be adapted to conditions and settings over time. Other studies have taken this approach of using implementation science to drive change.⁵ Although the intervention in the present study failed to improve the primary outcome, it did reduce the incidence of delirium, which is a significant outcome and one that may confer considerable benefits to older adults under the model’s care.

A limitation of the intervention’s nonprescriptive approach is that, because of the variation of the interventions across sites, it is difficult to discern what elements drove the clinical outcomes. In addition, it would be challenging to consider what aspects of the intervention did not work should refinement or changes be needed. How one may measure fidelity to the intervention or how well a site implements the intervention and its relationship with clinical outcomes will need to be examined further.

Application for Clinical Practice

Clinicians look to effective models of care to improve clinical outcomes for older adults in the hospital. The intervention described in this study offers a real-world approach that may need less upfront investment than other recently studied models, such as the Acute Care for the Elderly model, which requires structural and staffing enhancements. Clinicians and health system leaders may consider implementing this model to improve the care delivered to older adults in the hospital as it may help reduce the incidence of delirium among the older adults they serve.

–William W. Hung, MD, MPH

Disclosures: None.

 

Study Overview

Objective: To examine the effect of the intervention “Eat Walk Engage,” a program that is designed to more consistently deliver age-friendly principles of care to older individuals in acute medical and surgical wards.

Design: This cluster randomized trial to examine the effect of an intervention in acute medical and surgical wards on older adults was conducted in 8 acute medical and surgical wards in 4 public hospitals in Australia from 2016 to 2017. To be eligible to participate in this trial, wards had to have the following: a patient population with 50% of patients aged 65 years and older; perceived alignment with hospital priorities; and nurse manager agreement to participation. Randomization was stratified by hospital, resulting in 4 wards with the intervention (a general medicine ward, an orthopedic ward, a general surgery ward, and a respiratory medicine ward) and 4 control wards (2 general medicine wards, a respiratory medicine ward, and a general surgery ward). Participants were consecutive inpatients aged 65 years or older who were admitted to the ward for at least 3 consecutive days during the study time period. Exclusion criteria included terminal or critical illness, severe cognitive impairment without a surrogate decision-maker, non-English speaking, or previously enrolled in the trial. Of a total of 453 patients who were eligible from the intervention wards, 188 were excluded and 6 died, yielding 259 participants in the intervention group. There were 413 patients eligible from the control wards, with 139 excluded and 3 deaths, yielding 271 participants in the control group.

Intervention: The intervention, called “Eat Walk Engage,” was developed to target older adults at risk for hospital-associated complications of delirium, functional decline, pressure injuries, falls, and incontinence, and aimed to improve care practices, environment, and culture to support age-friendly principles. This ward-based program delivered a structured improvement intervention through a site facilitator who is a nurse or allied health professional. The site facilitator identified opportunities for improvement using structured assessments of context, patient-experience interviews, and audits of care processes, and engaged an interdisciplinary working group from the intervention wards to participate in an hour-per-month meeting to develop plans for iterative improvements. Each site developed their own intervention plan; examples of interventions include shifting priorities to enable staff to increase the proportion of patients sitting in a chair for meals; designating the patient lounge as a walking destination to increase the proportion of time patients spend mobile; and using orientation boards and small groups to engage older patients in meaningful activities.

Main outcome measures: Study outcome measures included hospital-associated complications for older people, which is a composite of hospital-associated delirium, hospital-associated disability, hospital-associated incontinence, and fall or pressure injury during hospitalization. Delirium was assessed using the 3-minute diagnostic interview for Confusion Assessment Method (3D-CAM); hospital-associated disability was defined as new disability at discharge compared to 2 weeks prior to hospitalization. The primary outcome was defined as incidence of any complications and hospital length of stay. Secondary outcomes included incidence of individual complications, hospital discharge to facility, mortality at 6 months, and readmission for any cause at 6 months.

Main results: Patient characteristics for the intervention and control groups, respectively, were: 47% women with a mean age of 75.9 years (SD, 7.3), and 53% women with a mean age of 78.0 years (SD, 8.2). For the primary outcome, 46.4% of participants in the intervention group experienced any hospital complications compared with 51.8% in the control group (odds ratio [OR], 1.07; 95% CI, 0.71-1.61). The incidence of delirium was lower in the intervention group as compared with the control group (15.9% vs 31.4%; OR, 0.53; 95% CI, 0.31-0.90), while there were no other differences in the incidence rates of other complications. There was also no difference in hospital length of stay; median length of stay in the intervention group was 6 days (interquartile range [IQR], 4-9 days) compared with 7 days in the control group (IQR, 5-10), with an estimated mean difference in length of stay of 0.16 days (95% CI, –0.43 to 0.78 days). There was also no significant difference in mortality or all-cause readmission at 6 months.

Conclusion: The intervention “Eat Walk Engage” did not reduce hospital-associated complications overall or hospital length of stay, but it did reduce the incidence of hospital-associated delirium.

 

 

Commentary

Older adults, often with reduced physiologic reserve, when admitted to the hospital with an acute illness may be vulnerable to potential hazards of hospitalization, such as complications from prolonged periods of immobility, pressure injury, and delirium.¹ Models of care in the inpatient setting to reduce these hazards, including the Acute Care for the Elderly model and the Mobile Acute Care for the Elderly Team model, have been examined in clinical trials.^2,3 Specifically, models of care to prevent and treat delirium have been developed and tested over the past decade.⁴ The effect of these models in improving function, reducing complications, and reducing delirium incidence has been well documented. The present study adds to the literature by testing a model that utilizes implementation science methods to take into account real-world settings. In contrast with prior models-of-care studies, the implementation of the intervention at each ward was not prescriptive, but rather was developed in each ward in an iterative manner with stakeholder input. The advantage of this approach is that engagement of stakeholders at each intervention ward obtains buy-in from staff, mobilizing staff in a way that a prescriptive model of care may not; this ultimately may lead to longer-lasting change. The iterative approach also allows for the intervention to be adapted to conditions and settings over time. Other studies have taken this approach of using implementation science to drive change.⁵ Although the intervention in the present study failed to improve the primary outcome, it did reduce the incidence of delirium, which is a significant outcome and one that may confer considerable benefits to older adults under the model’s care.

A limitation of the intervention’s nonprescriptive approach is that, because of the variation of the interventions across sites, it is difficult to discern what elements drove the clinical outcomes. In addition, it would be challenging to consider what aspects of the intervention did not work should refinement or changes be needed. How one may measure fidelity to the intervention or how well a site implements the intervention and its relationship with clinical outcomes will need to be examined further.

Application for Clinical Practice

Clinicians look to effective models of care to improve clinical outcomes for older adults in the hospital. The intervention described in this study offers a real-world approach that may need less upfront investment than other recently studied models, such as the Acute Care for the Elderly model, which requires structural and staffing enhancements. Clinicians and health system leaders may consider implementing this model to improve the care delivered to older adults in the hospital as it may help reduce the incidence of delirium among the older adults they serve.

–William W. Hung, MD, MPH

Disclosures: None.

 

Study Overview

Objective: To determine whether fractional flow reserve (FFR)–guided percutaneous coronary intervention (PCI) is noninferior to coronary-artery bypass grafting (CABG) in patients with 3-vessel coronary artery disease (CAD).

Design: Investigator-initiated, multicenter, international, randomized, controlled trial conducted at 48 sites.

Setting and participants: A total of 1500 patients with angiographically identified 3-vessel CAD not involving the left main coronary artery were randomly assigned to receive FFR-guided PCI with zotarolimus-eluting stents or CABG in a 1:1 ratio. Randomization was stratified according to trial site and diabetes status.

Main outcome measures: The primary end point was major adverse cardiac or cerebrovascular event, defined as death from any cause, myocardial infarction (MI), stroke, or repeat revascularization. The secondary end point was defined as a composite of death, MI, or stroke.

Results: At 1 year, the incidence of the composite primary end point was 10.6% for patients with FFR-guided PCI and 6.9% for patients with CABG (hazard ratio [HR], 1.5; 95% CI, 1.1-2.2; P = .35 for noninferiority), which was not consistent with noninferiority of FFR-guided PCI compared to CABG. The secondary end point occurred in 7.3% of patients in the FFR-guided PCI group compared with 5.2% in the CABG group (HR, 1.4; 95% CI, 0.9-2.1). Individual findings for the outcomes comprising the primary end point for the FFR-guided PCI group vs the CABG group were as follows: death, 1.6% vs 0.9%; MI, 5.2% vs 3.5%; stroke, 0.9% vs 1.1%; and repeat revascularization, 5.9% vs 3.9%. The CABG group had more extended hospital stays and higher incidences of major bleeding, arrhythmia, acute kidney injury, and rehospitalization within 30 days than the FFR-guided PCI group.

Conclusion: FFR-guided PCI was not found to be noninferior to CABG with respect to the incidence of a composite of death, MI, stroke, or repeat revascularization at 1 year.

Commentary

Revascularization for multivessel CAD can be performed by CABG or PCI. Previous studies have shown superior outcomes in patients with multivessel CAD who were treated with CABG compared to PCI.^1-3 The Synergy between PCI with Taxus and Cardiac Surgery (SYNTAX) trial, which compared CABG to PCI in patients with multivessel disease or unprotected left main CAD, stratified the anatomic complexity based on SYNTAX score and found that patients with higher anatomic complexity with a high SYNTAX score derive larger benefit from CABG compared to PCI.⁴ Therefore, the current guidelines favor CABG over PCI in patients with severe 3-vessel disease, except for patients with a lower SYNTAX score (<22) without diabetes.^5,6 However, except for a smaller size study,³ the previous trials that led to this recommendation used mostly first-generation drug-eluting stents and have not evaluated second-generation stents that have lower rates of in-stent restenosis and stent thrombosis. In addition, there have been significant improvements in PCI techniques since the study period, including the adoption of a radial approach and superior adjunct pharmacologic therapy. Furthermore, previous studies have not systematically investigated the use of FFR-guided PCI, which has been shown to be superior to angiography-guided PCI or medical treatment alone.^7-9

In this context, Fearon and the FAME-3 trial investigators studied the use of FFR-guided PCI with second-generation zotarolimus drug-eluting stents compared to CABG in patients with 3-vessel CAD. They randomized patients with angiographically identified 3-vessel CAD in a 1:1 ratio to receive FFR-guided PCI or CABG at 48 sites internationally. Patients with left main CAD, recent ST-elevation MI, cardiogenic shock, and left-ventricular ejection fraction <30% were excluded. The study results (composite primary end point incidence of 10.6% for patients with FFR-guided PCI vs 6.9% in the CABG group [HR, 1.5; 95% CI, 1.1-2.2; P = 0.35 for noninferiority]) showed that FFR-guided PCI did not meet the noninferiority criterion.

Although the FAME-3 study is an important study, there are a few points to consider. First, 24% of the lesions had a FFR measured at >0.80. The benefit of FFR-guided PCI lies in the number of lesions that are safely deferred compared to angiography-guided PCI. The small number of deferred lesions could have limited the benefit of FFR guidance compared with angiography. Second, this study did not include all comers who had angiographic 3-vessel disease. Patients who had FFR assessment of moderate lesions at the time of diagnostic angiogram and were found to have FFR >0.80 or were deemed single- or 2-vessel disease were likely treated with PCI. Therefore, as the authors point out, the patients included in this study may have been skewed to a higher-risk population compared to previous studies.

Third, the study may not reflect contemporary interventional practice, as the use of intravascular ultrasound was very low (12%). Intravascular ultrasound–guided PCI has been associated with increased luminal gain and improved outcomes compared to angiography-guided PCI.¹⁰ Although 20% of the patients in each arm were found to have chronic total occlusions, the completeness of revascularization has not yet been reported. It is possible that the PCI arm had fewer complete revascularizations, which has been shown in previous observational studies to be associated with worse clinical outcomes.^11,12

Although the current guidelines favor CABG over PCI in patients with multivessel disease, this recommendation is stratified by anatomic complexity.⁶ In fact, in the European guidelines, CABG and PCI are both class I recommendations for the treatment of 3-vessel disease with low SYNTAX score in patients without diabetes.⁵ Although the FAME-3 study failed to show noninferiority in the overall population, when stratified by the SYNTAX score, the major adverse cardiac event rate for the PCI group was numerically lower than that of the CABG group. The results from the FAME-3 study are overall in line with the previous studies and the current guidelines. Future studies are necessary to assess the outcomes of multivessel PCI compared to CABG using the most contemporary interventional practice and achieving complete revascularization in the PCI arm.

Applications for Clinical Practice

In patients with 3-vessel disease, FFR-guided PCI was not found to be noninferior to CABG; this finding is consistent with previous studies.

—Shubham Kanake, BS, Chirag Bavishi, MD, MPH, and Taishi Hirai, MD, University of Missouri, Columbia, MO

Disclosures: None.

Study Overview

Objective: To determine whether fractional flow reserve (FFR)–guided percutaneous coronary intervention (PCI) is noninferior to coronary-artery bypass grafting (CABG) in patients with 3-vessel coronary artery disease (CAD).

Design: Investigator-initiated, multicenter, international, randomized, controlled trial conducted at 48 sites.

Setting and participants: A total of 1500 patients with angiographically identified 3-vessel CAD not involving the left main coronary artery were randomly assigned to receive FFR-guided PCI with zotarolimus-eluting stents or CABG in a 1:1 ratio. Randomization was stratified according to trial site and diabetes status.

Main outcome measures: The primary end point was major adverse cardiac or cerebrovascular event, defined as death from any cause, myocardial infarction (MI), stroke, or repeat revascularization. The secondary end point was defined as a composite of death, MI, or stroke.

Results: At 1 year, the incidence of the composite primary end point was 10.6% for patients with FFR-guided PCI and 6.9% for patients with CABG (hazard ratio [HR], 1.5; 95% CI, 1.1-2.2; P = .35 for noninferiority), which was not consistent with noninferiority of FFR-guided PCI compared to CABG. The secondary end point occurred in 7.3% of patients in the FFR-guided PCI group compared with 5.2% in the CABG group (HR, 1.4; 95% CI, 0.9-2.1). Individual findings for the outcomes comprising the primary end point for the FFR-guided PCI group vs the CABG group were as follows: death, 1.6% vs 0.9%; MI, 5.2% vs 3.5%; stroke, 0.9% vs 1.1%; and repeat revascularization, 5.9% vs 3.9%. The CABG group had more extended hospital stays and higher incidences of major bleeding, arrhythmia, acute kidney injury, and rehospitalization within 30 days than the FFR-guided PCI group.

Conclusion: FFR-guided PCI was not found to be noninferior to CABG with respect to the incidence of a composite of death, MI, stroke, or repeat revascularization at 1 year.

Commentary

Revascularization for multivessel CAD can be performed by CABG or PCI. Previous studies have shown superior outcomes in patients with multivessel CAD who were treated with CABG compared to PCI.^1-3 The Synergy between PCI with Taxus and Cardiac Surgery (SYNTAX) trial, which compared CABG to PCI in patients with multivessel disease or unprotected left main CAD, stratified the anatomic complexity based on SYNTAX score and found that patients with higher anatomic complexity with a high SYNTAX score derive larger benefit from CABG compared to PCI.⁴ Therefore, the current guidelines favor CABG over PCI in patients with severe 3-vessel disease, except for patients with a lower SYNTAX score (<22) without diabetes.^5,6 However, except for a smaller size study,³ the previous trials that led to this recommendation used mostly first-generation drug-eluting stents and have not evaluated second-generation stents that have lower rates of in-stent restenosis and stent thrombosis. In addition, there have been significant improvements in PCI techniques since the study period, including the adoption of a radial approach and superior adjunct pharmacologic therapy. Furthermore, previous studies have not systematically investigated the use of FFR-guided PCI, which has been shown to be superior to angiography-guided PCI or medical treatment alone.^7-9

In this context, Fearon and the FAME-3 trial investigators studied the use of FFR-guided PCI with second-generation zotarolimus drug-eluting stents compared to CABG in patients with 3-vessel CAD. They randomized patients with angiographically identified 3-vessel CAD in a 1:1 ratio to receive FFR-guided PCI or CABG at 48 sites internationally. Patients with left main CAD, recent ST-elevation MI, cardiogenic shock, and left-ventricular ejection fraction <30% were excluded. The study results (composite primary end point incidence of 10.6% for patients with FFR-guided PCI vs 6.9% in the CABG group [HR, 1.5; 95% CI, 1.1-2.2; P = 0.35 for noninferiority]) showed that FFR-guided PCI did not meet the noninferiority criterion.

Although the FAME-3 study is an important study, there are a few points to consider. First, 24% of the lesions had a FFR measured at >0.80. The benefit of FFR-guided PCI lies in the number of lesions that are safely deferred compared to angiography-guided PCI. The small number of deferred lesions could have limited the benefit of FFR guidance compared with angiography. Second, this study did not include all comers who had angiographic 3-vessel disease. Patients who had FFR assessment of moderate lesions at the time of diagnostic angiogram and were found to have FFR >0.80 or were deemed single- or 2-vessel disease were likely treated with PCI. Therefore, as the authors point out, the patients included in this study may have been skewed to a higher-risk population compared to previous studies.

Third, the study may not reflect contemporary interventional practice, as the use of intravascular ultrasound was very low (12%). Intravascular ultrasound–guided PCI has been associated with increased luminal gain and improved outcomes compared to angiography-guided PCI.¹⁰ Although 20% of the patients in each arm were found to have chronic total occlusions, the completeness of revascularization has not yet been reported. It is possible that the PCI arm had fewer complete revascularizations, which has been shown in previous observational studies to be associated with worse clinical outcomes.^11,12

Although the current guidelines favor CABG over PCI in patients with multivessel disease, this recommendation is stratified by anatomic complexity.⁶ In fact, in the European guidelines, CABG and PCI are both class I recommendations for the treatment of 3-vessel disease with low SYNTAX score in patients without diabetes.⁵ Although the FAME-3 study failed to show noninferiority in the overall population, when stratified by the SYNTAX score, the major adverse cardiac event rate for the PCI group was numerically lower than that of the CABG group. The results from the FAME-3 study are overall in line with the previous studies and the current guidelines. Future studies are necessary to assess the outcomes of multivessel PCI compared to CABG using the most contemporary interventional practice and achieving complete revascularization in the PCI arm.

Applications for Clinical Practice

In patients with 3-vessel disease, FFR-guided PCI was not found to be noninferior to CABG; this finding is consistent with previous studies.

—Shubham Kanake, BS, Chirag Bavishi, MD, MPH, and Taishi Hirai, MD, University of Missouri, Columbia, MO

Disclosures: None.

Study Overview

Objective: To determine whether fractional flow reserve (FFR)–guided percutaneous coronary intervention (PCI) is noninferior to coronary-artery bypass grafting (CABG) in patients with 3-vessel coronary artery disease (CAD).

Design: Investigator-initiated, multicenter, international, randomized, controlled trial conducted at 48 sites.

Setting and participants: A total of 1500 patients with angiographically identified 3-vessel CAD not involving the left main coronary artery were randomly assigned to receive FFR-guided PCI with zotarolimus-eluting stents or CABG in a 1:1 ratio. Randomization was stratified according to trial site and diabetes status.

Main outcome measures: The primary end point was major adverse cardiac or cerebrovascular event, defined as death from any cause, myocardial infarction (MI), stroke, or repeat revascularization. The secondary end point was defined as a composite of death, MI, or stroke.

Results: At 1 year, the incidence of the composite primary end point was 10.6% for patients with FFR-guided PCI and 6.9% for patients with CABG (hazard ratio [HR], 1.5; 95% CI, 1.1-2.2; P = .35 for noninferiority), which was not consistent with noninferiority of FFR-guided PCI compared to CABG. The secondary end point occurred in 7.3% of patients in the FFR-guided PCI group compared with 5.2% in the CABG group (HR, 1.4; 95% CI, 0.9-2.1). Individual findings for the outcomes comprising the primary end point for the FFR-guided PCI group vs the CABG group were as follows: death, 1.6% vs 0.9%; MI, 5.2% vs 3.5%; stroke, 0.9% vs 1.1%; and repeat revascularization, 5.9% vs 3.9%. The CABG group had more extended hospital stays and higher incidences of major bleeding, arrhythmia, acute kidney injury, and rehospitalization within 30 days than the FFR-guided PCI group.

Conclusion: FFR-guided PCI was not found to be noninferior to CABG with respect to the incidence of a composite of death, MI, stroke, or repeat revascularization at 1 year.

Commentary

Revascularization for multivessel CAD can be performed by CABG or PCI. Previous studies have shown superior outcomes in patients with multivessel CAD who were treated with CABG compared to PCI.^1-3 The Synergy between PCI with Taxus and Cardiac Surgery (SYNTAX) trial, which compared CABG to PCI in patients with multivessel disease or unprotected left main CAD, stratified the anatomic complexity based on SYNTAX score and found that patients with higher anatomic complexity with a high SYNTAX score derive larger benefit from CABG compared to PCI.⁴ Therefore, the current guidelines favor CABG over PCI in patients with severe 3-vessel disease, except for patients with a lower SYNTAX score (<22) without diabetes.^5,6 However, except for a smaller size study,³ the previous trials that led to this recommendation used mostly first-generation drug-eluting stents and have not evaluated second-generation stents that have lower rates of in-stent restenosis and stent thrombosis. In addition, there have been significant improvements in PCI techniques since the study period, including the adoption of a radial approach and superior adjunct pharmacologic therapy. Furthermore, previous studies have not systematically investigated the use of FFR-guided PCI, which has been shown to be superior to angiography-guided PCI or medical treatment alone.^7-9

In this context, Fearon and the FAME-3 trial investigators studied the use of FFR-guided PCI with second-generation zotarolimus drug-eluting stents compared to CABG in patients with 3-vessel CAD. They randomized patients with angiographically identified 3-vessel CAD in a 1:1 ratio to receive FFR-guided PCI or CABG at 48 sites internationally. Patients with left main CAD, recent ST-elevation MI, cardiogenic shock, and left-ventricular ejection fraction <30% were excluded. The study results (composite primary end point incidence of 10.6% for patients with FFR-guided PCI vs 6.9% in the CABG group [HR, 1.5; 95% CI, 1.1-2.2; P = 0.35 for noninferiority]) showed that FFR-guided PCI did not meet the noninferiority criterion.

Although the FAME-3 study is an important study, there are a few points to consider. First, 24% of the lesions had a FFR measured at >0.80. The benefit of FFR-guided PCI lies in the number of lesions that are safely deferred compared to angiography-guided PCI. The small number of deferred lesions could have limited the benefit of FFR guidance compared with angiography. Second, this study did not include all comers who had angiographic 3-vessel disease. Patients who had FFR assessment of moderate lesions at the time of diagnostic angiogram and were found to have FFR >0.80 or were deemed single- or 2-vessel disease were likely treated with PCI. Therefore, as the authors point out, the patients included in this study may have been skewed to a higher-risk population compared to previous studies.

Third, the study may not reflect contemporary interventional practice, as the use of intravascular ultrasound was very low (12%). Intravascular ultrasound–guided PCI has been associated with increased luminal gain and improved outcomes compared to angiography-guided PCI.¹⁰ Although 20% of the patients in each arm were found to have chronic total occlusions, the completeness of revascularization has not yet been reported. It is possible that the PCI arm had fewer complete revascularizations, which has been shown in previous observational studies to be associated with worse clinical outcomes.^11,12

Although the current guidelines favor CABG over PCI in patients with multivessel disease, this recommendation is stratified by anatomic complexity.⁶ In fact, in the European guidelines, CABG and PCI are both class I recommendations for the treatment of 3-vessel disease with low SYNTAX score in patients without diabetes.⁵ Although the FAME-3 study failed to show noninferiority in the overall population, when stratified by the SYNTAX score, the major adverse cardiac event rate for the PCI group was numerically lower than that of the CABG group. The results from the FAME-3 study are overall in line with the previous studies and the current guidelines. Future studies are necessary to assess the outcomes of multivessel PCI compared to CABG using the most contemporary interventional practice and achieving complete revascularization in the PCI arm.

Applications for Clinical Practice

In patients with 3-vessel disease, FFR-guided PCI was not found to be noninferior to CABG; this finding is consistent with previous studies.

—Shubham Kanake, BS, Chirag Bavishi, MD, MPH, and Taishi Hirai, MD, University of Missouri, Columbia, MO

Disclosures: None.

Routine checks of vital signs during the night often prevent hospitalized patients from getting sufficient recuperative sleep. But patients who are judged to be clinically stable by an algorithm that uses real-time data can be safely spared these checks, according to a recent study published in JAMA Internal Medicine.

In their study, Nader Najafi, MD, MAS, from the University of California, San Francisco, and his colleagues were able to significantly reduce the number of checks at night without increasing transfers to the intensive care ward or heart-alarm triggers.

“Sleep is crucial to health,” writes Hyung J. Cho, MD, from the New York University Grossman School of Medicine, in an accompanying editorial. “Ironically, hospitals, where people go to recover from illness, are among the most difficult places to sleep.”

Number of night-time checks successfully reduced

The mean number of night-time checks was significantly lower in the algorithm group than in the standard-care group (0.97 vs. 1.41; P < .001).

The reduction in night-time checks had no effect on patient safety. There was no increase in transfers to the intensive care unit in the algorithm or standard-care groups (5% vs 5%; P = .92), and no difference between the number of heart alarms (0.2% vs. 0.9%; P = .07).

However, the reduction also had no effect on the incidence of episodes of delirium in the algorithm or standard-care groups (11% vs. 13%; P = .32).

“The reduction in vital signs checking, although statistically significant, was relatively small,” Dr. Cho explains. But the primary endpoint might have been different had the adherence to intervention been better, he notes.

In fact, the analysis confirmed that changes to routine daily practice in a hospital are not always easy to implement. In 35% of cases, the patients’ vital signs were checked at night, despite the physician’s order to the contrary.

“Busy patient-care assistants and nurses may check vital signs out of habit without noticing that the order has changed for some of the patients,” Dr. Najafi and his coauthors write. Many hospitals are used to thinking that regular measurements of the vital signs are part of good practice.
 

Include nursing staff

Future projects should use an interdisciplinary approach that includes nursing staff, Dr. Cho recommends. More user-friendly displays and optimized alerts in the electronic patient records could also encourage better implementation of the orders.

Less frequent checks of the vital signs would be welcomed by frontline staff because it would lighten their already heavy workload, he adds.

Although the study didn’t meet its primary endpoint, patients subjected to fewer night-time checks because of the algorithm were able to get a good night’s sleep. Other aspects of hospital care that are based on the patient’s stability, such as cardiac monitoring, could also potentially benefit from this type of intervention, Dr. Najafi and his colleagues suggest.

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

Routine checks of vital signs during the night often prevent hospitalized patients from getting sufficient recuperative sleep. But patients who are judged to be clinically stable by an algorithm that uses real-time data can be safely spared these checks, according to a recent study published in JAMA Internal Medicine.

In their study, Nader Najafi, MD, MAS, from the University of California, San Francisco, and his colleagues were able to significantly reduce the number of checks at night without increasing transfers to the intensive care ward or heart-alarm triggers.

“Sleep is crucial to health,” writes Hyung J. Cho, MD, from the New York University Grossman School of Medicine, in an accompanying editorial. “Ironically, hospitals, where people go to recover from illness, are among the most difficult places to sleep.”

Number of night-time checks successfully reduced

The mean number of night-time checks was significantly lower in the algorithm group than in the standard-care group (0.97 vs. 1.41; P < .001).

The reduction in night-time checks had no effect on patient safety. There was no increase in transfers to the intensive care unit in the algorithm or standard-care groups (5% vs 5%; P = .92), and no difference between the number of heart alarms (0.2% vs. 0.9%; P = .07).

However, the reduction also had no effect on the incidence of episodes of delirium in the algorithm or standard-care groups (11% vs. 13%; P = .32).

“The reduction in vital signs checking, although statistically significant, was relatively small,” Dr. Cho explains. But the primary endpoint might have been different had the adherence to intervention been better, he notes.

In fact, the analysis confirmed that changes to routine daily practice in a hospital are not always easy to implement. In 35% of cases, the patients’ vital signs were checked at night, despite the physician’s order to the contrary.

“Busy patient-care assistants and nurses may check vital signs out of habit without noticing that the order has changed for some of the patients,” Dr. Najafi and his coauthors write. Many hospitals are used to thinking that regular measurements of the vital signs are part of good practice.
 

Include nursing staff

Future projects should use an interdisciplinary approach that includes nursing staff, Dr. Cho recommends. More user-friendly displays and optimized alerts in the electronic patient records could also encourage better implementation of the orders.

Less frequent checks of the vital signs would be welcomed by frontline staff because it would lighten their already heavy workload, he adds.

Although the study didn’t meet its primary endpoint, patients subjected to fewer night-time checks because of the algorithm were able to get a good night’s sleep. Other aspects of hospital care that are based on the patient’s stability, such as cardiac monitoring, could also potentially benefit from this type of intervention, Dr. Najafi and his colleagues suggest.

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

Routine checks of vital signs during the night often prevent hospitalized patients from getting sufficient recuperative sleep. But patients who are judged to be clinically stable by an algorithm that uses real-time data can be safely spared these checks, according to a recent study published in JAMA Internal Medicine.

In their study, Nader Najafi, MD, MAS, from the University of California, San Francisco, and his colleagues were able to significantly reduce the number of checks at night without increasing transfers to the intensive care ward or heart-alarm triggers.

“Sleep is crucial to health,” writes Hyung J. Cho, MD, from the New York University Grossman School of Medicine, in an accompanying editorial. “Ironically, hospitals, where people go to recover from illness, are among the most difficult places to sleep.”

Number of night-time checks successfully reduced

The mean number of night-time checks was significantly lower in the algorithm group than in the standard-care group (0.97 vs. 1.41; P < .001).

The reduction in night-time checks had no effect on patient safety. There was no increase in transfers to the intensive care unit in the algorithm or standard-care groups (5% vs 5%; P = .92), and no difference between the number of heart alarms (0.2% vs. 0.9%; P = .07).

However, the reduction also had no effect on the incidence of episodes of delirium in the algorithm or standard-care groups (11% vs. 13%; P = .32).

“The reduction in vital signs checking, although statistically significant, was relatively small,” Dr. Cho explains. But the primary endpoint might have been different had the adherence to intervention been better, he notes.

In fact, the analysis confirmed that changes to routine daily practice in a hospital are not always easy to implement. In 35% of cases, the patients’ vital signs were checked at night, despite the physician’s order to the contrary.

“Busy patient-care assistants and nurses may check vital signs out of habit without noticing that the order has changed for some of the patients,” Dr. Najafi and his coauthors write. Many hospitals are used to thinking that regular measurements of the vital signs are part of good practice.
 

Include nursing staff

Future projects should use an interdisciplinary approach that includes nursing staff, Dr. Cho recommends. More user-friendly displays and optimized alerts in the electronic patient records could also encourage better implementation of the orders.

Less frequent checks of the vital signs would be welcomed by frontline staff because it would lighten their already heavy workload, he adds.

Although the study didn’t meet its primary endpoint, patients subjected to fewer night-time checks because of the algorithm were able to get a good night’s sleep. Other aspects of hospital care that are based on the patient’s stability, such as cardiac monitoring, could also potentially benefit from this type of intervention, Dr. Najafi and his colleagues suggest.

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

From the Department of Medicine (Drs. Meisenberg, Muganlinskaya, Sharma, Amjadi, Arnold, Barnes, Clance, Khalil, Miller, Mooradian, O’Connell, Patel, Press, Samaras, Shanmugam, Tavadze, and Thompson), Department of Pharmacy (Drs. Jiang, Jarawan, Sheth, and Trinh), Department of Nursing (Dr. Ohnmacht), and Department of Women and Children’s Services (Dr. Raji), Luminis Health, Annapolis, MD, and Lanham, MD.

Objective: The COVID-19 pandemic has been a challenge for hospital medical staffs worldwide due to high volumes of patients acutely ill with novel syndromes and prevailing uncertainty regarding optimum supportive and therapeutic interventions. Additionally, the response to this crisis was driven by a plethora of nontraditional information sources, such as email chains, websites, non–peer-reviewed preprints, and press releases. Care patterns became idiosyncratic and often incorporated unproven interventions driven by these nontraditional information sources. This report evaluates the efforts of a health system to create and empower a multidisciplinary committee to develop, implement, and monitor evidence-based, standardized protocols for patients with COVID-19.

Methods: This report describes the composition of the committee, its scope, and its important interactions with the health system pharmacy and therapeutics committee, research teams, and other work groups planning other aspects of COVID-19 management. It illustrates how the committee was used to demonstrate for trainees the process and value of critically examining evidence, even in a chaotic environment.

Results: Data show successful interventions in reducing excessive ordering of certain laboratory tests, reduction of nonrecommended therapies, and rapid uptake of evidence-based or guidelines-supported interventions.

Conclusions: A multidisciplinary committee dedicated solely to planning, implementing, and monitoring standard approaches that eventually became evidence-based decision-making led to an improved focus on treatment options and outcomes for COVID-19 patients. Data presented illustrate the attainable success that is both adaptable and suitable for similar emergencies in the future.

Keywords: COVID-19; clinical management; pharmacy and therapeutics; treatment; therapy.

The COVID-19 pandemic has spread to nearly all countries, carrying with it high morbidity, mortality, and severe impacts on both well-developed and less-well-developed health systems. Media reports of chaos within overwhelmed hospitals have been prominent.^1,2 As of January 5, 2022, SARS-CoV-2 has infected more than 295 million people globally and directly caused the death of more than 5.4 million,³ though this number is likely an undercount even in countries with well-developed mortality tracking.⁴

Throughout the COVID-19 pandemic, hospital-based medical teams have been confronted with a flood of severely ill patients with novel syndromes. Initially, there were no standards for therapy or supportive care except for treatments borrowed from similar syndromes. In the setting of high volumes, high acuity, and public dismay, it is unsurprising that the usual deliberative methods for weighing evidence and initiating interventions were often pushed aside in favor of the solace of active intervention.⁵ In this milieu of limited evidence, there was a lamentable, if understandable, tendency to seek guidance from “nontraditional” sources,⁶ including email chains from colleagues, hospital websites, non–peer-reviewed manuscripts, advanced publication by medical journals,⁷ and nonscientific media presentations. In many localities, practitioners responded in idiosyncratic ways. For example, findings of high cytokine levels in COVID-19,⁸ along with reports of in-vitro antiviral activity with drugs like hydroxychloroquine against both SARS⁹ and SARS-CoV-2,¹⁰ drove laboratory test ordering and therapeutic interventions, respectively, carving shortcuts into the traditional clinical trial–dependent standards. Clinical trial results eventually emerged.¹¹COVID-19 created a clinical dilemma for hospital medical staffs in terms of how to organize, standardize, and rapidly adapt to a flood of new information. In this report, we describe how 1 health system responded to these challenges by forming a COVID-19 Clinical Management Committee (CCMC) and empowering this interdisciplinary team to review evidence, create and adjust order sets, educate practitioners, oversee care, and collaborate across teams addressing other aspects of the COVID-19 response.

Program Overview

Health System Description

Luminis Health is a health system with 2 acute care hospitals that was formed in 2019 just before the start of the pandemic. Anne Arundel Medical Center (hospital A) is a 385-bed teaching hospital in Annapolis, MD. It has more than 23 000 discharges annually. Patients with COVID-19 were cared for by either an internal medicine teaching service or nonteaching hospitalist services on cohorted nursing units. Doctor’s Community Medical Center, in Lanham, MD (hospital B), is a 206-bed acute care hospital with more than 10 350 annual discharges. COVID-19 patients were cared for by hospitalist groups, initially in noncohorted units with transition to cohorted nursing units after a few months. The medical staffs are generally distinct, with different leadership structures, though the Luminis Health Department of Medicine has oversight responsibilities at both hospitals. More than 47 physicians attended COVID-19 patients at hospital A (with medical residents) and 30 individual physicians at hospital B, respectively, including intensivists. The nursing and pharmacy staffs are distinct, but there is a shared oversight Pharmacy and Therapeutics (P&T) Committee.

The 2 hospitals had distinct electronic medical records (EMR) until January 2021, when hospital B adopted the same EMR as hospital A (Epic).

Mission and Formation of CCMC

In order to coordinate the therapeutic approach across the health system, it was important for the CCMC to be designated by the health system P&T committee as an official subcommittee so that decisions on restrictions of medications and/or new or revised order sets could be rapidly initiated across the system without waiting for the subsequent P&T meetings. The full committee retained oversight of the CCMC. Some P&T members were also on the CCMC.

The committee reviewed new reports in medical journals and prepublication servers and consulted recommendations of professional societies, such as the National Institutes of Health (NIH) COVID-19 guidelines, Infectious Diseases Society of America, Society of Critical Care Medicine, and US Food and Drug Administration (FDA) Emergency Use Authorizations (EUA), among other sources.

Composition of the CCMC

Physician leaders from both hospitals in the following specialties were solicited for participation: critical care, epidemiology, hospital medicine (internal medicine), emergency medicine, infectious diseases, nephrology, women and children’s services, and medical informatics. Specialists in other areas, such as hematology, were invited for topic-specific discussions. Hospital pharmacists with different specialties and nursing leadership were essential contributors. The committee members were expected to use various communication channels to inform frontline clinicians of new care standards and the existence of new order sets, which were embedded in the EMR.

Clinical Research

An important connection for the CCMC was with theCOVID-19 clinical research team. Three members of the research team were also members of the CCMC. All new study proposals for therapeutics were discussed with the CCMC as they were being considered by the research team. In this way, feedback on the feasibility and acceptance of new study opportunities could be discussed with the CCMC. Occasionally, CCMC decisions impacted clinical research accrual strategies. For example, new data from randomized trials about tocilizumab^1,2 demonstrated benefits in some subsets of patients and resulted in a recommendation for use by the NIH guideline committee in these populations.¹ The CCMC quickly adopted this recommendation, which required a reprioritization of clinical research enrollment for studies testing other immune-modulating agents. This important dialogue was mediated within the CCMC.

Guideline Distribution, Reinforcement, and Platform for Feedback

New guidelines were disseminated to clinicians via daily brief patient huddles held on COVID units, with participation by nursing and pharmacy, and by weekly meetings with hospitalist leaders and frontline hospital physicians. Order sets and guidelines were maintained on the intranet. Adherence was reinforced by unit-based and central pharmacists. Order sets, including admission order sets, could be created only by designated informatics personnel, thus enforcing standardization. Feedback on the utility of the order sets was obtained during the weekly meetings or huddles, as described above. To ensure a sense of transparency, physicians who had interest in commenting on a particular therapy, or who wished to discuss a particular manuscript, news article, or website, were invited to attend CCMC meetings.

Scope of CCMC

In order to be effective and timely, we limited the scope of our work to the report to the inpatient therapeutic environment, allowing other committees to work on other aspects of the pandemic response. In addition to issuing guidance and creating order sets to direct clinical practice, the CCMC also monitored COVID-19 therapeutic shortages^15,16 and advised on prioritization of such treatments as convalescent plasma, remdesivir (prioritization and duration of therapy, 5 vs 10 days), baricitinib, and tocilizumab, depending upon the location of the patient (critical care or not). The CCMC was not involved in the management of non–COVID-19 shortages brought about by supply chain deficiencies.

Table 1 shows some aspects of the health system pandemic-response planning and the committee workforce that undertook that work. Though many items were out of scope for the CCMC, members of the CCMC did participate in the planning work of these other committees and therefore stayed connected to this complementary work.

A Teaching Opportunity About Making Thoughtful Choices

Another important feature of the CCMC was the contributions of residents from both pharmacy and internal medicine. The purpose and operations of the committee were recognized as an opportunity to involve learners in a curriculum based on Kern’s 6-step approach.¹⁷ Though the problem identification and general needs assessment were easily defined, the targeted needs assessment, extracted from individual and group interviews with learners and the committee members, pointed at the need to learn how to assess and analyze a rapidly growing body of literature on several relevant clinical aspects of SARS-CoV-2 and COVID-19. To achieve goals and objectives, residents were assigned to present current literature on a particular intervention during a committee meeting, specifically commenting on the merit or deficiencies of the study design, the strength of the data, and applicability to the local context with a recommendation. Prior to the presentations, the residents worked with faculty to identify the best studies or systematic analyses with potential to alter current practices. We thus used the CCMC process as a teaching tool about evidence-based medicine and the dilemma of clinical equipoise. This was imperative, since trainees thrust into the COVID-19 response have often keenly observed a movement away from deliberative decision-making.¹⁸ Indeed, including residents in the process of deliberative responses to COVID-19 addresses a recent call to adjust medical education during COVID-19 to “adapt curriculum to current issues in real time.”¹⁹

Interventions and Therapies Considered

Table 2 shows the topics reviewed by the CCMC. By the time of the first meeting, nonstandardization of care was already a source of concern for clinicians. Dialogue often continued outside of the formal meetings. Many topics were considered more than once as new guidance developed, changes to EUAs occurred, and new data or new publicity arose.

Methods

The Human Protections Administrator determined that this work constituted “quality improvement, and not research” and was therefore exempt from institutional review board review.

Quantitative Analysis

All admitted patients from March 10, 2020, through April 20, 2021, were considered in the quantitative aspects of this report except as noted. Patients diagnosed with COVID-19 were identified by searching our internal data base using diagnostic codes. Patient admissions with the following diagnostic codes were included (prior to April 1, 2020): J12.89, J20.8, J40, J22, J98.8, J80, each with the additional code of B97.29. After April 1, 2020, the guideline for coding COVID-19 was U07.1.

Descriptive statistics were used to measure utilization rates of certain medications and laboratory tests of interest over time. These data were adjusted for number of unique admissions. In a few cases, not all data elements were available from both hospitals due to differences in the EMR.

Case fatality rate was calculated based upon whether the patient died or was admitted to inpatient hospice as a result of COVID-19. Four patients transferred out of hospital A and 18 transferred out of hospital B were censored from case-fatality-rate determination.

Figure 1 shows the number of admissions for each acute care hospital in the health system and the combined COVID-19 case-fatality rate over time.

Results

A total of 5955 consecutive COVID-19 patients admitted from March 10, 2020, through April 30, 2021, were analyzed. Patients with International Statistical Classification of Diseases, Tenth Revision codes J12.89. J20.8, J40, J22, J98.8, J80, each with the additional code of B97.29 (or the code UO7.1 after April 1, 2020), were included in the analysis. The median age of admitted patients was 65 years (range 19-91 years). Using the NIH classification system for severity,²⁰ the distribution of severity during the first 24 hours after the time of hospital admission was as follows: asymptomatic/presymptomatic, 0.5%; mild illness, 5.3%; moderate illness, 37.1%; severe illness, 55.5%; and critical illness, 1.1%.

The impact of the CCMC can be estimated by looking at care patterns over time. Since the work of the CCMC was aimed at influencing and standardizing physician ordering and therapy choices through order set creation and other forms of oversight, we measured the use of the CCMC-approved order sets at both hospitals and the use of certain laboratory tests and therapies that the CCMC sought either to limit or increase. These counts were adjusted for number of unique COVID-19 admissions. But the limits of the case collection tool meant it also collected cases that were not eligible for some of the interventions. For example, COVID-19 admissions without hypoxemia would not have been eligible for remdesivir or glucocorticoids. When admitted, some patients were already on steroids for other medical indications and did not receive the prescribed dexamethasone dose that we measured in pharmacy databases. Similarly, a few patients were hospitalized for indications unrelated to COVID-19, such as surgery or childbirth, and were found to be SARS-CoV-2-positive on routine screening.

Figure 2 shows the utilization of CCMC-approved standard COVID-19 admission order sets as a proportion of all COVID-19 admissions over time. The trend reveals a modest increase in usage (R² = 0.34), but these data do not reflect the progressive build of content into order sets over time. One of the goals of the order sets was to standardize and reduce the ordering of certain biomarkers: C-reactive protein, serum ferritin, and D-dimer, which were ordered frequently in many early patients. Orders for these 3 laboratory tests are combined and expressed as an average number of labs per COVID-19 admission in Figure 2. A downward trend, with an R² value of 0.65, is suggestive of impact from the order sets, though other explanations are possible.

Medication guidance was also a goal of the CCMC, simultaneously discouraging poorly supported interventions and driving uptake of the recommended evidence-based interventions in appropriate patients. Figure 3 shows the utilization pattern for some drugs of interest over the course of the pandemic, specifically the proportion of patients receiving at least 1 dose of medication among all COVID-19 admissions by month. (Data for hospital B was excluded from this analysis because it did not include all admitted patients.)

Hydroxychloroquine, which enjoyed a wave of popularity early on during the pandemic, was a target of successful order stewardship through the CCMC. Use of hydroxychloroquine as a COVID-19 therapeutic option after the first 2 months of the pandemic stopped, and subsequent use at low levels likely represented continuation therapy for outpatients who took hydroxychloroquine for rheumatologic indications.

Dexamethasone, as used in the RECOVERY trial,²¹ had a swift uptake among physicians after it was incorporated into order sets and its use encouraged. Similarly, uptake was immediate for remdesivir when, in May 2020, preliminary reports showed at least some benefits, confirmed by later analysis,²² and it received an FDA EUA.

Our data also show successful stewardship of the interleukin-6 antagonist toclilizumab, which was discouraged early on by the CCMC due to lack of data or negative results. But in March 2021, with new studies releasing data^12,13 and new recommendations¹⁴ for its use in some subsets of patients with COVID-19, this drug was encouraged in appropriate subsets. A new order set with qualifying indications was prepared by the CCMC and new educational efforts made to encourage its use in appropriate patients.

Ivermectin was nonformulary at the start of the pandemic. This drug enjoyed much publicity from media sources and was promoted by certain physicians and on websites,²³ based on in-vitro activity against coronaviruses. Eventually, the World Health Organization²⁴ and the FDA²⁵ found it necessary to issue advisory statements to the public against its use outside of clinical trials. The CCMC had requests from physicians to incorporate ivermectin but declined to add it to the formulary and recommended not approving nonformulary requests due to lack of data. As a result, ivermectin was not used at either hospital.

Discussion

COVID-19 represents many challenges to health systems all over the world. For Luminis Health, the high volume of acutely ill patients with novel syndromes was a particular challenge for the hospital-based care teams. A flood of information from preprints, press releases, preliminary reports, and many other nontraditional sources made deliberative management decisions difficult for individual physicians. Much commentary has appeared around the phenomenon but with less practical advice about how to make day-to-day care decisions at a time of scientific uncertainty and intense pressure to intervene.^26,27 The CCMC was designed to overcome the information management dilemma. The need to coordinate, standardize, and oversee care was necessary given the large number of physicians who cared for COVID-19 patients on inpatient services.

It should be noted that creating order sets and issuing guidance is necessary, but not sufficient, to achieve our goals of being updated and consistent. This is especially true with large cadres of health care workers attending COVID-19 patients. Guidelines and recommendations were reinforced by unit-based oversight and stewardship from pharmacy and other leaders who constituted the CCMC.

The reduction in COVID-19 mortality over time experienced in this health care system was not unique and cannot necessarily be attributed to standardization of care. Similar improvements in mortality have been reported at many US hospitals in aggregate.²⁸ Many other factors, including changes in patient characteristics, may be responsible for reduction in mortality over time.

Throughout this report we have relied upon an implicit assumption that standardization of medical therapeutics is desirable and leads to better outcomes as compared with allowing unlimited empiricism by individual physicians, either consultants or hospitalists. Our program represents a single health system with 2 acute care hospitals located 25 miles apart and which thus were similarly impacted by the different phases of the pandemic. Generalizability to health systems either smaller or larger, or in different geographical areas, has not been established. Data limitations have already been discussed.

We did not measure user satisfaction with the program either from physicians or nurses. However, the high rate of compliance suggests general agreement with the content and process.

We cannot definitively ascribe reduction in utilization of some nonrecommended treatments and increased utilization of the recommended therapies to the work of the CCMC. Individual physicians may have made these adjustments on their own or under the influence of other sources.

Finally, it should be noted that the mission to rapidly respond to data from well-conducted trials might be thwarted by too rigid a process or a committee’s lack of a sense of urgency. Organizing a committee and then empowering it to act is no guarantee of success; commitment to the mission is.

Conclusion

COVID-19 represented a challenge to medical staffs everywhere, inundating them with high volumes of acutely ill patients presenting with unfamiliar syndromes. Initial responses were characterized by idiosyncratic management approaches based on nontraditional sources of opinion and influences.

This report describes how a complex medical system brought order and standardization through a deliberative, but urgent, multidisciplinary committee with responsibility for planning, implementing, and monitoring standard approaches that eventually became evidence based. The composition of the committee and its scope of influence, limited to inpatient management, were important elements of success, allowing for better focus on the many treatment decisions. The important connection between the management committee and the system P&T committee, the clinical research effort, and teaching programs in both medicine and pharmacy are offered as exemplars of coordination. The data presented show success in achieving standardized, guideline-directed care. The approach is adoptable and suitable for similar emergencies in the future.

Acknowledgments: The authors thank Gary Scabis, Kip Waite, John Moxley, Angela Clubb, and David Woodley for their assistance in gathering data. We express appreciation and admiration for all our colleagues at the bedside.

Corresponding author: Barry R. Meisenberg, MD, Department of Medicine, Luminis Health, 2001 Medical Pkwy, Annapolis, MD 21401; meisenberg@AAHS.org.

Financial disclosures: None.

From the Department of Medicine (Drs. Meisenberg, Muganlinskaya, Sharma, Amjadi, Arnold, Barnes, Clance, Khalil, Miller, Mooradian, O’Connell, Patel, Press, Samaras, Shanmugam, Tavadze, and Thompson), Department of Pharmacy (Drs. Jiang, Jarawan, Sheth, and Trinh), Department of Nursing (Dr. Ohnmacht), and Department of Women and Children’s Services (Dr. Raji), Luminis Health, Annapolis, MD, and Lanham, MD.

Objective: The COVID-19 pandemic has been a challenge for hospital medical staffs worldwide due to high volumes of patients acutely ill with novel syndromes and prevailing uncertainty regarding optimum supportive and therapeutic interventions. Additionally, the response to this crisis was driven by a plethora of nontraditional information sources, such as email chains, websites, non–peer-reviewed preprints, and press releases. Care patterns became idiosyncratic and often incorporated unproven interventions driven by these nontraditional information sources. This report evaluates the efforts of a health system to create and empower a multidisciplinary committee to develop, implement, and monitor evidence-based, standardized protocols for patients with COVID-19.

Methods: This report describes the composition of the committee, its scope, and its important interactions with the health system pharmacy and therapeutics committee, research teams, and other work groups planning other aspects of COVID-19 management. It illustrates how the committee was used to demonstrate for trainees the process and value of critically examining evidence, even in a chaotic environment.

Results: Data show successful interventions in reducing excessive ordering of certain laboratory tests, reduction of nonrecommended therapies, and rapid uptake of evidence-based or guidelines-supported interventions.

Conclusions: A multidisciplinary committee dedicated solely to planning, implementing, and monitoring standard approaches that eventually became evidence-based decision-making led to an improved focus on treatment options and outcomes for COVID-19 patients. Data presented illustrate the attainable success that is both adaptable and suitable for similar emergencies in the future.

Keywords: COVID-19; clinical management; pharmacy and therapeutics; treatment; therapy.

The COVID-19 pandemic has spread to nearly all countries, carrying with it high morbidity, mortality, and severe impacts on both well-developed and less-well-developed health systems. Media reports of chaos within overwhelmed hospitals have been prominent.^1,2 As of January 5, 2022, SARS-CoV-2 has infected more than 295 million people globally and directly caused the death of more than 5.4 million,³ though this number is likely an undercount even in countries with well-developed mortality tracking.⁴

Throughout the COVID-19 pandemic, hospital-based medical teams have been confronted with a flood of severely ill patients with novel syndromes. Initially, there were no standards for therapy or supportive care except for treatments borrowed from similar syndromes. In the setting of high volumes, high acuity, and public dismay, it is unsurprising that the usual deliberative methods for weighing evidence and initiating interventions were often pushed aside in favor of the solace of active intervention.⁵ In this milieu of limited evidence, there was a lamentable, if understandable, tendency to seek guidance from “nontraditional” sources,⁶ including email chains from colleagues, hospital websites, non–peer-reviewed manuscripts, advanced publication by medical journals,⁷ and nonscientific media presentations. In many localities, practitioners responded in idiosyncratic ways. For example, findings of high cytokine levels in COVID-19,⁸ along with reports of in-vitro antiviral activity with drugs like hydroxychloroquine against both SARS⁹ and SARS-CoV-2,¹⁰ drove laboratory test ordering and therapeutic interventions, respectively, carving shortcuts into the traditional clinical trial–dependent standards. Clinical trial results eventually emerged.¹¹COVID-19 created a clinical dilemma for hospital medical staffs in terms of how to organize, standardize, and rapidly adapt to a flood of new information. In this report, we describe how 1 health system responded to these challenges by forming a COVID-19 Clinical Management Committee (CCMC) and empowering this interdisciplinary team to review evidence, create and adjust order sets, educate practitioners, oversee care, and collaborate across teams addressing other aspects of the COVID-19 response.

Program Overview

Health System Description

Luminis Health is a health system with 2 acute care hospitals that was formed in 2019 just before the start of the pandemic. Anne Arundel Medical Center (hospital A) is a 385-bed teaching hospital in Annapolis, MD. It has more than 23 000 discharges annually. Patients with COVID-19 were cared for by either an internal medicine teaching service or nonteaching hospitalist services on cohorted nursing units. Doctor’s Community Medical Center, in Lanham, MD (hospital B), is a 206-bed acute care hospital with more than 10 350 annual discharges. COVID-19 patients were cared for by hospitalist groups, initially in noncohorted units with transition to cohorted nursing units after a few months. The medical staffs are generally distinct, with different leadership structures, though the Luminis Health Department of Medicine has oversight responsibilities at both hospitals. More than 47 physicians attended COVID-19 patients at hospital A (with medical residents) and 30 individual physicians at hospital B, respectively, including intensivists. The nursing and pharmacy staffs are distinct, but there is a shared oversight Pharmacy and Therapeutics (P&T) Committee.

The 2 hospitals had distinct electronic medical records (EMR) until January 2021, when hospital B adopted the same EMR as hospital A (Epic).

Mission and Formation of CCMC

In order to coordinate the therapeutic approach across the health system, it was important for the CCMC to be designated by the health system P&T committee as an official subcommittee so that decisions on restrictions of medications and/or new or revised order sets could be rapidly initiated across the system without waiting for the subsequent P&T meetings. The full committee retained oversight of the CCMC. Some P&T members were also on the CCMC.

The committee reviewed new reports in medical journals and prepublication servers and consulted recommendations of professional societies, such as the National Institutes of Health (NIH) COVID-19 guidelines, Infectious Diseases Society of America, Society of Critical Care Medicine, and US Food and Drug Administration (FDA) Emergency Use Authorizations (EUA), among other sources.

Composition of the CCMC

Physician leaders from both hospitals in the following specialties were solicited for participation: critical care, epidemiology, hospital medicine (internal medicine), emergency medicine, infectious diseases, nephrology, women and children’s services, and medical informatics. Specialists in other areas, such as hematology, were invited for topic-specific discussions. Hospital pharmacists with different specialties and nursing leadership were essential contributors. The committee members were expected to use various communication channels to inform frontline clinicians of new care standards and the existence of new order sets, which were embedded in the EMR.

Clinical Research

An important connection for the CCMC was with theCOVID-19 clinical research team. Three members of the research team were also members of the CCMC. All new study proposals for therapeutics were discussed with the CCMC as they were being considered by the research team. In this way, feedback on the feasibility and acceptance of new study opportunities could be discussed with the CCMC. Occasionally, CCMC decisions impacted clinical research accrual strategies. For example, new data from randomized trials about tocilizumab^1,2 demonstrated benefits in some subsets of patients and resulted in a recommendation for use by the NIH guideline committee in these populations.¹ The CCMC quickly adopted this recommendation, which required a reprioritization of clinical research enrollment for studies testing other immune-modulating agents. This important dialogue was mediated within the CCMC.

Guideline Distribution, Reinforcement, and Platform for Feedback

New guidelines were disseminated to clinicians via daily brief patient huddles held on COVID units, with participation by nursing and pharmacy, and by weekly meetings with hospitalist leaders and frontline hospital physicians. Order sets and guidelines were maintained on the intranet. Adherence was reinforced by unit-based and central pharmacists. Order sets, including admission order sets, could be created only by designated informatics personnel, thus enforcing standardization. Feedback on the utility of the order sets was obtained during the weekly meetings or huddles, as described above. To ensure a sense of transparency, physicians who had interest in commenting on a particular therapy, or who wished to discuss a particular manuscript, news article, or website, were invited to attend CCMC meetings.

Scope of CCMC

In order to be effective and timely, we limited the scope of our work to the report to the inpatient therapeutic environment, allowing other committees to work on other aspects of the pandemic response. In addition to issuing guidance and creating order sets to direct clinical practice, the CCMC also monitored COVID-19 therapeutic shortages^15,16 and advised on prioritization of such treatments as convalescent plasma, remdesivir (prioritization and duration of therapy, 5 vs 10 days), baricitinib, and tocilizumab, depending upon the location of the patient (critical care or not). The CCMC was not involved in the management of non–COVID-19 shortages brought about by supply chain deficiencies.

Table 1 shows some aspects of the health system pandemic-response planning and the committee workforce that undertook that work. Though many items were out of scope for the CCMC, members of the CCMC did participate in the planning work of these other committees and therefore stayed connected to this complementary work.

A Teaching Opportunity About Making Thoughtful Choices

Another important feature of the CCMC was the contributions of residents from both pharmacy and internal medicine. The purpose and operations of the committee were recognized as an opportunity to involve learners in a curriculum based on Kern’s 6-step approach.¹⁷ Though the problem identification and general needs assessment were easily defined, the targeted needs assessment, extracted from individual and group interviews with learners and the committee members, pointed at the need to learn how to assess and analyze a rapidly growing body of literature on several relevant clinical aspects of SARS-CoV-2 and COVID-19. To achieve goals and objectives, residents were assigned to present current literature on a particular intervention during a committee meeting, specifically commenting on the merit or deficiencies of the study design, the strength of the data, and applicability to the local context with a recommendation. Prior to the presentations, the residents worked with faculty to identify the best studies or systematic analyses with potential to alter current practices. We thus used the CCMC process as a teaching tool about evidence-based medicine and the dilemma of clinical equipoise. This was imperative, since trainees thrust into the COVID-19 response have often keenly observed a movement away from deliberative decision-making.¹⁸ Indeed, including residents in the process of deliberative responses to COVID-19 addresses a recent call to adjust medical education during COVID-19 to “adapt curriculum to current issues in real time.”¹⁹

Interventions and Therapies Considered

Table 2 shows the topics reviewed by the CCMC. By the time of the first meeting, nonstandardization of care was already a source of concern for clinicians. Dialogue often continued outside of the formal meetings. Many topics were considered more than once as new guidance developed, changes to EUAs occurred, and new data or new publicity arose.

Methods

The Human Protections Administrator determined that this work constituted “quality improvement, and not research” and was therefore exempt from institutional review board review.

Quantitative Analysis

All admitted patients from March 10, 2020, through April 20, 2021, were considered in the quantitative aspects of this report except as noted. Patients diagnosed with COVID-19 were identified by searching our internal data base using diagnostic codes. Patient admissions with the following diagnostic codes were included (prior to April 1, 2020): J12.89, J20.8, J40, J22, J98.8, J80, each with the additional code of B97.29. After April 1, 2020, the guideline for coding COVID-19 was U07.1.

Descriptive statistics were used to measure utilization rates of certain medications and laboratory tests of interest over time. These data were adjusted for number of unique admissions. In a few cases, not all data elements were available from both hospitals due to differences in the EMR.

Case fatality rate was calculated based upon whether the patient died or was admitted to inpatient hospice as a result of COVID-19. Four patients transferred out of hospital A and 18 transferred out of hospital B were censored from case-fatality-rate determination.

Figure 1 shows the number of admissions for each acute care hospital in the health system and the combined COVID-19 case-fatality rate over time.

Results

A total of 5955 consecutive COVID-19 patients admitted from March 10, 2020, through April 30, 2021, were analyzed. Patients with International Statistical Classification of Diseases, Tenth Revision codes J12.89. J20.8, J40, J22, J98.8, J80, each with the additional code of B97.29 (or the code UO7.1 after April 1, 2020), were included in the analysis. The median age of admitted patients was 65 years (range 19-91 years). Using the NIH classification system for severity,²⁰ the distribution of severity during the first 24 hours after the time of hospital admission was as follows: asymptomatic/presymptomatic, 0.5%; mild illness, 5.3%; moderate illness, 37.1%; severe illness, 55.5%; and critical illness, 1.1%.

The impact of the CCMC can be estimated by looking at care patterns over time. Since the work of the CCMC was aimed at influencing and standardizing physician ordering and therapy choices through order set creation and other forms of oversight, we measured the use of the CCMC-approved order sets at both hospitals and the use of certain laboratory tests and therapies that the CCMC sought either to limit or increase. These counts were adjusted for number of unique COVID-19 admissions. But the limits of the case collection tool meant it also collected cases that were not eligible for some of the interventions. For example, COVID-19 admissions without hypoxemia would not have been eligible for remdesivir or glucocorticoids. When admitted, some patients were already on steroids for other medical indications and did not receive the prescribed dexamethasone dose that we measured in pharmacy databases. Similarly, a few patients were hospitalized for indications unrelated to COVID-19, such as surgery or childbirth, and were found to be SARS-CoV-2-positive on routine screening.

Figure 2 shows the utilization of CCMC-approved standard COVID-19 admission order sets as a proportion of all COVID-19 admissions over time. The trend reveals a modest increase in usage (R² = 0.34), but these data do not reflect the progressive build of content into order sets over time. One of the goals of the order sets was to standardize and reduce the ordering of certain biomarkers: C-reactive protein, serum ferritin, and D-dimer, which were ordered frequently in many early patients. Orders for these 3 laboratory tests are combined and expressed as an average number of labs per COVID-19 admission in Figure 2. A downward trend, with an R² value of 0.65, is suggestive of impact from the order sets, though other explanations are possible.

Medication guidance was also a goal of the CCMC, simultaneously discouraging poorly supported interventions and driving uptake of the recommended evidence-based interventions in appropriate patients. Figure 3 shows the utilization pattern for some drugs of interest over the course of the pandemic, specifically the proportion of patients receiving at least 1 dose of medication among all COVID-19 admissions by month. (Data for hospital B was excluded from this analysis because it did not include all admitted patients.)

Hydroxychloroquine, which enjoyed a wave of popularity early on during the pandemic, was a target of successful order stewardship through the CCMC. Use of hydroxychloroquine as a COVID-19 therapeutic option after the first 2 months of the pandemic stopped, and subsequent use at low levels likely represented continuation therapy for outpatients who took hydroxychloroquine for rheumatologic indications.

Dexamethasone, as used in the RECOVERY trial,²¹ had a swift uptake among physicians after it was incorporated into order sets and its use encouraged. Similarly, uptake was immediate for remdesivir when, in May 2020, preliminary reports showed at least some benefits, confirmed by later analysis,²² and it received an FDA EUA.

Our data also show successful stewardship of the interleukin-6 antagonist toclilizumab, which was discouraged early on by the CCMC due to lack of data or negative results. But in March 2021, with new studies releasing data^12,13 and new recommendations¹⁴ for its use in some subsets of patients with COVID-19, this drug was encouraged in appropriate subsets. A new order set with qualifying indications was prepared by the CCMC and new educational efforts made to encourage its use in appropriate patients.

Ivermectin was nonformulary at the start of the pandemic. This drug enjoyed much publicity from media sources and was promoted by certain physicians and on websites,²³ based on in-vitro activity against coronaviruses. Eventually, the World Health Organization²⁴ and the FDA²⁵ found it necessary to issue advisory statements to the public against its use outside of clinical trials. The CCMC had requests from physicians to incorporate ivermectin but declined to add it to the formulary and recommended not approving nonformulary requests due to lack of data. As a result, ivermectin was not used at either hospital.

Discussion

COVID-19 represents many challenges to health systems all over the world. For Luminis Health, the high volume of acutely ill patients with novel syndromes was a particular challenge for the hospital-based care teams. A flood of information from preprints, press releases, preliminary reports, and many other nontraditional sources made deliberative management decisions difficult for individual physicians. Much commentary has appeared around the phenomenon but with less practical advice about how to make day-to-day care decisions at a time of scientific uncertainty and intense pressure to intervene.^26,27 The CCMC was designed to overcome the information management dilemma. The need to coordinate, standardize, and oversee care was necessary given the large number of physicians who cared for COVID-19 patients on inpatient services.

It should be noted that creating order sets and issuing guidance is necessary, but not sufficient, to achieve our goals of being updated and consistent. This is especially true with large cadres of health care workers attending COVID-19 patients. Guidelines and recommendations were reinforced by unit-based oversight and stewardship from pharmacy and other leaders who constituted the CCMC.

The reduction in COVID-19 mortality over time experienced in this health care system was not unique and cannot necessarily be attributed to standardization of care. Similar improvements in mortality have been reported at many US hospitals in aggregate.²⁸ Many other factors, including changes in patient characteristics, may be responsible for reduction in mortality over time.

Throughout this report we have relied upon an implicit assumption that standardization of medical therapeutics is desirable and leads to better outcomes as compared with allowing unlimited empiricism by individual physicians, either consultants or hospitalists. Our program represents a single health system with 2 acute care hospitals located 25 miles apart and which thus were similarly impacted by the different phases of the pandemic. Generalizability to health systems either smaller or larger, or in different geographical areas, has not been established. Data limitations have already been discussed.

We did not measure user satisfaction with the program either from physicians or nurses. However, the high rate of compliance suggests general agreement with the content and process.

We cannot definitively ascribe reduction in utilization of some nonrecommended treatments and increased utilization of the recommended therapies to the work of the CCMC. Individual physicians may have made these adjustments on their own or under the influence of other sources.

Finally, it should be noted that the mission to rapidly respond to data from well-conducted trials might be thwarted by too rigid a process or a committee’s lack of a sense of urgency. Organizing a committee and then empowering it to act is no guarantee of success; commitment to the mission is.

Conclusion

COVID-19 represented a challenge to medical staffs everywhere, inundating them with high volumes of acutely ill patients presenting with unfamiliar syndromes. Initial responses were characterized by idiosyncratic management approaches based on nontraditional sources of opinion and influences.

This report describes how a complex medical system brought order and standardization through a deliberative, but urgent, multidisciplinary committee with responsibility for planning, implementing, and monitoring standard approaches that eventually became evidence based. The composition of the committee and its scope of influence, limited to inpatient management, were important elements of success, allowing for better focus on the many treatment decisions. The important connection between the management committee and the system P&T committee, the clinical research effort, and teaching programs in both medicine and pharmacy are offered as exemplars of coordination. The data presented show success in achieving standardized, guideline-directed care. The approach is adoptable and suitable for similar emergencies in the future.

Acknowledgments: The authors thank Gary Scabis, Kip Waite, John Moxley, Angela Clubb, and David Woodley for their assistance in gathering data. We express appreciation and admiration for all our colleagues at the bedside.

Corresponding author: Barry R. Meisenberg, MD, Department of Medicine, Luminis Health, 2001 Medical Pkwy, Annapolis, MD 21401; meisenberg@AAHS.org.

Financial disclosures: None.

From the Department of Medicine (Drs. Meisenberg, Muganlinskaya, Sharma, Amjadi, Arnold, Barnes, Clance, Khalil, Miller, Mooradian, O’Connell, Patel, Press, Samaras, Shanmugam, Tavadze, and Thompson), Department of Pharmacy (Drs. Jiang, Jarawan, Sheth, and Trinh), Department of Nursing (Dr. Ohnmacht), and Department of Women and Children’s Services (Dr. Raji), Luminis Health, Annapolis, MD, and Lanham, MD.

Objective: The COVID-19 pandemic has been a challenge for hospital medical staffs worldwide due to high volumes of patients acutely ill with novel syndromes and prevailing uncertainty regarding optimum supportive and therapeutic interventions. Additionally, the response to this crisis was driven by a plethora of nontraditional information sources, such as email chains, websites, non–peer-reviewed preprints, and press releases. Care patterns became idiosyncratic and often incorporated unproven interventions driven by these nontraditional information sources. This report evaluates the efforts of a health system to create and empower a multidisciplinary committee to develop, implement, and monitor evidence-based, standardized protocols for patients with COVID-19.

Methods: This report describes the composition of the committee, its scope, and its important interactions with the health system pharmacy and therapeutics committee, research teams, and other work groups planning other aspects of COVID-19 management. It illustrates how the committee was used to demonstrate for trainees the process and value of critically examining evidence, even in a chaotic environment.

Results: Data show successful interventions in reducing excessive ordering of certain laboratory tests, reduction of nonrecommended therapies, and rapid uptake of evidence-based or guidelines-supported interventions.

Conclusions: A multidisciplinary committee dedicated solely to planning, implementing, and monitoring standard approaches that eventually became evidence-based decision-making led to an improved focus on treatment options and outcomes for COVID-19 patients. Data presented illustrate the attainable success that is both adaptable and suitable for similar emergencies in the future.

Keywords: COVID-19; clinical management; pharmacy and therapeutics; treatment; therapy.

The COVID-19 pandemic has spread to nearly all countries, carrying with it high morbidity, mortality, and severe impacts on both well-developed and less-well-developed health systems. Media reports of chaos within overwhelmed hospitals have been prominent.^1,2 As of January 5, 2022, SARS-CoV-2 has infected more than 295 million people globally and directly caused the death of more than 5.4 million,³ though this number is likely an undercount even in countries with well-developed mortality tracking.⁴

Throughout the COVID-19 pandemic, hospital-based medical teams have been confronted with a flood of severely ill patients with novel syndromes. Initially, there were no standards for therapy or supportive care except for treatments borrowed from similar syndromes. In the setting of high volumes, high acuity, and public dismay, it is unsurprising that the usual deliberative methods for weighing evidence and initiating interventions were often pushed aside in favor of the solace of active intervention.⁵ In this milieu of limited evidence, there was a lamentable, if understandable, tendency to seek guidance from “nontraditional” sources,⁶ including email chains from colleagues, hospital websites, non–peer-reviewed manuscripts, advanced publication by medical journals,⁷ and nonscientific media presentations. In many localities, practitioners responded in idiosyncratic ways. For example, findings of high cytokine levels in COVID-19,⁸ along with reports of in-vitro antiviral activity with drugs like hydroxychloroquine against both SARS⁹ and SARS-CoV-2,¹⁰ drove laboratory test ordering and therapeutic interventions, respectively, carving shortcuts into the traditional clinical trial–dependent standards. Clinical trial results eventually emerged.¹¹COVID-19 created a clinical dilemma for hospital medical staffs in terms of how to organize, standardize, and rapidly adapt to a flood of new information. In this report, we describe how 1 health system responded to these challenges by forming a COVID-19 Clinical Management Committee (CCMC) and empowering this interdisciplinary team to review evidence, create and adjust order sets, educate practitioners, oversee care, and collaborate across teams addressing other aspects of the COVID-19 response.

Program Overview

Health System Description

Luminis Health is a health system with 2 acute care hospitals that was formed in 2019 just before the start of the pandemic. Anne Arundel Medical Center (hospital A) is a 385-bed teaching hospital in Annapolis, MD. It has more than 23 000 discharges annually. Patients with COVID-19 were cared for by either an internal medicine teaching service or nonteaching hospitalist services on cohorted nursing units. Doctor’s Community Medical Center, in Lanham, MD (hospital B), is a 206-bed acute care hospital with more than 10 350 annual discharges. COVID-19 patients were cared for by hospitalist groups, initially in noncohorted units with transition to cohorted nursing units after a few months. The medical staffs are generally distinct, with different leadership structures, though the Luminis Health Department of Medicine has oversight responsibilities at both hospitals. More than 47 physicians attended COVID-19 patients at hospital A (with medical residents) and 30 individual physicians at hospital B, respectively, including intensivists. The nursing and pharmacy staffs are distinct, but there is a shared oversight Pharmacy and Therapeutics (P&T) Committee.

The 2 hospitals had distinct electronic medical records (EMR) until January 2021, when hospital B adopted the same EMR as hospital A (Epic).

Mission and Formation of CCMC

In order to coordinate the therapeutic approach across the health system, it was important for the CCMC to be designated by the health system P&T committee as an official subcommittee so that decisions on restrictions of medications and/or new or revised order sets could be rapidly initiated across the system without waiting for the subsequent P&T meetings. The full committee retained oversight of the CCMC. Some P&T members were also on the CCMC.

The committee reviewed new reports in medical journals and prepublication servers and consulted recommendations of professional societies, such as the National Institutes of Health (NIH) COVID-19 guidelines, Infectious Diseases Society of America, Society of Critical Care Medicine, and US Food and Drug Administration (FDA) Emergency Use Authorizations (EUA), among other sources.

Composition of the CCMC

Physician leaders from both hospitals in the following specialties were solicited for participation: critical care, epidemiology, hospital medicine (internal medicine), emergency medicine, infectious diseases, nephrology, women and children’s services, and medical informatics. Specialists in other areas, such as hematology, were invited for topic-specific discussions. Hospital pharmacists with different specialties and nursing leadership were essential contributors. The committee members were expected to use various communication channels to inform frontline clinicians of new care standards and the existence of new order sets, which were embedded in the EMR.

Clinical Research

An important connection for the CCMC was with theCOVID-19 clinical research team. Three members of the research team were also members of the CCMC. All new study proposals for therapeutics were discussed with the CCMC as they were being considered by the research team. In this way, feedback on the feasibility and acceptance of new study opportunities could be discussed with the CCMC. Occasionally, CCMC decisions impacted clinical research accrual strategies. For example, new data from randomized trials about tocilizumab^1,2 demonstrated benefits in some subsets of patients and resulted in a recommendation for use by the NIH guideline committee in these populations.¹ The CCMC quickly adopted this recommendation, which required a reprioritization of clinical research enrollment for studies testing other immune-modulating agents. This important dialogue was mediated within the CCMC.

Guideline Distribution, Reinforcement, and Platform for Feedback

New guidelines were disseminated to clinicians via daily brief patient huddles held on COVID units, with participation by nursing and pharmacy, and by weekly meetings with hospitalist leaders and frontline hospital physicians. Order sets and guidelines were maintained on the intranet. Adherence was reinforced by unit-based and central pharmacists. Order sets, including admission order sets, could be created only by designated informatics personnel, thus enforcing standardization. Feedback on the utility of the order sets was obtained during the weekly meetings or huddles, as described above. To ensure a sense of transparency, physicians who had interest in commenting on a particular therapy, or who wished to discuss a particular manuscript, news article, or website, were invited to attend CCMC meetings.

Scope of CCMC

In order to be effective and timely, we limited the scope of our work to the report to the inpatient therapeutic environment, allowing other committees to work on other aspects of the pandemic response. In addition to issuing guidance and creating order sets to direct clinical practice, the CCMC also monitored COVID-19 therapeutic shortages^15,16 and advised on prioritization of such treatments as convalescent plasma, remdesivir (prioritization and duration of therapy, 5 vs 10 days), baricitinib, and tocilizumab, depending upon the location of the patient (critical care or not). The CCMC was not involved in the management of non–COVID-19 shortages brought about by supply chain deficiencies.

Table 1 shows some aspects of the health system pandemic-response planning and the committee workforce that undertook that work. Though many items were out of scope for the CCMC, members of the CCMC did participate in the planning work of these other committees and therefore stayed connected to this complementary work.

A Teaching Opportunity About Making Thoughtful Choices

Another important feature of the CCMC was the contributions of residents from both pharmacy and internal medicine. The purpose and operations of the committee were recognized as an opportunity to involve learners in a curriculum based on Kern’s 6-step approach.¹⁷ Though the problem identification and general needs assessment were easily defined, the targeted needs assessment, extracted from individual and group interviews with learners and the committee members, pointed at the need to learn how to assess and analyze a rapidly growing body of literature on several relevant clinical aspects of SARS-CoV-2 and COVID-19. To achieve goals and objectives, residents were assigned to present current literature on a particular intervention during a committee meeting, specifically commenting on the merit or deficiencies of the study design, the strength of the data, and applicability to the local context with a recommendation. Prior to the presentations, the residents worked with faculty to identify the best studies or systematic analyses with potential to alter current practices. We thus used the CCMC process as a teaching tool about evidence-based medicine and the dilemma of clinical equipoise. This was imperative, since trainees thrust into the COVID-19 response have often keenly observed a movement away from deliberative decision-making.¹⁸ Indeed, including residents in the process of deliberative responses to COVID-19 addresses a recent call to adjust medical education during COVID-19 to “adapt curriculum to current issues in real time.”¹⁹

Interventions and Therapies Considered

Table 2 shows the topics reviewed by the CCMC. By the time of the first meeting, nonstandardization of care was already a source of concern for clinicians. Dialogue often continued outside of the formal meetings. Many topics were considered more than once as new guidance developed, changes to EUAs occurred, and new data or new publicity arose.

Methods

The Human Protections Administrator determined that this work constituted “quality improvement, and not research” and was therefore exempt from institutional review board review.

Quantitative Analysis

All admitted patients from March 10, 2020, through April 20, 2021, were considered in the quantitative aspects of this report except as noted. Patients diagnosed with COVID-19 were identified by searching our internal data base using diagnostic codes. Patient admissions with the following diagnostic codes were included (prior to April 1, 2020): J12.89, J20.8, J40, J22, J98.8, J80, each with the additional code of B97.29. After April 1, 2020, the guideline for coding COVID-19 was U07.1.

Descriptive statistics were used to measure utilization rates of certain medications and laboratory tests of interest over time. These data were adjusted for number of unique admissions. In a few cases, not all data elements were available from both hospitals due to differences in the EMR.

Case fatality rate was calculated based upon whether the patient died or was admitted to inpatient hospice as a result of COVID-19. Four patients transferred out of hospital A and 18 transferred out of hospital B were censored from case-fatality-rate determination.

Figure 1 shows the number of admissions for each acute care hospital in the health system and the combined COVID-19 case-fatality rate over time.

Results

A total of 5955 consecutive COVID-19 patients admitted from March 10, 2020, through April 30, 2021, were analyzed. Patients with International Statistical Classification of Diseases, Tenth Revision codes J12.89. J20.8, J40, J22, J98.8, J80, each with the additional code of B97.29 (or the code UO7.1 after April 1, 2020), were included in the analysis. The median age of admitted patients was 65 years (range 19-91 years). Using the NIH classification system for severity,²⁰ the distribution of severity during the first 24 hours after the time of hospital admission was as follows: asymptomatic/presymptomatic, 0.5%; mild illness, 5.3%; moderate illness, 37.1%; severe illness, 55.5%; and critical illness, 1.1%.

The impact of the CCMC can be estimated by looking at care patterns over time. Since the work of the CCMC was aimed at influencing and standardizing physician ordering and therapy choices through order set creation and other forms of oversight, we measured the use of the CCMC-approved order sets at both hospitals and the use of certain laboratory tests and therapies that the CCMC sought either to limit or increase. These counts were adjusted for number of unique COVID-19 admissions. But the limits of the case collection tool meant it also collected cases that were not eligible for some of the interventions. For example, COVID-19 admissions without hypoxemia would not have been eligible for remdesivir or glucocorticoids. When admitted, some patients were already on steroids for other medical indications and did not receive the prescribed dexamethasone dose that we measured in pharmacy databases. Similarly, a few patients were hospitalized for indications unrelated to COVID-19, such as surgery or childbirth, and were found to be SARS-CoV-2-positive on routine screening.

Figure 2 shows the utilization of CCMC-approved standard COVID-19 admission order sets as a proportion of all COVID-19 admissions over time. The trend reveals a modest increase in usage (R² = 0.34), but these data do not reflect the progressive build of content into order sets over time. One of the goals of the order sets was to standardize and reduce the ordering of certain biomarkers: C-reactive protein, serum ferritin, and D-dimer, which were ordered frequently in many early patients. Orders for these 3 laboratory tests are combined and expressed as an average number of labs per COVID-19 admission in Figure 2. A downward trend, with an R² value of 0.65, is suggestive of impact from the order sets, though other explanations are possible.

Medication guidance was also a goal of the CCMC, simultaneously discouraging poorly supported interventions and driving uptake of the recommended evidence-based interventions in appropriate patients. Figure 3 shows the utilization pattern for some drugs of interest over the course of the pandemic, specifically the proportion of patients receiving at least 1 dose of medication among all COVID-19 admissions by month. (Data for hospital B was excluded from this analysis because it did not include all admitted patients.)

Hydroxychloroquine, which enjoyed a wave of popularity early on during the pandemic, was a target of successful order stewardship through the CCMC. Use of hydroxychloroquine as a COVID-19 therapeutic option after the first 2 months of the pandemic stopped, and subsequent use at low levels likely represented continuation therapy for outpatients who took hydroxychloroquine for rheumatologic indications.

Dexamethasone, as used in the RECOVERY trial,²¹ had a swift uptake among physicians after it was incorporated into order sets and its use encouraged. Similarly, uptake was immediate for remdesivir when, in May 2020, preliminary reports showed at least some benefits, confirmed by later analysis,²² and it received an FDA EUA.

Our data also show successful stewardship of the interleukin-6 antagonist toclilizumab, which was discouraged early on by the CCMC due to lack of data or negative results. But in March 2021, with new studies releasing data^12,13 and new recommendations¹⁴ for its use in some subsets of patients with COVID-19, this drug was encouraged in appropriate subsets. A new order set with qualifying indications was prepared by the CCMC and new educational efforts made to encourage its use in appropriate patients.

Ivermectin was nonformulary at the start of the pandemic. This drug enjoyed much publicity from media sources and was promoted by certain physicians and on websites,²³ based on in-vitro activity against coronaviruses. Eventually, the World Health Organization²⁴ and the FDA²⁵ found it necessary to issue advisory statements to the public against its use outside of clinical trials. The CCMC had requests from physicians to incorporate ivermectin but declined to add it to the formulary and recommended not approving nonformulary requests due to lack of data. As a result, ivermectin was not used at either hospital.

Discussion

COVID-19 represents many challenges to health systems all over the world. For Luminis Health, the high volume of acutely ill patients with novel syndromes was a particular challenge for the hospital-based care teams. A flood of information from preprints, press releases, preliminary reports, and many other nontraditional sources made deliberative management decisions difficult for individual physicians. Much commentary has appeared around the phenomenon but with less practical advice about how to make day-to-day care decisions at a time of scientific uncertainty and intense pressure to intervene.^26,27 The CCMC was designed to overcome the information management dilemma. The need to coordinate, standardize, and oversee care was necessary given the large number of physicians who cared for COVID-19 patients on inpatient services.

It should be noted that creating order sets and issuing guidance is necessary, but not sufficient, to achieve our goals of being updated and consistent. This is especially true with large cadres of health care workers attending COVID-19 patients. Guidelines and recommendations were reinforced by unit-based oversight and stewardship from pharmacy and other leaders who constituted the CCMC.

The reduction in COVID-19 mortality over time experienced in this health care system was not unique and cannot necessarily be attributed to standardization of care. Similar improvements in mortality have been reported at many US hospitals in aggregate.²⁸ Many other factors, including changes in patient characteristics, may be responsible for reduction in mortality over time.

Throughout this report we have relied upon an implicit assumption that standardization of medical therapeutics is desirable and leads to better outcomes as compared with allowing unlimited empiricism by individual physicians, either consultants or hospitalists. Our program represents a single health system with 2 acute care hospitals located 25 miles apart and which thus were similarly impacted by the different phases of the pandemic. Generalizability to health systems either smaller or larger, or in different geographical areas, has not been established. Data limitations have already been discussed.

We did not measure user satisfaction with the program either from physicians or nurses. However, the high rate of compliance suggests general agreement with the content and process.

We cannot definitively ascribe reduction in utilization of some nonrecommended treatments and increased utilization of the recommended therapies to the work of the CCMC. Individual physicians may have made these adjustments on their own or under the influence of other sources.

Finally, it should be noted that the mission to rapidly respond to data from well-conducted trials might be thwarted by too rigid a process or a committee’s lack of a sense of urgency. Organizing a committee and then empowering it to act is no guarantee of success; commitment to the mission is.

Conclusion

COVID-19 represented a challenge to medical staffs everywhere, inundating them with high volumes of acutely ill patients presenting with unfamiliar syndromes. Initial responses were characterized by idiosyncratic management approaches based on nontraditional sources of opinion and influences.

This report describes how a complex medical system brought order and standardization through a deliberative, but urgent, multidisciplinary committee with responsibility for planning, implementing, and monitoring standard approaches that eventually became evidence based. The composition of the committee and its scope of influence, limited to inpatient management, were important elements of success, allowing for better focus on the many treatment decisions. The important connection between the management committee and the system P&T committee, the clinical research effort, and teaching programs in both medicine and pharmacy are offered as exemplars of coordination. The data presented show success in achieving standardized, guideline-directed care. The approach is adoptable and suitable for similar emergencies in the future.

Acknowledgments: The authors thank Gary Scabis, Kip Waite, John Moxley, Angela Clubb, and David Woodley for their assistance in gathering data. We express appreciation and admiration for all our colleagues at the bedside.

Corresponding author: Barry R. Meisenberg, MD, Department of Medicine, Luminis Health, 2001 Medical Pkwy, Annapolis, MD 21401; meisenberg@AAHS.org.

Financial disclosures: None.

Electronic consultation (e-consult) is designed to increase access to specialty care by facilitating communication between primary care and specialty clinicians without the need for outpatient face-to-face encounters.^1–4 In 2011, the US Department of Veterans Affairs (VA) implemented an e-consult program as a component of its overall strategy to increase access to specialty services, reduce costs of care, and reduce appointment travel burden on patients.

E-consult has substantially increased within the VA since its implementation.^5,6 Consistent with limited evaluations from other health care systems, evaluations of the VA e-consult program demonstrated reduced costs, reduced travel time for patients, and improved access to specialty care.^2,5–11 However, there is wide variation in e-consult use across VA specialties, facilities, and regions.^5,6,12,13 For example, hematology, preoperative evaluation, neurosurgery, endocrinology, and infectious diseases use e-consults more frequently when compared with in-person consults in the VA.⁶ Reasons for this variation or specific barriers and facilitators of using e-consults have not been described.

Prior qualitative studies report that primary care practitioners (PCPs) describe e-consults as convenient, educational, beneficial for patient care, and useful for improving patient access to specialty care.^8,14,15 One study identified limited PCP knowledge of e-consults as a barrier to use.¹⁶ Specialists have reported that e-consult improves clinical communication, but increases their workload.^1,14,17,18 These studies did not assess perspectives from both clinicians who initiate e-consults and those who respond to them. This is the first qualitative study to assess e-consult perceptions from perspectives of both PCPs and specialists among a large, national sample of VA clinicians who use e-consults. The objective of this study was to understand perspectives of e-consults between PCPs and specialists that may be relevant to increasing adoption in the VA.

Methods

The team (CL, ML, PG, 2 analysts under the guidance of GS and JS and support from RRK, and a biostatistician) conducted semistructured interviews with PCPs, specialists, and specialty division leaders who were employed by VA in 2016 and 2017. Specialties of interest were identified by the VA Office of Specialty Care and included cardiology, endocrinology, gastroenterology, and hematology.

E-Consult Procedures

Within the VA, the specific procedures used to initiate, triage and manage e-consults are coordinated at VA medical centers (VAMCs) and at the Veterans Integrated Service Network (VISN) regional level. E-consult can be requested by any clinician. Generally, e-consults are initiated by PCPs through standardized, specialty-specific templates. Recipients, typically specialists, respond by answering questions, suggesting additional testing and evaluation, or requesting an in-person visit. Communication is documented in the patient’s electronic health record (EHR). Specialists receive different levels of workload credit for responding to e-consults similar to a relative value unit reimbursement model. Training in the use of e-consults is available to practitioners but may vary at local and regional levels.

Recruitment

Our sample included PCPs, specialists, and specialty care division leaders. We first quantified e-consult rates (e-consults per 100 patient visits) between July 2016 and June 2017 at VA facilities within primary care and the 4 priority specialties and identified the 30 sites with the highest e-consult rates and 30 sites with the lowest e-consult rates. Sites with < 500 total visits, < 3 specialties, or without any e-consult visit during the study period were excluded. E-consult rates at community-based outpatient clinics were included with associated VAMCs. We then stratified PCPs by whether they were high or low users of e-consults (determined by the top and bottom users within each site) and credentials (MD vs nurse practitioner [NP] or physician assistant [PA]). Specialists were sampled based on their rate of use relative to colleagues within their site and the use rate of their division. We sampled division chiefs and individuals who had > 300 total visits and 1 e-consult during the study period. To recruit participants, the primary investigator sent an initial email and 2 reminder emails. The team followed up with respondents to schedule an interview.

Interview guides were designed to elicit rich descriptions of barriers and facilitators to e-consult use (eAppendix available at doi:10.12788/fp.0214). The team used the Practical Robust Implementation and Sustainability Model (PRISM), which considers factors along 6 domains for intervention planning, implementation, and sustainment.¹⁹ Telephone interviews lasted about 20 minutes and were conducted between September 2017 and March 2018. Interviews were recorded and transcribed verbatim.

Analysis

The team used an iterative, team-based, inductive/deductive approach to conventional content analysis.^20,21 Initial code categories were created so that we could identify e-consult best practices—facilitators of e-consult that were recommended by both PCPs and specialists. Inductive codes or labels applied to identify meaningful quotations, phrases, or key terms were used to identify emergent ideas and were added throughout coding after discussion among team members. Consensus was reached using a team-based approach.²¹ Four analysts independently coded the same 3 transcripts and met to discuss points of divergence and convergence. Analyses continued with emergent themes, categories, and conclusions. Atlas.ti. v.7 was used for coding and data management.²²

Results

We conducted 34 interviews with clinicians (Table 1) from 13 VISNs. Four best-practice themes emerged among both PCPs and specialists, including that e-consults (1) are best suited for certain clinical questions and patients; (2) require relevant background information from requesting clinicians and clear recommendations from responding clinicians; (3) are a novel opportunity to provide efficient, transparent care; and (4) may not be fully adopted due to low awareness. Supporting quotations for the following findings are provided in Table 2.

Specific Clinical Questions and Patients

PCPs described specific patients and questions for which they most frequently used e-consults, such as for medication changes (Q1), determining treatment steps (Q2,3), and or clarifying laboratory or imaging findings. PCPs frequently used e-consults for patients who did not require a physical examination or when specialists could make recommendations without seeing patients face-to-face (Q3). An important use of e-consults described by PCPs was for treating conditions they could manage within primary care if additional guidance were available (Q4). Several PCPs and specialists also noted that e-consults were particularly useful for patients who were unable to travel or did not want face-to-face appointments (Q5). Notably, PCPs and specialists mentioned situations for which e-consults were inappropriate, including when a detailed history or physical examination was needed, or if a complex condition was suspected (Q6).

Background Data and Clear Recommendations

Participants described necessary data that should be included in high-quality e-consults. Specialists voiced frustration in time-consuming chart reviews that were often necessary when these data were not provided by the requestor. In some cases, specialists were unable to access necessary EHR data, which delayed responses (Q7). PCPs noted that the most useful responses carefully considered the question, used current patient information to determine treatments, provided clear recommendations, and defined who was responsible for next steps (Q8). PCPs and specialists stated that e-consult templates that required relevant information facilitated high-quality e-consults. Neither wanted to waste the other clinician's time (Q8).

A Novel Opportunity

Many PCPs felt that e-consults improved communication (eg, efficiency, response time), established new communication between clinicians, and reduced patients’ appointment burden (Q10, Q11). Many specialists felt that e-consults improved documentation of communication between clinicians and increased transparency of clinical decisions (Q12). Additionally, many specialists mentioned that e-consults capture previously informal curbside consults, enabling them to receive workload credit (Q13).

Lack of Awareness

Some noted that the biggest barrier to e-consults was not being aware of them generally, or which specialties offer e-consults (Q14). One PCP described e-consults as the best kept secret and found value in sharing the utility of e-consults with colleagues (Q15). All participants, including those who did not frequently use e-consults, felt that e-consults improved the quality of care by providing more timely care or better answers to clinical questions (Q16). Several practitioners also felt that e-consults increased access to specialty care. For example, specialists reported that e-consults enabled them to better manage patient load by using e-consults to answer relatively simple questions, reserving face-to-face consults for more complex patients (Q17).

Discussion

The objective of this study was to identify potential best practices for e-consults that may help increase their quality and use within the VA. We built on prior studies that offered insights on PCP and specialists’ overall satisfaction with e-consult by identifying several themes relevant to the further adoption of e-consults in the VA and elsewhere without a face-to-face visit.^{8,13,14,16–18} Future work may be beneficial in identifying whether the study themes identified can explain variation in e-consult use or whether addressing these factors might lead to increased or higher quality e-consult use. We are unaware of any qualitative study of comparable scale in a different health care system. Further, this is the first study to assess perspectives on e-consults among those who initiate and respond to them within the same health care system. Perhaps the most important finding from this study is that e-consults are generally viewed favorably, which is a necessary leverage point to increase their adoption within the system.

Clinicians reported several benefits to e-consults, including timely responses to clinical questions, efficient communication, allow for documentation of specialist recommendations, and help capture workload. These benefits are consistent with prior literature that indicates both PCPs and specialists in the VA and other health care systems feel that e-consults improves communication, decreases unnecessary visits, and improves quality of care.^1,14,17,18 In particular, clinicians reported that e-consults improve their practice efficiency and efficacy. This is of critical importance given the pressures of providing timely access to primary and specialty care within the VA. Interestingly, many VA practitioners were unaware which specialties offered e-consults within their facilities, reflecting previous work showing that PCPs are often unaware of e-consult options.¹⁶ This may partially explain variation in e-consult use. Increasing awareness and educating clinicians on the benefits of e-consults may help promote use among non- and low users.

A common theme reported by both groups was the importance of providing necessary information within e-consult questions and responses. Specialists felt there was a need to ensure that PCPs provide relevant and patient-specific information that would enable them to efficiently and accurately answer questions without the need for extensive EHR review. This reflects previous work showing that specialists are often unable to respond to e-consult requests because they do not contain sufficient information.²² PCPs described a need to ensure that specialists’ responses included information that was detailed enough to make clinical decisions without the need for a reconsult. This highlights a common challenge to medical consultation, in that necessary or relevant information may not be apparent to all clinicians. To address this, there may be a role in developing enhanced, flexible templating that elicits necessary patient-specific information. Such a template may automatically pull relevant data from the EHR and prompt clinicians to provide important information. We did not assess how perspectives of templates varied, and further work could help define precisely what constitutes an effective template, including how it should capture appropriate patient data and how this impacts acceptability or use of e-consults generally. Collaboratively developed service agreements and e-consult templates could help guide PCPs and specialists to engage in efficient communication.

Another theme among both groups was that e-consult is most appropriate within specific clinical scenarios. Examples included review of laboratory results, questions about medication changes, or for patients who were reluctant to travel to appointments. Identifying and promoting specific opportunities for e-consults may help increase their use and align e-consult practices with scenarios that are likely to provide the most benefit to patients. For example, it could be helpful to understand the distance patients must travel for specialty care. Providing that information during clinical encounters could trigger clinicians to consider e-consults as an option. Future work might aim to identify clinical scenarios that clinicians feel are not well suited for e-consults and determine how to adapt them for those scenarios.

Limitations

Generalizability of these findings is limited given the qualitative study design. Participants’ descriptions of experiences with e-consults reflect the experiences of clinicians in the VA and may not reflect clinicians in other settings. We also interviewed a sample of clinicians who were already using e-consults. Important information could be learned from future work with those who have not yet adopted e-consult procedures or adopted and abandoned them.

Conclusions

E-consult is perceived as beneficial by VA PCPs and specialists. Participants suggested using e-consults for appropriate questions or patients and including necessary information and next steps in both the initial e-consult and response. Finding ways to facilitate e-consults with these suggestions in mind may increase delivery of high-quality e-consults. Future work could compare the findings of this work to similar work assessing clinicians perceptions of e-consults outside of the VA.

Electronic consultation (e-consult) is designed to increase access to specialty care by facilitating communication between primary care and specialty clinicians without the need for outpatient face-to-face encounters.^1–4 In 2011, the US Department of Veterans Affairs (VA) implemented an e-consult program as a component of its overall strategy to increase access to specialty services, reduce costs of care, and reduce appointment travel burden on patients.

E-consult has substantially increased within the VA since its implementation.^5,6 Consistent with limited evaluations from other health care systems, evaluations of the VA e-consult program demonstrated reduced costs, reduced travel time for patients, and improved access to specialty care.^2,5–11 However, there is wide variation in e-consult use across VA specialties, facilities, and regions.^5,6,12,13 For example, hematology, preoperative evaluation, neurosurgery, endocrinology, and infectious diseases use e-consults more frequently when compared with in-person consults in the VA.⁶ Reasons for this variation or specific barriers and facilitators of using e-consults have not been described.

Prior qualitative studies report that primary care practitioners (PCPs) describe e-consults as convenient, educational, beneficial for patient care, and useful for improving patient access to specialty care.^8,14,15 One study identified limited PCP knowledge of e-consults as a barrier to use.¹⁶ Specialists have reported that e-consult improves clinical communication, but increases their workload.^1,14,17,18 These studies did not assess perspectives from both clinicians who initiate e-consults and those who respond to them. This is the first qualitative study to assess e-consult perceptions from perspectives of both PCPs and specialists among a large, national sample of VA clinicians who use e-consults. The objective of this study was to understand perspectives of e-consults between PCPs and specialists that may be relevant to increasing adoption in the VA.

Methods

The team (CL, ML, PG, 2 analysts under the guidance of GS and JS and support from RRK, and a biostatistician) conducted semistructured interviews with PCPs, specialists, and specialty division leaders who were employed by VA in 2016 and 2017. Specialties of interest were identified by the VA Office of Specialty Care and included cardiology, endocrinology, gastroenterology, and hematology.

E-Consult Procedures

Within the VA, the specific procedures used to initiate, triage and manage e-consults are coordinated at VA medical centers (VAMCs) and at the Veterans Integrated Service Network (VISN) regional level. E-consult can be requested by any clinician. Generally, e-consults are initiated by PCPs through standardized, specialty-specific templates. Recipients, typically specialists, respond by answering questions, suggesting additional testing and evaluation, or requesting an in-person visit. Communication is documented in the patient’s electronic health record (EHR). Specialists receive different levels of workload credit for responding to e-consults similar to a relative value unit reimbursement model. Training in the use of e-consults is available to practitioners but may vary at local and regional levels.

Recruitment

Our sample included PCPs, specialists, and specialty care division leaders. We first quantified e-consult rates (e-consults per 100 patient visits) between July 2016 and June 2017 at VA facilities within primary care and the 4 priority specialties and identified the 30 sites with the highest e-consult rates and 30 sites with the lowest e-consult rates. Sites with < 500 total visits, < 3 specialties, or without any e-consult visit during the study period were excluded. E-consult rates at community-based outpatient clinics were included with associated VAMCs. We then stratified PCPs by whether they were high or low users of e-consults (determined by the top and bottom users within each site) and credentials (MD vs nurse practitioner [NP] or physician assistant [PA]). Specialists were sampled based on their rate of use relative to colleagues within their site and the use rate of their division. We sampled division chiefs and individuals who had > 300 total visits and 1 e-consult during the study period. To recruit participants, the primary investigator sent an initial email and 2 reminder emails. The team followed up with respondents to schedule an interview.

Interview guides were designed to elicit rich descriptions of barriers and facilitators to e-consult use (eAppendix available at doi:10.12788/fp.0214). The team used the Practical Robust Implementation and Sustainability Model (PRISM), which considers factors along 6 domains for intervention planning, implementation, and sustainment.¹⁹ Telephone interviews lasted about 20 minutes and were conducted between September 2017 and March 2018. Interviews were recorded and transcribed verbatim.

Analysis

The team used an iterative, team-based, inductive/deductive approach to conventional content analysis.^20,21 Initial code categories were created so that we could identify e-consult best practices—facilitators of e-consult that were recommended by both PCPs and specialists. Inductive codes or labels applied to identify meaningful quotations, phrases, or key terms were used to identify emergent ideas and were added throughout coding after discussion among team members. Consensus was reached using a team-based approach.²¹ Four analysts independently coded the same 3 transcripts and met to discuss points of divergence and convergence. Analyses continued with emergent themes, categories, and conclusions. Atlas.ti. v.7 was used for coding and data management.²²

Results

We conducted 34 interviews with clinicians (Table 1) from 13 VISNs. Four best-practice themes emerged among both PCPs and specialists, including that e-consults (1) are best suited for certain clinical questions and patients; (2) require relevant background information from requesting clinicians and clear recommendations from responding clinicians; (3) are a novel opportunity to provide efficient, transparent care; and (4) may not be fully adopted due to low awareness. Supporting quotations for the following findings are provided in Table 2.

Specific Clinical Questions and Patients

PCPs described specific patients and questions for which they most frequently used e-consults, such as for medication changes (Q1), determining treatment steps (Q2,3), and or clarifying laboratory or imaging findings. PCPs frequently used e-consults for patients who did not require a physical examination or when specialists could make recommendations without seeing patients face-to-face (Q3). An important use of e-consults described by PCPs was for treating conditions they could manage within primary care if additional guidance were available (Q4). Several PCPs and specialists also noted that e-consults were particularly useful for patients who were unable to travel or did not want face-to-face appointments (Q5). Notably, PCPs and specialists mentioned situations for which e-consults were inappropriate, including when a detailed history or physical examination was needed, or if a complex condition was suspected (Q6).

Background Data and Clear Recommendations

Participants described necessary data that should be included in high-quality e-consults. Specialists voiced frustration in time-consuming chart reviews that were often necessary when these data were not provided by the requestor. In some cases, specialists were unable to access necessary EHR data, which delayed responses (Q7). PCPs noted that the most useful responses carefully considered the question, used current patient information to determine treatments, provided clear recommendations, and defined who was responsible for next steps (Q8). PCPs and specialists stated that e-consult templates that required relevant information facilitated high-quality e-consults. Neither wanted to waste the other clinician's time (Q8).

A Novel Opportunity

Many PCPs felt that e-consults improved communication (eg, efficiency, response time), established new communication between clinicians, and reduced patients’ appointment burden (Q10, Q11). Many specialists felt that e-consults improved documentation of communication between clinicians and increased transparency of clinical decisions (Q12). Additionally, many specialists mentioned that e-consults capture previously informal curbside consults, enabling them to receive workload credit (Q13).

Lack of Awareness

Some noted that the biggest barrier to e-consults was not being aware of them generally, or which specialties offer e-consults (Q14). One PCP described e-consults as the best kept secret and found value in sharing the utility of e-consults with colleagues (Q15). All participants, including those who did not frequently use e-consults, felt that e-consults improved the quality of care by providing more timely care or better answers to clinical questions (Q16). Several practitioners also felt that e-consults increased access to specialty care. For example, specialists reported that e-consults enabled them to better manage patient load by using e-consults to answer relatively simple questions, reserving face-to-face consults for more complex patients (Q17).

Discussion

The objective of this study was to identify potential best practices for e-consults that may help increase their quality and use within the VA. We built on prior studies that offered insights on PCP and specialists’ overall satisfaction with e-consult by identifying several themes relevant to the further adoption of e-consults in the VA and elsewhere without a face-to-face visit.^{8,13,14,16–18} Future work may be beneficial in identifying whether the study themes identified can explain variation in e-consult use or whether addressing these factors might lead to increased or higher quality e-consult use. We are unaware of any qualitative study of comparable scale in a different health care system. Further, this is the first study to assess perspectives on e-consults among those who initiate and respond to them within the same health care system. Perhaps the most important finding from this study is that e-consults are generally viewed favorably, which is a necessary leverage point to increase their adoption within the system.

Clinicians reported several benefits to e-consults, including timely responses to clinical questions, efficient communication, allow for documentation of specialist recommendations, and help capture workload. These benefits are consistent with prior literature that indicates both PCPs and specialists in the VA and other health care systems feel that e-consults improves communication, decreases unnecessary visits, and improves quality of care.^1,14,17,18 In particular, clinicians reported that e-consults improve their practice efficiency and efficacy. This is of critical importance given the pressures of providing timely access to primary and specialty care within the VA. Interestingly, many VA practitioners were unaware which specialties offered e-consults within their facilities, reflecting previous work showing that PCPs are often unaware of e-consult options.¹⁶ This may partially explain variation in e-consult use. Increasing awareness and educating clinicians on the benefits of e-consults may help promote use among non- and low users.

A common theme reported by both groups was the importance of providing necessary information within e-consult questions and responses. Specialists felt there was a need to ensure that PCPs provide relevant and patient-specific information that would enable them to efficiently and accurately answer questions without the need for extensive EHR review. This reflects previous work showing that specialists are often unable to respond to e-consult requests because they do not contain sufficient information.²² PCPs described a need to ensure that specialists’ responses included information that was detailed enough to make clinical decisions without the need for a reconsult. This highlights a common challenge to medical consultation, in that necessary or relevant information may not be apparent to all clinicians. To address this, there may be a role in developing enhanced, flexible templating that elicits necessary patient-specific information. Such a template may automatically pull relevant data from the EHR and prompt clinicians to provide important information. We did not assess how perspectives of templates varied, and further work could help define precisely what constitutes an effective template, including how it should capture appropriate patient data and how this impacts acceptability or use of e-consults generally. Collaboratively developed service agreements and e-consult templates could help guide PCPs and specialists to engage in efficient communication.

Another theme among both groups was that e-consult is most appropriate within specific clinical scenarios. Examples included review of laboratory results, questions about medication changes, or for patients who were reluctant to travel to appointments. Identifying and promoting specific opportunities for e-consults may help increase their use and align e-consult practices with scenarios that are likely to provide the most benefit to patients. For example, it could be helpful to understand the distance patients must travel for specialty care. Providing that information during clinical encounters could trigger clinicians to consider e-consults as an option. Future work might aim to identify clinical scenarios that clinicians feel are not well suited for e-consults and determine how to adapt them for those scenarios.

Limitations

Generalizability of these findings is limited given the qualitative study design. Participants’ descriptions of experiences with e-consults reflect the experiences of clinicians in the VA and may not reflect clinicians in other settings. We also interviewed a sample of clinicians who were already using e-consults. Important information could be learned from future work with those who have not yet adopted e-consult procedures or adopted and abandoned them.

Conclusions

E-consult is perceived as beneficial by VA PCPs and specialists. Participants suggested using e-consults for appropriate questions or patients and including necessary information and next steps in both the initial e-consult and response. Finding ways to facilitate e-consults with these suggestions in mind may increase delivery of high-quality e-consults. Future work could compare the findings of this work to similar work assessing clinicians perceptions of e-consults outside of the VA.

Electronic consultation (e-consult) is designed to increase access to specialty care by facilitating communication between primary care and specialty clinicians without the need for outpatient face-to-face encounters.^1–4 In 2011, the US Department of Veterans Affairs (VA) implemented an e-consult program as a component of its overall strategy to increase access to specialty services, reduce costs of care, and reduce appointment travel burden on patients.

E-consult has substantially increased within the VA since its implementation.^5,6 Consistent with limited evaluations from other health care systems, evaluations of the VA e-consult program demonstrated reduced costs, reduced travel time for patients, and improved access to specialty care.^2,5–11 However, there is wide variation in e-consult use across VA specialties, facilities, and regions.^5,6,12,13 For example, hematology, preoperative evaluation, neurosurgery, endocrinology, and infectious diseases use e-consults more frequently when compared with in-person consults in the VA.⁶ Reasons for this variation or specific barriers and facilitators of using e-consults have not been described.

Prior qualitative studies report that primary care practitioners (PCPs) describe e-consults as convenient, educational, beneficial for patient care, and useful for improving patient access to specialty care.^8,14,15 One study identified limited PCP knowledge of e-consults as a barrier to use.¹⁶ Specialists have reported that e-consult improves clinical communication, but increases their workload.^1,14,17,18 These studies did not assess perspectives from both clinicians who initiate e-consults and those who respond to them. This is the first qualitative study to assess e-consult perceptions from perspectives of both PCPs and specialists among a large, national sample of VA clinicians who use e-consults. The objective of this study was to understand perspectives of e-consults between PCPs and specialists that may be relevant to increasing adoption in the VA.

Methods

The team (CL, ML, PG, 2 analysts under the guidance of GS and JS and support from RRK, and a biostatistician) conducted semistructured interviews with PCPs, specialists, and specialty division leaders who were employed by VA in 2016 and 2017. Specialties of interest were identified by the VA Office of Specialty Care and included cardiology, endocrinology, gastroenterology, and hematology.

E-Consult Procedures

Within the VA, the specific procedures used to initiate, triage and manage e-consults are coordinated at VA medical centers (VAMCs) and at the Veterans Integrated Service Network (VISN) regional level. E-consult can be requested by any clinician. Generally, e-consults are initiated by PCPs through standardized, specialty-specific templates. Recipients, typically specialists, respond by answering questions, suggesting additional testing and evaluation, or requesting an in-person visit. Communication is documented in the patient’s electronic health record (EHR). Specialists receive different levels of workload credit for responding to e-consults similar to a relative value unit reimbursement model. Training in the use of e-consults is available to practitioners but may vary at local and regional levels.

Recruitment

Our sample included PCPs, specialists, and specialty care division leaders. We first quantified e-consult rates (e-consults per 100 patient visits) between July 2016 and June 2017 at VA facilities within primary care and the 4 priority specialties and identified the 30 sites with the highest e-consult rates and 30 sites with the lowest e-consult rates. Sites with < 500 total visits, < 3 specialties, or without any e-consult visit during the study period were excluded. E-consult rates at community-based outpatient clinics were included with associated VAMCs. We then stratified PCPs by whether they were high or low users of e-consults (determined by the top and bottom users within each site) and credentials (MD vs nurse practitioner [NP] or physician assistant [PA]). Specialists were sampled based on their rate of use relative to colleagues within their site and the use rate of their division. We sampled division chiefs and individuals who had > 300 total visits and 1 e-consult during the study period. To recruit participants, the primary investigator sent an initial email and 2 reminder emails. The team followed up with respondents to schedule an interview.

Interview guides were designed to elicit rich descriptions of barriers and facilitators to e-consult use (eAppendix available at doi:10.12788/fp.0214). The team used the Practical Robust Implementation and Sustainability Model (PRISM), which considers factors along 6 domains for intervention planning, implementation, and sustainment.¹⁹ Telephone interviews lasted about 20 minutes and were conducted between September 2017 and March 2018. Interviews were recorded and transcribed verbatim.

Analysis

The team used an iterative, team-based, inductive/deductive approach to conventional content analysis.^20,21 Initial code categories were created so that we could identify e-consult best practices—facilitators of e-consult that were recommended by both PCPs and specialists. Inductive codes or labels applied to identify meaningful quotations, phrases, or key terms were used to identify emergent ideas and were added throughout coding after discussion among team members. Consensus was reached using a team-based approach.²¹ Four analysts independently coded the same 3 transcripts and met to discuss points of divergence and convergence. Analyses continued with emergent themes, categories, and conclusions. Atlas.ti. v.7 was used for coding and data management.²²

Results

We conducted 34 interviews with clinicians (Table 1) from 13 VISNs. Four best-practice themes emerged among both PCPs and specialists, including that e-consults (1) are best suited for certain clinical questions and patients; (2) require relevant background information from requesting clinicians and clear recommendations from responding clinicians; (3) are a novel opportunity to provide efficient, transparent care; and (4) may not be fully adopted due to low awareness. Supporting quotations for the following findings are provided in Table 2.

Specific Clinical Questions and Patients

PCPs described specific patients and questions for which they most frequently used e-consults, such as for medication changes (Q1), determining treatment steps (Q2,3), and or clarifying laboratory or imaging findings. PCPs frequently used e-consults for patients who did not require a physical examination or when specialists could make recommendations without seeing patients face-to-face (Q3). An important use of e-consults described by PCPs was for treating conditions they could manage within primary care if additional guidance were available (Q4). Several PCPs and specialists also noted that e-consults were particularly useful for patients who were unable to travel or did not want face-to-face appointments (Q5). Notably, PCPs and specialists mentioned situations for which e-consults were inappropriate, including when a detailed history or physical examination was needed, or if a complex condition was suspected (Q6).

Background Data and Clear Recommendations

Participants described necessary data that should be included in high-quality e-consults. Specialists voiced frustration in time-consuming chart reviews that were often necessary when these data were not provided by the requestor. In some cases, specialists were unable to access necessary EHR data, which delayed responses (Q7). PCPs noted that the most useful responses carefully considered the question, used current patient information to determine treatments, provided clear recommendations, and defined who was responsible for next steps (Q8). PCPs and specialists stated that e-consult templates that required relevant information facilitated high-quality e-consults. Neither wanted to waste the other clinician's time (Q8).

A Novel Opportunity

Many PCPs felt that e-consults improved communication (eg, efficiency, response time), established new communication between clinicians, and reduced patients’ appointment burden (Q10, Q11). Many specialists felt that e-consults improved documentation of communication between clinicians and increased transparency of clinical decisions (Q12). Additionally, many specialists mentioned that e-consults capture previously informal curbside consults, enabling them to receive workload credit (Q13).

Lack of Awareness

Some noted that the biggest barrier to e-consults was not being aware of them generally, or which specialties offer e-consults (Q14). One PCP described e-consults as the best kept secret and found value in sharing the utility of e-consults with colleagues (Q15). All participants, including those who did not frequently use e-consults, felt that e-consults improved the quality of care by providing more timely care or better answers to clinical questions (Q16). Several practitioners also felt that e-consults increased access to specialty care. For example, specialists reported that e-consults enabled them to better manage patient load by using e-consults to answer relatively simple questions, reserving face-to-face consults for more complex patients (Q17).

Discussion

The objective of this study was to identify potential best practices for e-consults that may help increase their quality and use within the VA. We built on prior studies that offered insights on PCP and specialists’ overall satisfaction with e-consult by identifying several themes relevant to the further adoption of e-consults in the VA and elsewhere without a face-to-face visit.^{8,13,14,16–18} Future work may be beneficial in identifying whether the study themes identified can explain variation in e-consult use or whether addressing these factors might lead to increased or higher quality e-consult use. We are unaware of any qualitative study of comparable scale in a different health care system. Further, this is the first study to assess perspectives on e-consults among those who initiate and respond to them within the same health care system. Perhaps the most important finding from this study is that e-consults are generally viewed favorably, which is a necessary leverage point to increase their adoption within the system.

Clinicians reported several benefits to e-consults, including timely responses to clinical questions, efficient communication, allow for documentation of specialist recommendations, and help capture workload. These benefits are consistent with prior literature that indicates both PCPs and specialists in the VA and other health care systems feel that e-consults improves communication, decreases unnecessary visits, and improves quality of care.^1,14,17,18 In particular, clinicians reported that e-consults improve their practice efficiency and efficacy. This is of critical importance given the pressures of providing timely access to primary and specialty care within the VA. Interestingly, many VA practitioners were unaware which specialties offered e-consults within their facilities, reflecting previous work showing that PCPs are often unaware of e-consult options.¹⁶ This may partially explain variation in e-consult use. Increasing awareness and educating clinicians on the benefits of e-consults may help promote use among non- and low users.

A common theme reported by both groups was the importance of providing necessary information within e-consult questions and responses. Specialists felt there was a need to ensure that PCPs provide relevant and patient-specific information that would enable them to efficiently and accurately answer questions without the need for extensive EHR review. This reflects previous work showing that specialists are often unable to respond to e-consult requests because they do not contain sufficient information.²² PCPs described a need to ensure that specialists’ responses included information that was detailed enough to make clinical decisions without the need for a reconsult. This highlights a common challenge to medical consultation, in that necessary or relevant information may not be apparent to all clinicians. To address this, there may be a role in developing enhanced, flexible templating that elicits necessary patient-specific information. Such a template may automatically pull relevant data from the EHR and prompt clinicians to provide important information. We did not assess how perspectives of templates varied, and further work could help define precisely what constitutes an effective template, including how it should capture appropriate patient data and how this impacts acceptability or use of e-consults generally. Collaboratively developed service agreements and e-consult templates could help guide PCPs and specialists to engage in efficient communication.

Another theme among both groups was that e-consult is most appropriate within specific clinical scenarios. Examples included review of laboratory results, questions about medication changes, or for patients who were reluctant to travel to appointments. Identifying and promoting specific opportunities for e-consults may help increase their use and align e-consult practices with scenarios that are likely to provide the most benefit to patients. For example, it could be helpful to understand the distance patients must travel for specialty care. Providing that information during clinical encounters could trigger clinicians to consider e-consults as an option. Future work might aim to identify clinical scenarios that clinicians feel are not well suited for e-consults and determine how to adapt them for those scenarios.

Limitations

Generalizability of these findings is limited given the qualitative study design. Participants’ descriptions of experiences with e-consults reflect the experiences of clinicians in the VA and may not reflect clinicians in other settings. We also interviewed a sample of clinicians who were already using e-consults. Important information could be learned from future work with those who have not yet adopted e-consult procedures or adopted and abandoned them.

Conclusions

E-consult is perceived as beneficial by VA PCPs and specialists. Participants suggested using e-consults for appropriate questions or patients and including necessary information and next steps in both the initial e-consult and response. Finding ways to facilitate e-consults with these suggestions in mind may increase delivery of high-quality e-consults. Future work could compare the findings of this work to similar work assessing clinicians perceptions of e-consults outside of the VA.

It has been 19 years since the publication of the landmark AFFIRM trial.¹ At the time of publication, a “rhythm control” strategy was the preferred therapy, with a rate control approach an accepted alternative. AFFIRM showed no mortality benefit of rhythm control over rate control, and its result dramatically shifted the paradigm of atrial fibrillation (AF) management. However, the high crossover rate between treatment arms may have biased the study toward the null hypothesis. Post hoc analyses of AFFIRM and other observational studies indicate that sinus rhythm was associated with a lower risk of death.² Since AFFIRM, technical advances and procedural experience have improved the safety and efficacy of catheter ablation (CA), and recently published randomized trials have shown improved outcomes with rhythm control. This Progress Note summarizes the recent evidence, updating hospitalists on the management of AF, including inpatient cardioversion, patient selection for CA, use of antiarrhythmic drugs (AADs), and lifestyle modifications associated with maintenance of sinus rhythm.

A PubMed search for recent publications using combined the MeSH terms “atrial fibrillation” with “catheter ablation,” “antiarrhythmic drugs,” and “lifestyle modifications.” Our review filtered for randomized trials, guidelines, and selected reviews. 

Urgent cardioversion is recommended for those with hemodynamic instability, AF associated ischemia, or acute heart failure.³ Whether to perform elective cardioversion depends on AF duration, symptoms, and the initial evaluation for structural heart disease or reversible causes of AF. Evaluation for new-onset AF includes eliciting a history of AF-associated comorbidities (hypertension, alcohol use, obstructive sleep apnea) and an echocardiogram and thyroid, renal, and liver function tests.³ Stable patients with AF precipitated by high-catecholamine states (eg, postoperative AF, sepsis, hyperthyroidism, pulmonary embolism, substance use) require management of the underlying condition before considering rhythm control. Inpatient electrical or pharmacologic cardioversion may be considered for patients with stable, new-onset AF sufficiently symptomatic to require hospitalization. Pre-procedure anticoagulation and a transesophageal echocardiogram to rule out left atrial thrombus before cardioversion is preferred for a first episode of AF suspected of lasting longer than 48 hours but requires anesthesia and considerable resources. In resource-constrained settings, patients asymptomatic once rate controlled may be safely discharged with a referral for outpatient cardioversion.

For patients with structural heart disease (left atrial dilation), previously failed cardioversion, or recurrent AF, initiating AADs (eg, ibutilide, amiodarone) before electrical cardioversion can improve the success rate of cardioversion.³ Ibutilide infusion requires cardiology consultation and postinfusion hemodynamic and QTc monitoring. Defer immediate cardioversion among stable patients unable to continue a minimum of 4 weeks of anticoagulation or with comorbidities for which risks of cardioversion outweigh benefits.

Successful maintenance of sinus rhythm is associated with reduced symptom burden and improved quality of life and is recommended for patients with persistent symptoms, failure of rate control, younger age, first episode of AF, or patient preference for rhythm control.³ Since AF progression results in irreversible cardiac remodeling, earlier rhythm control may prevent further atrial remodeling and atrial myopathy.

The EAST-AFNET 4 trial evaluated a rhythm-control strategy in patients with AF duration <12 months and who met two of the following: age > 65 years, female sex, heart failure, hypertension, diabetes, coronary artery disease, and chronic kidney disease.⁴ Maintenance of sinus rhythm was associated with a lower composite outcome of adverse cardiovascular outcomes and death from cardiovascular causes over 5 years compared to rate control (3.9/100 person-years vs 5.0/100 person-years, P = .005). Interestingly, roughly 20% of patients underwent CA and the remainder received AADs. The large proportion of patients treated with AADs raises the question of why the results differed from AFFIRM. There are four primary differences between these trials to consider. First, EAST-AFNET 4 used an early rhythm-control strategy (<12 months). Second, nearly all patients in EAST-AFNET 4 continued guideline-recommend anticoagulation compared to 70% receiving rhythm control in AFFIRM. Third, in AFFIRM, 62.8% of patients received amiodarone, which has significant long-term adverse effects compared to 11.8% by the end of EAST-AFNET 4. Finally, increased use of CA in EAST-AFNET 4 may have contributed to the success of rhythm control. In patients with cardiovascular disease or cardiovascular risk factors, a rhythm-control strategy will be best if implemented early (<12 months), before the development of long-standing persistent AF, and if clinicians adhere to anticoagulation recommendations.

Antiarrhythmic Drugs

Antiarrhythmic drug use prior to CA remains the cornerstone of a rhythm-control strategy for patients meeting EAST-AFNET 4 trial criteria or patient preference for medical management. Hospitalists’ knowledge of key differences between AADs used in EAST-AFNET 4 and AFFIRM as well as American Heart Association/American College of Cardiology/Heart Rhythm Society (AHA/ACC/HRS) guideline recommendations help avoid harmful AAD prescribing. Notably, 21.9% of patients in AFFIRM received AADs no longer recommended to maintain sinus rhythm in the AHA/ACC/HRS guidelines (quinidine, disopyramide, procainamide, moricizine).³ For patients without structural heart disease, flecainide, propafenone, sotalol, or dronedarone are preferred. Dronedarone and sotalol remain an option for those with coronary artery disease. For patients with heart failure with reduced ejection fraction (HFrEF), amiodarone and dofetilide are preferred (Table).³

Catheter Ablation

The AHA/ACC/HRS guidelines offer a Ia recommendation for CA in patients with recurrent, symptomatic AF who failed AAD therapy. Initial CA is a IIa recommendation and is increasingly common for patients with paroxysmal AF who prefer this strategy to long-term AAD use.³ Recent trials evaluated CA as a primary treatment modality in patients with heart failure and as initial management before AADs.

Initial Catheter Ablation

The CABANA trial compared CA with AADs as an initial approach for maintaining sinus rhythm.⁵ In the intention-to-treat analysis, there was no difference in all death or disabling stroke between AAD therapy and CA at 5-year follow-up. The results are limited by a 27.5% crossover rate from drug therapy to CA. The per-protocol analysis based on the treatment received favored CA for the primary composite outcome of death, disabling stroke, serious bleeding, or cardiac arrest at 12 months. The STOP-AF and EARLY-AF trials found that initial CA was more successful in maintaining freedom from atrial arrhythmias (74.6% vs 45.0%, P < .001)⁶ and fewer symptomatic atrial arrhythmias among patients with paroxysmal AF compared to AADs, without significant CA-associated adverse events.^6,7

While hospitalists should interpret the per-protocol analysis cautiously when determining the clinical benefit, these trials indicate initial CA is as safe as AADs and improves freedom from AF. Duration of AF, knowledge of periprocedural anticoagulation recommendations, and CA procedural complications are important when recommending CA (Figure). Efficacy of CA is approximately 70% in paroxysmal AF and decreases for persistent and long-standing AF.⁶ Complications of CA include venous access site hematoma, cardiac tamponade, phrenic nerve injury, pulmonary vein stenosis, atrial-esophageal fistula, left atrial flutter, and stroke due to endothelial injury and intraprocedural thrombosis.³ Therapeutic anticoagulation is required before CA and for at least 2 months post ablation regardless of the CHA₂DS₂-VASc score.³

Catheter Ablation Plus Antiarrhythmics

Ongoing AADs following CA may suppress AF triggers, especially in patients with persistent AF or high-risk for recurrence post ablation (left atrial dilation). The AMIO-CAT trial found that 4 weeks of amiodarone after ablation reduced early AF recurrence at 3 months (34% vs 53%, P = .006), arrhythmia-related hospitalizations, and need for cardioversion in patients with paroxysmal and persistent AF.⁸ However, amiodarone did not reduce recurrent atrial tachyarrhythmias at 6 months. The POWDER-AF trial evaluated AAD use for 1 year after CA in patients with drug-refractory paroxysmal AF.⁹ Continuation of class IC (eg, flecainide) and III (eg, amiodarone) AADs resulted in a near 20% absolute risk reduction in recurrent atrial arrhythmias and reduced the need for repeat CA. These trials suggest that discharging patients on adjunctive AADs decreases early recurrence of AF and arrhythmia-related hospitalizations; however, studies evaluating additional clinical outcomes are needed.

Heart Failure

The AATAC trial found CA was superior to amiodarone therapy at maintaining freedom from AF and reducing unplanned hospitalizations and mortality among patients with persistent AF and HFrEF.¹⁰ The larger CASTLE-AF trial randomized patients with an ejection fraction below 35% and NYHA class II or greater symptoms with symptomatic paroxysmal AF or persistent AF in whom AAD therapy failed to CA or medical therapy.¹¹ The CA group experienced lower cardiovascular mortality (11.2% vs 22.3%, P = .009) and fewer heart failure hospitalizations (20.7% vs 35.9%, P = .004). The subsequent AMICA trial did not find a benefit of CA in patients with HFrEF and persistent or long-standing persistent AF; however, this trial was limited to 12 months, whereas the benefit of CA in CASTLE-AF was observed after 12 months.¹² Also, AMICA enrolled patients with higher NYHA class. Therefore, hospitalists should refer AF patients with left ventricular systolic dysfunction and NYHA II or III symptoms for CA. Comparing AMICA and CASTLE-AF suggests earlier referral for CA, prior to the development of worsening heart failure symptoms, may improve outcomes.

Data for patients with heart failure with preserved EF (HFpEF) is limited. One small trial showed reduced heart failure hospitalizations in HFpEF patients treated with CA compared to AADs or beta-blockers.¹³ It is reasonable to refer HFpEF patients with persisting symptoms or reduced quality of life for CA.

The AHA Scientific Statement on Lifestyle and Risk Factor Modification for Reduction of Atrial Fibrillation delineates risk factors that increase the incidence of AF, including alcohol consumption, obstructive sleep apnea, hypertension, and obesity.¹⁴ Among regular alcohol consumers with paroxysmal or persistent AF managed with a rhythm-control strategy, cessation of alcohol has been shown to significantly lower the incidence of recurrent AF (53.0% vs 73.0%, P = .005), and lead to a longer time until recurrence of AF compared to patients regularly consuming alcohol.¹⁵ Among patients with obstructive sleep apnea, a systematic review of nonrandomized studies showed continuous positive airway pressure is associated with maintenance of sinus rhythm.¹⁴ Control of these risk factors is associated with up to approximately 40% of patients maintaining sinus rhythm without intervention, and hospitalists should encourage lifestyle modification to maximize the probability of maintaining sinus rhythm. 

Hospitalists frequently determine the best initial management strategy for patients admitted with new-onset AF, and recent literature may shift more patients towards management with rhythm control. Based on the trials reviewed in this Progress Note, hospitalists should recommend a rhythm-control strategy for patients with symptomatic, paroxysmal, or persistent AF of <12 months’ duration and refer patients with HFrEF for CA. Adherence to guideline recommendations is essential when prescribing AADs to avoid adverse drug events. It is vital to ensure patients managed with a rhythm-control strategy receive anticoagulation for 4 weeks post cardioversion or 2 months post CA with long-term anticoagulation based on CHA₂DS₂-VASc score. Finally, admissions for AF should serve as a catalyst to communicate to patients the importance of addressing obstructive sleep apnea, obesity, and alcohol use disorders. Applying these evidence-based practices will enable hospitalists to make clinical decisions that improve symptom burden and survival for patients with AF.

It has been 19 years since the publication of the landmark AFFIRM trial.¹ At the time of publication, a “rhythm control” strategy was the preferred therapy, with a rate control approach an accepted alternative. AFFIRM showed no mortality benefit of rhythm control over rate control, and its result dramatically shifted the paradigm of atrial fibrillation (AF) management. However, the high crossover rate between treatment arms may have biased the study toward the null hypothesis. Post hoc analyses of AFFIRM and other observational studies indicate that sinus rhythm was associated with a lower risk of death.² Since AFFIRM, technical advances and procedural experience have improved the safety and efficacy of catheter ablation (CA), and recently published randomized trials have shown improved outcomes with rhythm control. This Progress Note summarizes the recent evidence, updating hospitalists on the management of AF, including inpatient cardioversion, patient selection for CA, use of antiarrhythmic drugs (AADs), and lifestyle modifications associated with maintenance of sinus rhythm.

A PubMed search for recent publications using combined the MeSH terms “atrial fibrillation” with “catheter ablation,” “antiarrhythmic drugs,” and “lifestyle modifications.” Our review filtered for randomized trials, guidelines, and selected reviews. 

Urgent cardioversion is recommended for those with hemodynamic instability, AF associated ischemia, or acute heart failure.³ Whether to perform elective cardioversion depends on AF duration, symptoms, and the initial evaluation for structural heart disease or reversible causes of AF. Evaluation for new-onset AF includes eliciting a history of AF-associated comorbidities (hypertension, alcohol use, obstructive sleep apnea) and an echocardiogram and thyroid, renal, and liver function tests.³ Stable patients with AF precipitated by high-catecholamine states (eg, postoperative AF, sepsis, hyperthyroidism, pulmonary embolism, substance use) require management of the underlying condition before considering rhythm control. Inpatient electrical or pharmacologic cardioversion may be considered for patients with stable, new-onset AF sufficiently symptomatic to require hospitalization. Pre-procedure anticoagulation and a transesophageal echocardiogram to rule out left atrial thrombus before cardioversion is preferred for a first episode of AF suspected of lasting longer than 48 hours but requires anesthesia and considerable resources. In resource-constrained settings, patients asymptomatic once rate controlled may be safely discharged with a referral for outpatient cardioversion.

For patients with structural heart disease (left atrial dilation), previously failed cardioversion, or recurrent AF, initiating AADs (eg, ibutilide, amiodarone) before electrical cardioversion can improve the success rate of cardioversion.³ Ibutilide infusion requires cardiology consultation and postinfusion hemodynamic and QTc monitoring. Defer immediate cardioversion among stable patients unable to continue a minimum of 4 weeks of anticoagulation or with comorbidities for which risks of cardioversion outweigh benefits.

Successful maintenance of sinus rhythm is associated with reduced symptom burden and improved quality of life and is recommended for patients with persistent symptoms, failure of rate control, younger age, first episode of AF, or patient preference for rhythm control.³ Since AF progression results in irreversible cardiac remodeling, earlier rhythm control may prevent further atrial remodeling and atrial myopathy.

The EAST-AFNET 4 trial evaluated a rhythm-control strategy in patients with AF duration <12 months and who met two of the following: age > 65 years, female sex, heart failure, hypertension, diabetes, coronary artery disease, and chronic kidney disease.⁴ Maintenance of sinus rhythm was associated with a lower composite outcome of adverse cardiovascular outcomes and death from cardiovascular causes over 5 years compared to rate control (3.9/100 person-years vs 5.0/100 person-years, P = .005). Interestingly, roughly 20% of patients underwent CA and the remainder received AADs. The large proportion of patients treated with AADs raises the question of why the results differed from AFFIRM. There are four primary differences between these trials to consider. First, EAST-AFNET 4 used an early rhythm-control strategy (<12 months). Second, nearly all patients in EAST-AFNET 4 continued guideline-recommend anticoagulation compared to 70% receiving rhythm control in AFFIRM. Third, in AFFIRM, 62.8% of patients received amiodarone, which has significant long-term adverse effects compared to 11.8% by the end of EAST-AFNET 4. Finally, increased use of CA in EAST-AFNET 4 may have contributed to the success of rhythm control. In patients with cardiovascular disease or cardiovascular risk factors, a rhythm-control strategy will be best if implemented early (<12 months), before the development of long-standing persistent AF, and if clinicians adhere to anticoagulation recommendations.

Antiarrhythmic Drugs

Antiarrhythmic drug use prior to CA remains the cornerstone of a rhythm-control strategy for patients meeting EAST-AFNET 4 trial criteria or patient preference for medical management. Hospitalists’ knowledge of key differences between AADs used in EAST-AFNET 4 and AFFIRM as well as American Heart Association/American College of Cardiology/Heart Rhythm Society (AHA/ACC/HRS) guideline recommendations help avoid harmful AAD prescribing. Notably, 21.9% of patients in AFFIRM received AADs no longer recommended to maintain sinus rhythm in the AHA/ACC/HRS guidelines (quinidine, disopyramide, procainamide, moricizine).³ For patients without structural heart disease, flecainide, propafenone, sotalol, or dronedarone are preferred. Dronedarone and sotalol remain an option for those with coronary artery disease. For patients with heart failure with reduced ejection fraction (HFrEF), amiodarone and dofetilide are preferred (Table).³

Catheter Ablation

The AHA/ACC/HRS guidelines offer a Ia recommendation for CA in patients with recurrent, symptomatic AF who failed AAD therapy. Initial CA is a IIa recommendation and is increasingly common for patients with paroxysmal AF who prefer this strategy to long-term AAD use.³ Recent trials evaluated CA as a primary treatment modality in patients with heart failure and as initial management before AADs.

Initial Catheter Ablation

The CABANA trial compared CA with AADs as an initial approach for maintaining sinus rhythm.⁵ In the intention-to-treat analysis, there was no difference in all death or disabling stroke between AAD therapy and CA at 5-year follow-up. The results are limited by a 27.5% crossover rate from drug therapy to CA. The per-protocol analysis based on the treatment received favored CA for the primary composite outcome of death, disabling stroke, serious bleeding, or cardiac arrest at 12 months. The STOP-AF and EARLY-AF trials found that initial CA was more successful in maintaining freedom from atrial arrhythmias (74.6% vs 45.0%, P < .001)⁶ and fewer symptomatic atrial arrhythmias among patients with paroxysmal AF compared to AADs, without significant CA-associated adverse events.^6,7

While hospitalists should interpret the per-protocol analysis cautiously when determining the clinical benefit, these trials indicate initial CA is as safe as AADs and improves freedom from AF. Duration of AF, knowledge of periprocedural anticoagulation recommendations, and CA procedural complications are important when recommending CA (Figure). Efficacy of CA is approximately 70% in paroxysmal AF and decreases for persistent and long-standing AF.⁶ Complications of CA include venous access site hematoma, cardiac tamponade, phrenic nerve injury, pulmonary vein stenosis, atrial-esophageal fistula, left atrial flutter, and stroke due to endothelial injury and intraprocedural thrombosis.³ Therapeutic anticoagulation is required before CA and for at least 2 months post ablation regardless of the CHA₂DS₂-VASc score.³

Catheter Ablation Plus Antiarrhythmics

Ongoing AADs following CA may suppress AF triggers, especially in patients with persistent AF or high-risk for recurrence post ablation (left atrial dilation). The AMIO-CAT trial found that 4 weeks of amiodarone after ablation reduced early AF recurrence at 3 months (34% vs 53%, P = .006), arrhythmia-related hospitalizations, and need for cardioversion in patients with paroxysmal and persistent AF.⁸ However, amiodarone did not reduce recurrent atrial tachyarrhythmias at 6 months. The POWDER-AF trial evaluated AAD use for 1 year after CA in patients with drug-refractory paroxysmal AF.⁹ Continuation of class IC (eg, flecainide) and III (eg, amiodarone) AADs resulted in a near 20% absolute risk reduction in recurrent atrial arrhythmias and reduced the need for repeat CA. These trials suggest that discharging patients on adjunctive AADs decreases early recurrence of AF and arrhythmia-related hospitalizations; however, studies evaluating additional clinical outcomes are needed.

Heart Failure

The AATAC trial found CA was superior to amiodarone therapy at maintaining freedom from AF and reducing unplanned hospitalizations and mortality among patients with persistent AF and HFrEF.¹⁰ The larger CASTLE-AF trial randomized patients with an ejection fraction below 35% and NYHA class II or greater symptoms with symptomatic paroxysmal AF or persistent AF in whom AAD therapy failed to CA or medical therapy.¹¹ The CA group experienced lower cardiovascular mortality (11.2% vs 22.3%, P = .009) and fewer heart failure hospitalizations (20.7% vs 35.9%, P = .004). The subsequent AMICA trial did not find a benefit of CA in patients with HFrEF and persistent or long-standing persistent AF; however, this trial was limited to 12 months, whereas the benefit of CA in CASTLE-AF was observed after 12 months.¹² Also, AMICA enrolled patients with higher NYHA class. Therefore, hospitalists should refer AF patients with left ventricular systolic dysfunction and NYHA II or III symptoms for CA. Comparing AMICA and CASTLE-AF suggests earlier referral for CA, prior to the development of worsening heart failure symptoms, may improve outcomes.

Data for patients with heart failure with preserved EF (HFpEF) is limited. One small trial showed reduced heart failure hospitalizations in HFpEF patients treated with CA compared to AADs or beta-blockers.¹³ It is reasonable to refer HFpEF patients with persisting symptoms or reduced quality of life for CA.

The AHA Scientific Statement on Lifestyle and Risk Factor Modification for Reduction of Atrial Fibrillation delineates risk factors that increase the incidence of AF, including alcohol consumption, obstructive sleep apnea, hypertension, and obesity.¹⁴ Among regular alcohol consumers with paroxysmal or persistent AF managed with a rhythm-control strategy, cessation of alcohol has been shown to significantly lower the incidence of recurrent AF (53.0% vs 73.0%, P = .005), and lead to a longer time until recurrence of AF compared to patients regularly consuming alcohol.¹⁵ Among patients with obstructive sleep apnea, a systematic review of nonrandomized studies showed continuous positive airway pressure is associated with maintenance of sinus rhythm.¹⁴ Control of these risk factors is associated with up to approximately 40% of patients maintaining sinus rhythm without intervention, and hospitalists should encourage lifestyle modification to maximize the probability of maintaining sinus rhythm. 

Hospitalists frequently determine the best initial management strategy for patients admitted with new-onset AF, and recent literature may shift more patients towards management with rhythm control. Based on the trials reviewed in this Progress Note, hospitalists should recommend a rhythm-control strategy for patients with symptomatic, paroxysmal, or persistent AF of <12 months’ duration and refer patients with HFrEF for CA. Adherence to guideline recommendations is essential when prescribing AADs to avoid adverse drug events. It is vital to ensure patients managed with a rhythm-control strategy receive anticoagulation for 4 weeks post cardioversion or 2 months post CA with long-term anticoagulation based on CHA₂DS₂-VASc score. Finally, admissions for AF should serve as a catalyst to communicate to patients the importance of addressing obstructive sleep apnea, obesity, and alcohol use disorders. Applying these evidence-based practices will enable hospitalists to make clinical decisions that improve symptom burden and survival for patients with AF.

It has been 19 years since the publication of the landmark AFFIRM trial.¹ At the time of publication, a “rhythm control” strategy was the preferred therapy, with a rate control approach an accepted alternative. AFFIRM showed no mortality benefit of rhythm control over rate control, and its result dramatically shifted the paradigm of atrial fibrillation (AF) management. However, the high crossover rate between treatment arms may have biased the study toward the null hypothesis. Post hoc analyses of AFFIRM and other observational studies indicate that sinus rhythm was associated with a lower risk of death.² Since AFFIRM, technical advances and procedural experience have improved the safety and efficacy of catheter ablation (CA), and recently published randomized trials have shown improved outcomes with rhythm control. This Progress Note summarizes the recent evidence, updating hospitalists on the management of AF, including inpatient cardioversion, patient selection for CA, use of antiarrhythmic drugs (AADs), and lifestyle modifications associated with maintenance of sinus rhythm.

A PubMed search for recent publications using combined the MeSH terms “atrial fibrillation” with “catheter ablation,” “antiarrhythmic drugs,” and “lifestyle modifications.” Our review filtered for randomized trials, guidelines, and selected reviews. 

Urgent cardioversion is recommended for those with hemodynamic instability, AF associated ischemia, or acute heart failure.³ Whether to perform elective cardioversion depends on AF duration, symptoms, and the initial evaluation for structural heart disease or reversible causes of AF. Evaluation for new-onset AF includes eliciting a history of AF-associated comorbidities (hypertension, alcohol use, obstructive sleep apnea) and an echocardiogram and thyroid, renal, and liver function tests.³ Stable patients with AF precipitated by high-catecholamine states (eg, postoperative AF, sepsis, hyperthyroidism, pulmonary embolism, substance use) require management of the underlying condition before considering rhythm control. Inpatient electrical or pharmacologic cardioversion may be considered for patients with stable, new-onset AF sufficiently symptomatic to require hospitalization. Pre-procedure anticoagulation and a transesophageal echocardiogram to rule out left atrial thrombus before cardioversion is preferred for a first episode of AF suspected of lasting longer than 48 hours but requires anesthesia and considerable resources. In resource-constrained settings, patients asymptomatic once rate controlled may be safely discharged with a referral for outpatient cardioversion.

For patients with structural heart disease (left atrial dilation), previously failed cardioversion, or recurrent AF, initiating AADs (eg, ibutilide, amiodarone) before electrical cardioversion can improve the success rate of cardioversion.³ Ibutilide infusion requires cardiology consultation and postinfusion hemodynamic and QTc monitoring. Defer immediate cardioversion among stable patients unable to continue a minimum of 4 weeks of anticoagulation or with comorbidities for which risks of cardioversion outweigh benefits.

Successful maintenance of sinus rhythm is associated with reduced symptom burden and improved quality of life and is recommended for patients with persistent symptoms, failure of rate control, younger age, first episode of AF, or patient preference for rhythm control.³ Since AF progression results in irreversible cardiac remodeling, earlier rhythm control may prevent further atrial remodeling and atrial myopathy.

The EAST-AFNET 4 trial evaluated a rhythm-control strategy in patients with AF duration <12 months and who met two of the following: age > 65 years, female sex, heart failure, hypertension, diabetes, coronary artery disease, and chronic kidney disease.⁴ Maintenance of sinus rhythm was associated with a lower composite outcome of adverse cardiovascular outcomes and death from cardiovascular causes over 5 years compared to rate control (3.9/100 person-years vs 5.0/100 person-years, P = .005). Interestingly, roughly 20% of patients underwent CA and the remainder received AADs. The large proportion of patients treated with AADs raises the question of why the results differed from AFFIRM. There are four primary differences between these trials to consider. First, EAST-AFNET 4 used an early rhythm-control strategy (<12 months). Second, nearly all patients in EAST-AFNET 4 continued guideline-recommend anticoagulation compared to 70% receiving rhythm control in AFFIRM. Third, in AFFIRM, 62.8% of patients received amiodarone, which has significant long-term adverse effects compared to 11.8% by the end of EAST-AFNET 4. Finally, increased use of CA in EAST-AFNET 4 may have contributed to the success of rhythm control. In patients with cardiovascular disease or cardiovascular risk factors, a rhythm-control strategy will be best if implemented early (<12 months), before the development of long-standing persistent AF, and if clinicians adhere to anticoagulation recommendations.

Antiarrhythmic Drugs

Antiarrhythmic drug use prior to CA remains the cornerstone of a rhythm-control strategy for patients meeting EAST-AFNET 4 trial criteria or patient preference for medical management. Hospitalists’ knowledge of key differences between AADs used in EAST-AFNET 4 and AFFIRM as well as American Heart Association/American College of Cardiology/Heart Rhythm Society (AHA/ACC/HRS) guideline recommendations help avoid harmful AAD prescribing. Notably, 21.9% of patients in AFFIRM received AADs no longer recommended to maintain sinus rhythm in the AHA/ACC/HRS guidelines (quinidine, disopyramide, procainamide, moricizine).³ For patients without structural heart disease, flecainide, propafenone, sotalol, or dronedarone are preferred. Dronedarone and sotalol remain an option for those with coronary artery disease. For patients with heart failure with reduced ejection fraction (HFrEF), amiodarone and dofetilide are preferred (Table).³

Catheter Ablation

The AHA/ACC/HRS guidelines offer a Ia recommendation for CA in patients with recurrent, symptomatic AF who failed AAD therapy. Initial CA is a IIa recommendation and is increasingly common for patients with paroxysmal AF who prefer this strategy to long-term AAD use.³ Recent trials evaluated CA as a primary treatment modality in patients with heart failure and as initial management before AADs.

Initial Catheter Ablation

The CABANA trial compared CA with AADs as an initial approach for maintaining sinus rhythm.⁵ In the intention-to-treat analysis, there was no difference in all death or disabling stroke between AAD therapy and CA at 5-year follow-up. The results are limited by a 27.5% crossover rate from drug therapy to CA. The per-protocol analysis based on the treatment received favored CA for the primary composite outcome of death, disabling stroke, serious bleeding, or cardiac arrest at 12 months. The STOP-AF and EARLY-AF trials found that initial CA was more successful in maintaining freedom from atrial arrhythmias (74.6% vs 45.0%, P < .001)⁶ and fewer symptomatic atrial arrhythmias among patients with paroxysmal AF compared to AADs, without significant CA-associated adverse events.^6,7

While hospitalists should interpret the per-protocol analysis cautiously when determining the clinical benefit, these trials indicate initial CA is as safe as AADs and improves freedom from AF. Duration of AF, knowledge of periprocedural anticoagulation recommendations, and CA procedural complications are important when recommending CA (Figure). Efficacy of CA is approximately 70% in paroxysmal AF and decreases for persistent and long-standing AF.⁶ Complications of CA include venous access site hematoma, cardiac tamponade, phrenic nerve injury, pulmonary vein stenosis, atrial-esophageal fistula, left atrial flutter, and stroke due to endothelial injury and intraprocedural thrombosis.³ Therapeutic anticoagulation is required before CA and for at least 2 months post ablation regardless of the CHA₂DS₂-VASc score.³

Catheter Ablation Plus Antiarrhythmics

Ongoing AADs following CA may suppress AF triggers, especially in patients with persistent AF or high-risk for recurrence post ablation (left atrial dilation). The AMIO-CAT trial found that 4 weeks of amiodarone after ablation reduced early AF recurrence at 3 months (34% vs 53%, P = .006), arrhythmia-related hospitalizations, and need for cardioversion in patients with paroxysmal and persistent AF.⁸ However, amiodarone did not reduce recurrent atrial tachyarrhythmias at 6 months. The POWDER-AF trial evaluated AAD use for 1 year after CA in patients with drug-refractory paroxysmal AF.⁹ Continuation of class IC (eg, flecainide) and III (eg, amiodarone) AADs resulted in a near 20% absolute risk reduction in recurrent atrial arrhythmias and reduced the need for repeat CA. These trials suggest that discharging patients on adjunctive AADs decreases early recurrence of AF and arrhythmia-related hospitalizations; however, studies evaluating additional clinical outcomes are needed.

Heart Failure

The AATAC trial found CA was superior to amiodarone therapy at maintaining freedom from AF and reducing unplanned hospitalizations and mortality among patients with persistent AF and HFrEF.¹⁰ The larger CASTLE-AF trial randomized patients with an ejection fraction below 35% and NYHA class II or greater symptoms with symptomatic paroxysmal AF or persistent AF in whom AAD therapy failed to CA or medical therapy.¹¹ The CA group experienced lower cardiovascular mortality (11.2% vs 22.3%, P = .009) and fewer heart failure hospitalizations (20.7% vs 35.9%, P = .004). The subsequent AMICA trial did not find a benefit of CA in patients with HFrEF and persistent or long-standing persistent AF; however, this trial was limited to 12 months, whereas the benefit of CA in CASTLE-AF was observed after 12 months.¹² Also, AMICA enrolled patients with higher NYHA class. Therefore, hospitalists should refer AF patients with left ventricular systolic dysfunction and NYHA II or III symptoms for CA. Comparing AMICA and CASTLE-AF suggests earlier referral for CA, prior to the development of worsening heart failure symptoms, may improve outcomes.

Data for patients with heart failure with preserved EF (HFpEF) is limited. One small trial showed reduced heart failure hospitalizations in HFpEF patients treated with CA compared to AADs or beta-blockers.¹³ It is reasonable to refer HFpEF patients with persisting symptoms or reduced quality of life for CA.

The AHA Scientific Statement on Lifestyle and Risk Factor Modification for Reduction of Atrial Fibrillation delineates risk factors that increase the incidence of AF, including alcohol consumption, obstructive sleep apnea, hypertension, and obesity.¹⁴ Among regular alcohol consumers with paroxysmal or persistent AF managed with a rhythm-control strategy, cessation of alcohol has been shown to significantly lower the incidence of recurrent AF (53.0% vs 73.0%, P = .005), and lead to a longer time until recurrence of AF compared to patients regularly consuming alcohol.¹⁵ Among patients with obstructive sleep apnea, a systematic review of nonrandomized studies showed continuous positive airway pressure is associated with maintenance of sinus rhythm.¹⁴ Control of these risk factors is associated with up to approximately 40% of patients maintaining sinus rhythm without intervention, and hospitalists should encourage lifestyle modification to maximize the probability of maintaining sinus rhythm. 

Hospitalists frequently determine the best initial management strategy for patients admitted with new-onset AF, and recent literature may shift more patients towards management with rhythm control. Based on the trials reviewed in this Progress Note, hospitalists should recommend a rhythm-control strategy for patients with symptomatic, paroxysmal, or persistent AF of <12 months’ duration and refer patients with HFrEF for CA. Adherence to guideline recommendations is essential when prescribing AADs to avoid adverse drug events. It is vital to ensure patients managed with a rhythm-control strategy receive anticoagulation for 4 weeks post cardioversion or 2 months post CA with long-term anticoagulation based on CHA₂DS₂-VASc score. Finally, admissions for AF should serve as a catalyst to communicate to patients the importance of addressing obstructive sleep apnea, obesity, and alcohol use disorders. Applying these evidence-based practices will enable hospitalists to make clinical decisions that improve symptom burden and survival for patients with AF.

Rosa* was one of my first patients as an intern rotating at the county hospital. Her marriage had disintegrated years earlier. To cope with depression, she hid a daily ritual of orange juice and vodka from her children. She worked as a cashier, until nausea and fatigue overwhelmed her.

The first time I met her she sat on the gurney: petite, tanned, and pregnant. Then I saw her yellow eyes and revised: temporal wasting, jaundiced, and swollen with ascites. Rosa didn’t know that alcohol could cause liver disease. Without insurance or access to primary care, her untreated alcohol use disorder (AUD) and depression had snowballed for years. 

Midway through my intern year, I’d taken care of many people with AUD. However, I’d barely learned anything about it as a medical student, though we’d spent weeks studying esoteric diseases, that now––9 years after medical school––I still have not encountered. 

Among the 28.3 million individuals in the United States with AUD, only 1% receive medication treatment.¹ In the United States, unhealthy alcohol use accounts for more than 95,000 deaths each year.² This number likely under-captures alcohol-related mortality and is higher now given recent reports of increasing alcohol-related deaths and prevalence of unhealthy alcohol use, especially among women, younger age groups, and marginalized populations.^3-5 

Rosa had alcohol-related hepatitis, which can cause severe inflammation and liver failure and quickly lead to death. As her liver failure progressed, I asked the gastroenterologists, “What other treatments can we offer? Is she a liver transplant candidate?” “Nothing” and “No” they answered.

Later, I emailed the hepatologist and transplant surgeon begging them to reevaluate her transplantation candidacy, but they told me there was no exception to the institution’s 6-month sobriety rule.

Maintaining a 6-month sobriety period is not an evidence-based criterion for transplantation. However, 50% of transplant centers do not perform transplantation prior to 6 months of alcohol abstinence for alcohol-related hepatitis due to concern for return to drinking after transplant.⁶ This practice may promote bias in patient selection for transplantation. A recent study found that individuals with alcohol-related liver disease transplanted before 6 months of abstinence had similar rates of survival and return to drinking compared to those who abstained from alcohol for 6 months and participated in AUD treatment before transplantation.⁷

There are other liver transplant practices that result in inequities for individuals with substance use disorders (SUD). Some liver transplant centers consider being on a medication for opioid use disorder a contraindication for transplantation—even if the individual is in recovery and abstaining from substances.⁸ Others mandate that individuals with alcohol-related liver disease attend Alcoholics Anonymous (AA) meetings prior to transplant. While mutual help groups, including AA, may benefit some individuals, different approaches work for different people.⁹ Other psychosocial interventions (eg, cognitive-behavioral therapy, contingency management, and residential treatment) and medications also help individuals reduce or stop drinking. Some meet their goals without any treatment. Addiction care works best when it respects autonomy and meets individuals where they are by allowing them to decide among options.

While organ allocations are a crystalized example of inequities in addiction care, they are also ethically complex. Many individuals—with and without SUD—die on waiting lists and must meet stringent transplantation criteria. However, we can at least remove the unnecessary biases that compound inequities in care people with SUD already face.

As Rosa’s liver succumbed, her kidneys failed too, and she required dialysis. She sensed what was coming. “I want everything…for now. I need to take care of my children.” I, too, wanted Rosa to live and see her youngest start kindergarten.

A few days before her discharge, I walked to the pharmacy and bought a purple journal. In a rare moment, I found Rosa alone in her room, without her ex-husband, sister, and mother, who rarely left her bedside. Together, we called AA and explored whether she could start participating in phone meetings from the hospital. I explained that one way to document a commitment to sobriety, as the transplant center’s rules dictated, was to attend and document AA meetings in this notebook. “In 5 months, you will be a liver transplant candidate,” I remember saying, wishing it to fruition.

I became Rosa’s primary care physician and saw her in clinic. Over the next few weeks, her skin took on an ashen tone. Sleep escaped her and her thoughts and speech blurred. Her walk slowed and she needed a wheelchair. The quiet fierceness that had defined her dissipated as encephalopathy took over. But until our last visit, she brought her purple journal, tracking the AA meetings she’d attended. Dialysis became intolerable, but not before Rosa made care arrangements for her girls. When that happened, she stopped dialysis and went to Mexico, where she died in her sleep after saying good-bye to her father. 

Earlier access to healthcare and effective depression and AUD treatment could have saved Rosa’s life. While it was too late for her, as hospitalists we care for many others with substance-related complications and may miss opportunities to discuss and offer evidence-based addiction treatment. For example, we initiate the most up-to-date management for a patient’s gastrointestinal bleed but may leave the alcohol discussion for someone else. It is similar for other SUD: we treat cellulitis, epidural abscesses, bacteremia, chronic obstructive pulmonary disease, heart failure exacerbations, and other complications of SUD without addressing the root cause of the hospitalization—other than to prescribe abstinence from substance use or, at our worst, scold individuals for continuing to use.

But what can we offer? Most healthcare professionals still do not receive addiction education during training. Without tools, we enact temporizing measures, until patients return to the hospital or die.

In addition to increasing alcohol-related morbidity, there have also been increases in drug-related overdoses, fueled by COVID-19, synthetic opioids like fentanyl, and stimulants.¹⁰ In the 12-month period ending April 2021, more than 100,000 individuals died of drug-related overdoses, the highest number of deaths ever recorded in a year.¹¹ Despite this, most healthcare systems remain unequipped to provide addiction services during hospitalization due to inadequate training, stigma, and lack of systems-based care.

Hospitalists and healthcare systems cannot be bystanders amid our worsening addiction crisis. We must empower clinicians with addiction education and ensure health systems offer evidence-based SUD services.

Educational efforts can close the knowledge gaps for both medical students and hospitalists. Medical schools should include foundational curricular content in screening, assessing, diagnosing, and treating SUD in alignment with standards set by the Liaison Committee on Medical Education, which accredits US medical schools. Residency programs can offer educational conferences, cased-based discussions, and addiction medicine rotations. Hospitalists can participate in educational didactics and review evidence-based addiction guidelines.^12,13 While the focus here is on hospitalists, clinicians across practice settings and specialties will encounter patients with SUD, and all need to be well-versed in the diagnosis and treatment of addiction given the all-hands-on deck approach necessary amidst our worsening addiction crisis.

With one in nine hospitalizations involving individuals with SUD, and this number quickly rising, and with an annual cost to US hospitals of $13.2 billion, healthcare system leaders must invest in addiction care.^14,15 Hospital-based addiction services could pay for themselves and save healthcare systems money while improving the patient and clinician experience.¹⁶One way to implement hospital-based addiction care is through an addiction consult team (ACT).¹⁷ While ACT compositions vary, most are interprofessional, offer evidence-based addiction treatment, and connect patients to community care.¹⁸ Our hospital’s ACT has nurses, patient navigators, and physicians who assess, diagnose, and treat SUD, and arrange follow-up addiction care.¹⁹ In addition to caring for individual patients, our ACT has led systems change. For example, we created order sets to guide clinicians, added medications to our hospital formulary to ensure access to evidence-based addiction treatment, and partnered with community stakeholders to streamline care transitions and access to psychosocial and medication treatment. Our team also worked with hospital leadership, nursing, and a syringe service program to integrate hospital harm reduction education and supply provision. Additionally, we are building capacity among staff, trainees, and clinicians through education and systems changes.

In hospitals without an ACT, leadership can finance SUD champions and integrate them into policy-level decision-making to implement best practices in addiction care and lead hospital-wide educational efforts. This will transform hospital culture and improve care as all clinicians develop essential addiction skills.

Addiction champions and ACTs could also advocate for equitable practices for patients with SUD to reduce the stigma that both prevents patients from seeking care and results in self-discharges.²⁰ For example, with interprofessional support, we revised our in-hospital substance use policy. It previously entailed hospital security responding to substance use concerns, which unintentionally harmed patients and perpetuated stigma. Our revised policy ensures we offer medications for cravings and withdrawal, adequate pain management, and other services that address patients’ reasons for in-hospital substance use.

With the increasing prevalence of SUD among hospitalized patients, escalating substance-related deaths, rising healthcare costs, and the impact of addiction on health and well-being, addiction care, including ACTs and champions, must be adequately funded. However, sustainable financing remains a challenge.¹⁸

Caring for Rosa and others with SUD sparked my desire to learn about addiction, obtain addiction medicine board certification as a practicing hospitalist, and create an ACT that offers evidence-based addiction treatment. While much remains to be done, by collaborating with addiction champions and engaging hospital leadership, we have transformed our hospital’s approach to substance use care.

With the knowledge and resources I now have as an addiction medicine physician, I reimagine the possibilities for patients like Rosa.

Rosa died when living was possible.

*Name has been changed for patient privacy.

Rosa* was one of my first patients as an intern rotating at the county hospital. Her marriage had disintegrated years earlier. To cope with depression, she hid a daily ritual of orange juice and vodka from her children. She worked as a cashier, until nausea and fatigue overwhelmed her.

The first time I met her she sat on the gurney: petite, tanned, and pregnant. Then I saw her yellow eyes and revised: temporal wasting, jaundiced, and swollen with ascites. Rosa didn’t know that alcohol could cause liver disease. Without insurance or access to primary care, her untreated alcohol use disorder (AUD) and depression had snowballed for years. 

Midway through my intern year, I’d taken care of many people with AUD. However, I’d barely learned anything about it as a medical student, though we’d spent weeks studying esoteric diseases, that now––9 years after medical school––I still have not encountered. 

Among the 28.3 million individuals in the United States with AUD, only 1% receive medication treatment.¹ In the United States, unhealthy alcohol use accounts for more than 95,000 deaths each year.² This number likely under-captures alcohol-related mortality and is higher now given recent reports of increasing alcohol-related deaths and prevalence of unhealthy alcohol use, especially among women, younger age groups, and marginalized populations.^3-5 

Rosa had alcohol-related hepatitis, which can cause severe inflammation and liver failure and quickly lead to death. As her liver failure progressed, I asked the gastroenterologists, “What other treatments can we offer? Is she a liver transplant candidate?” “Nothing” and “No” they answered.

Later, I emailed the hepatologist and transplant surgeon begging them to reevaluate her transplantation candidacy, but they told me there was no exception to the institution’s 6-month sobriety rule.

Maintaining a 6-month sobriety period is not an evidence-based criterion for transplantation. However, 50% of transplant centers do not perform transplantation prior to 6 months of alcohol abstinence for alcohol-related hepatitis due to concern for return to drinking after transplant.⁶ This practice may promote bias in patient selection for transplantation. A recent study found that individuals with alcohol-related liver disease transplanted before 6 months of abstinence had similar rates of survival and return to drinking compared to those who abstained from alcohol for 6 months and participated in AUD treatment before transplantation.⁷

There are other liver transplant practices that result in inequities for individuals with substance use disorders (SUD). Some liver transplant centers consider being on a medication for opioid use disorder a contraindication for transplantation—even if the individual is in recovery and abstaining from substances.⁸ Others mandate that individuals with alcohol-related liver disease attend Alcoholics Anonymous (AA) meetings prior to transplant. While mutual help groups, including AA, may benefit some individuals, different approaches work for different people.⁹ Other psychosocial interventions (eg, cognitive-behavioral therapy, contingency management, and residential treatment) and medications also help individuals reduce or stop drinking. Some meet their goals without any treatment. Addiction care works best when it respects autonomy and meets individuals where they are by allowing them to decide among options.

While organ allocations are a crystalized example of inequities in addiction care, they are also ethically complex. Many individuals—with and without SUD—die on waiting lists and must meet stringent transplantation criteria. However, we can at least remove the unnecessary biases that compound inequities in care people with SUD already face.

As Rosa’s liver succumbed, her kidneys failed too, and she required dialysis. She sensed what was coming. “I want everything…for now. I need to take care of my children.” I, too, wanted Rosa to live and see her youngest start kindergarten.

A few days before her discharge, I walked to the pharmacy and bought a purple journal. In a rare moment, I found Rosa alone in her room, without her ex-husband, sister, and mother, who rarely left her bedside. Together, we called AA and explored whether she could start participating in phone meetings from the hospital. I explained that one way to document a commitment to sobriety, as the transplant center’s rules dictated, was to attend and document AA meetings in this notebook. “In 5 months, you will be a liver transplant candidate,” I remember saying, wishing it to fruition.

I became Rosa’s primary care physician and saw her in clinic. Over the next few weeks, her skin took on an ashen tone. Sleep escaped her and her thoughts and speech blurred. Her walk slowed and she needed a wheelchair. The quiet fierceness that had defined her dissipated as encephalopathy took over. But until our last visit, she brought her purple journal, tracking the AA meetings she’d attended. Dialysis became intolerable, but not before Rosa made care arrangements for her girls. When that happened, she stopped dialysis and went to Mexico, where she died in her sleep after saying good-bye to her father. 

Earlier access to healthcare and effective depression and AUD treatment could have saved Rosa’s life. While it was too late for her, as hospitalists we care for many others with substance-related complications and may miss opportunities to discuss and offer evidence-based addiction treatment. For example, we initiate the most up-to-date management for a patient’s gastrointestinal bleed but may leave the alcohol discussion for someone else. It is similar for other SUD: we treat cellulitis, epidural abscesses, bacteremia, chronic obstructive pulmonary disease, heart failure exacerbations, and other complications of SUD without addressing the root cause of the hospitalization—other than to prescribe abstinence from substance use or, at our worst, scold individuals for continuing to use.

But what can we offer? Most healthcare professionals still do not receive addiction education during training. Without tools, we enact temporizing measures, until patients return to the hospital or die.

In addition to increasing alcohol-related morbidity, there have also been increases in drug-related overdoses, fueled by COVID-19, synthetic opioids like fentanyl, and stimulants.¹⁰ In the 12-month period ending April 2021, more than 100,000 individuals died of drug-related overdoses, the highest number of deaths ever recorded in a year.¹¹ Despite this, most healthcare systems remain unequipped to provide addiction services during hospitalization due to inadequate training, stigma, and lack of systems-based care.

Hospitalists and healthcare systems cannot be bystanders amid our worsening addiction crisis. We must empower clinicians with addiction education and ensure health systems offer evidence-based SUD services.

Educational efforts can close the knowledge gaps for both medical students and hospitalists. Medical schools should include foundational curricular content in screening, assessing, diagnosing, and treating SUD in alignment with standards set by the Liaison Committee on Medical Education, which accredits US medical schools. Residency programs can offer educational conferences, cased-based discussions, and addiction medicine rotations. Hospitalists can participate in educational didactics and review evidence-based addiction guidelines.^12,13 While the focus here is on hospitalists, clinicians across practice settings and specialties will encounter patients with SUD, and all need to be well-versed in the diagnosis and treatment of addiction given the all-hands-on deck approach necessary amidst our worsening addiction crisis.

With one in nine hospitalizations involving individuals with SUD, and this number quickly rising, and with an annual cost to US hospitals of $13.2 billion, healthcare system leaders must invest in addiction care.^14,15 Hospital-based addiction services could pay for themselves and save healthcare systems money while improving the patient and clinician experience.¹⁶One way to implement hospital-based addiction care is through an addiction consult team (ACT).¹⁷ While ACT compositions vary, most are interprofessional, offer evidence-based addiction treatment, and connect patients to community care.¹⁸ Our hospital’s ACT has nurses, patient navigators, and physicians who assess, diagnose, and treat SUD, and arrange follow-up addiction care.¹⁹ In addition to caring for individual patients, our ACT has led systems change. For example, we created order sets to guide clinicians, added medications to our hospital formulary to ensure access to evidence-based addiction treatment, and partnered with community stakeholders to streamline care transitions and access to psychosocial and medication treatment. Our team also worked with hospital leadership, nursing, and a syringe service program to integrate hospital harm reduction education and supply provision. Additionally, we are building capacity among staff, trainees, and clinicians through education and systems changes.

In hospitals without an ACT, leadership can finance SUD champions and integrate them into policy-level decision-making to implement best practices in addiction care and lead hospital-wide educational efforts. This will transform hospital culture and improve care as all clinicians develop essential addiction skills.

Addiction champions and ACTs could also advocate for equitable practices for patients with SUD to reduce the stigma that both prevents patients from seeking care and results in self-discharges.²⁰ For example, with interprofessional support, we revised our in-hospital substance use policy. It previously entailed hospital security responding to substance use concerns, which unintentionally harmed patients and perpetuated stigma. Our revised policy ensures we offer medications for cravings and withdrawal, adequate pain management, and other services that address patients’ reasons for in-hospital substance use.

With the increasing prevalence of SUD among hospitalized patients, escalating substance-related deaths, rising healthcare costs, and the impact of addiction on health and well-being, addiction care, including ACTs and champions, must be adequately funded. However, sustainable financing remains a challenge.¹⁸

Caring for Rosa and others with SUD sparked my desire to learn about addiction, obtain addiction medicine board certification as a practicing hospitalist, and create an ACT that offers evidence-based addiction treatment. While much remains to be done, by collaborating with addiction champions and engaging hospital leadership, we have transformed our hospital’s approach to substance use care.

With the knowledge and resources I now have as an addiction medicine physician, I reimagine the possibilities for patients like Rosa.

Rosa died when living was possible.

*Name has been changed for patient privacy.

Rosa* was one of my first patients as an intern rotating at the county hospital. Her marriage had disintegrated years earlier. To cope with depression, she hid a daily ritual of orange juice and vodka from her children. She worked as a cashier, until nausea and fatigue overwhelmed her.

The first time I met her she sat on the gurney: petite, tanned, and pregnant. Then I saw her yellow eyes and revised: temporal wasting, jaundiced, and swollen with ascites. Rosa didn’t know that alcohol could cause liver disease. Without insurance or access to primary care, her untreated alcohol use disorder (AUD) and depression had snowballed for years. 

Midway through my intern year, I’d taken care of many people with AUD. However, I’d barely learned anything about it as a medical student, though we’d spent weeks studying esoteric diseases, that now––9 years after medical school––I still have not encountered. 

Among the 28.3 million individuals in the United States with AUD, only 1% receive medication treatment.¹ In the United States, unhealthy alcohol use accounts for more than 95,000 deaths each year.² This number likely under-captures alcohol-related mortality and is higher now given recent reports of increasing alcohol-related deaths and prevalence of unhealthy alcohol use, especially among women, younger age groups, and marginalized populations.^3-5 

Rosa had alcohol-related hepatitis, which can cause severe inflammation and liver failure and quickly lead to death. As her liver failure progressed, I asked the gastroenterologists, “What other treatments can we offer? Is she a liver transplant candidate?” “Nothing” and “No” they answered.

Later, I emailed the hepatologist and transplant surgeon begging them to reevaluate her transplantation candidacy, but they told me there was no exception to the institution’s 6-month sobriety rule.

Maintaining a 6-month sobriety period is not an evidence-based criterion for transplantation. However, 50% of transplant centers do not perform transplantation prior to 6 months of alcohol abstinence for alcohol-related hepatitis due to concern for return to drinking after transplant.⁶ This practice may promote bias in patient selection for transplantation. A recent study found that individuals with alcohol-related liver disease transplanted before 6 months of abstinence had similar rates of survival and return to drinking compared to those who abstained from alcohol for 6 months and participated in AUD treatment before transplantation.⁷

There are other liver transplant practices that result in inequities for individuals with substance use disorders (SUD). Some liver transplant centers consider being on a medication for opioid use disorder a contraindication for transplantation—even if the individual is in recovery and abstaining from substances.⁸ Others mandate that individuals with alcohol-related liver disease attend Alcoholics Anonymous (AA) meetings prior to transplant. While mutual help groups, including AA, may benefit some individuals, different approaches work for different people.⁹ Other psychosocial interventions (eg, cognitive-behavioral therapy, contingency management, and residential treatment) and medications also help individuals reduce or stop drinking. Some meet their goals without any treatment. Addiction care works best when it respects autonomy and meets individuals where they are by allowing them to decide among options.

While organ allocations are a crystalized example of inequities in addiction care, they are also ethically complex. Many individuals—with and without SUD—die on waiting lists and must meet stringent transplantation criteria. However, we can at least remove the unnecessary biases that compound inequities in care people with SUD already face.

As Rosa’s liver succumbed, her kidneys failed too, and she required dialysis. She sensed what was coming. “I want everything…for now. I need to take care of my children.” I, too, wanted Rosa to live and see her youngest start kindergarten.

A few days before her discharge, I walked to the pharmacy and bought a purple journal. In a rare moment, I found Rosa alone in her room, without her ex-husband, sister, and mother, who rarely left her bedside. Together, we called AA and explored whether she could start participating in phone meetings from the hospital. I explained that one way to document a commitment to sobriety, as the transplant center’s rules dictated, was to attend and document AA meetings in this notebook. “In 5 months, you will be a liver transplant candidate,” I remember saying, wishing it to fruition.

I became Rosa’s primary care physician and saw her in clinic. Over the next few weeks, her skin took on an ashen tone. Sleep escaped her and her thoughts and speech blurred. Her walk slowed and she needed a wheelchair. The quiet fierceness that had defined her dissipated as encephalopathy took over. But until our last visit, she brought her purple journal, tracking the AA meetings she’d attended. Dialysis became intolerable, but not before Rosa made care arrangements for her girls. When that happened, she stopped dialysis and went to Mexico, where she died in her sleep after saying good-bye to her father. 

Earlier access to healthcare and effective depression and AUD treatment could have saved Rosa’s life. While it was too late for her, as hospitalists we care for many others with substance-related complications and may miss opportunities to discuss and offer evidence-based addiction treatment. For example, we initiate the most up-to-date management for a patient’s gastrointestinal bleed but may leave the alcohol discussion for someone else. It is similar for other SUD: we treat cellulitis, epidural abscesses, bacteremia, chronic obstructive pulmonary disease, heart failure exacerbations, and other complications of SUD without addressing the root cause of the hospitalization—other than to prescribe abstinence from substance use or, at our worst, scold individuals for continuing to use.

But what can we offer? Most healthcare professionals still do not receive addiction education during training. Without tools, we enact temporizing measures, until patients return to the hospital or die.

In addition to increasing alcohol-related morbidity, there have also been increases in drug-related overdoses, fueled by COVID-19, synthetic opioids like fentanyl, and stimulants.¹⁰ In the 12-month period ending April 2021, more than 100,000 individuals died of drug-related overdoses, the highest number of deaths ever recorded in a year.¹¹ Despite this, most healthcare systems remain unequipped to provide addiction services during hospitalization due to inadequate training, stigma, and lack of systems-based care.

Hospitalists and healthcare systems cannot be bystanders amid our worsening addiction crisis. We must empower clinicians with addiction education and ensure health systems offer evidence-based SUD services.

Educational efforts can close the knowledge gaps for both medical students and hospitalists. Medical schools should include foundational curricular content in screening, assessing, diagnosing, and treating SUD in alignment with standards set by the Liaison Committee on Medical Education, which accredits US medical schools. Residency programs can offer educational conferences, cased-based discussions, and addiction medicine rotations. Hospitalists can participate in educational didactics and review evidence-based addiction guidelines.^12,13 While the focus here is on hospitalists, clinicians across practice settings and specialties will encounter patients with SUD, and all need to be well-versed in the diagnosis and treatment of addiction given the all-hands-on deck approach necessary amidst our worsening addiction crisis.

With one in nine hospitalizations involving individuals with SUD, and this number quickly rising, and with an annual cost to US hospitals of $13.2 billion, healthcare system leaders must invest in addiction care.^14,15 Hospital-based addiction services could pay for themselves and save healthcare systems money while improving the patient and clinician experience.¹⁶One way to implement hospital-based addiction care is through an addiction consult team (ACT).¹⁷ While ACT compositions vary, most are interprofessional, offer evidence-based addiction treatment, and connect patients to community care.¹⁸ Our hospital’s ACT has nurses, patient navigators, and physicians who assess, diagnose, and treat SUD, and arrange follow-up addiction care.¹⁹ In addition to caring for individual patients, our ACT has led systems change. For example, we created order sets to guide clinicians, added medications to our hospital formulary to ensure access to evidence-based addiction treatment, and partnered with community stakeholders to streamline care transitions and access to psychosocial and medication treatment. Our team also worked with hospital leadership, nursing, and a syringe service program to integrate hospital harm reduction education and supply provision. Additionally, we are building capacity among staff, trainees, and clinicians through education and systems changes.

In hospitals without an ACT, leadership can finance SUD champions and integrate them into policy-level decision-making to implement best practices in addiction care and lead hospital-wide educational efforts. This will transform hospital culture and improve care as all clinicians develop essential addiction skills.

Addiction champions and ACTs could also advocate for equitable practices for patients with SUD to reduce the stigma that both prevents patients from seeking care and results in self-discharges.²⁰ For example, with interprofessional support, we revised our in-hospital substance use policy. It previously entailed hospital security responding to substance use concerns, which unintentionally harmed patients and perpetuated stigma. Our revised policy ensures we offer medications for cravings and withdrawal, adequate pain management, and other services that address patients’ reasons for in-hospital substance use.

With the increasing prevalence of SUD among hospitalized patients, escalating substance-related deaths, rising healthcare costs, and the impact of addiction on health and well-being, addiction care, including ACTs and champions, must be adequately funded. However, sustainable financing remains a challenge.¹⁸

Caring for Rosa and others with SUD sparked my desire to learn about addiction, obtain addiction medicine board certification as a practicing hospitalist, and create an ACT that offers evidence-based addiction treatment. While much remains to be done, by collaborating with addiction champions and engaging hospital leadership, we have transformed our hospital’s approach to substance use care.

With the knowledge and resources I now have as an addiction medicine physician, I reimagine the possibilities for patients like Rosa.

Rosa died when living was possible.

*Name has been changed for patient privacy.