Practice Management

Study 1 Overview (Park et al)

Objective: To compare rates of adverse events and 30-day readmission among patients with dementia who undergo percutaneous coronary intervention (PCI) with those without dementia.

Design: This cohort study used a national database of hospital readmissions developed by the Agency for Healthcare Research and Quality.

Setting and participants: Data from State Inpatient Databases were used to derive this national readmissions database representing 80% of hospitals from 28 states that contribute data. The study included all individuals aged 18 years and older who were identified to have had a PCI procedure in the years 2017 and 2018. International Classification of Diseases, Tenth Revision (ICD-10) codes were used to identify PCI procedures, including drug-eluting stent placement, bare-metal stent placement, and balloon angioplasty, performed in patients who presented with myocardial infarction and unstable angina and those with stable ischemic heart disease. Patients were stratified into those with or without dementia, also defined using ICD-10 codes. A total of 755,406 index hospitalizations were included; 2.3% of the patients had dementia.

Main outcome measures: The primary study outcome was 30-day all-cause readmission, with the cause classified as cardiovascular or noncardiovascular. Secondary outcome measures examined were delirium, in-hospital mortality, cardiac arrest, blood transfusion, acute kidney injury, fall in hospital, length of hospital stay, and other adverse outcomes. Location at discharge was also examined. Other covariates included in the analysis were age, sex, comorbidities, hospital characteristics, primary payer, and median income. For analysis, a propensity score matching algorithm was applied to match patients with and without dementia. Kaplan-Meier curves were used to examine 30-day readmission rates, and a Cox proportional hazards model was used to calculate hazard ratios (HR) for those with and without dementia. For secondary outcomes, logistic regression models were used to calculate odds ratios (OR) of outcomes between those with and without dementia.

Main results: The average age of those with dementia was 78.8 years vs 64.9 years in those without dementia. Women made up 42.8% of those with dementia and 31.3% of those without dementia. Those with dementia also had higher rates of comorbidities, such as heart failure, renal failure, and depression. After propensity score matching, 17,309 and 17,187 patients with and without dementia, respectively, were included. Covariates were balanced between the 2 groups after matching. For the primary outcome, patients with dementia were more likely to be readmitted at 30 days (HR, 1.11; 95% CI, 1.05-1.18; P < .01) when compared to those without dementia. For other adverse outcomes, delirium was significantly more likely to occur for those with dementia (OR, 4.37; 95% CI, 3.69-5.16; P < .01). Patients with dementia were also more likely to die in hospital (OR, 1.15; 95% CI, 1.01-1.30; P = .03), have cardiac arrest (OR, 1.19; 95% CI, 1.01-1.39; P = .04), receive a blood transfusion (OR, 1.17; 95% CI, 1.00-1.36; P = .05), experience acute kidney injury (OR, 1.30; 95% CI, 1.21-1.39; P < .01), and fall in hospital (OR, 2.51; 95% CI, 2.06-3.07; P < .01). Hospital length of stay was higher for those with dementia, with a mean difference of 1.43 days. For discharge location, patients with dementia were more likely to be sent to a skilled nursing facility (30.1% vs 12.2%) and less likely to be discharged home.

Conclusion: Patients with dementia are more likely to experience adverse events, including delirium, mortality, kidney injury, and falls after PCI, and are more likely to be readmitted to the hospital in 30 days compared to those without dementia.

Study 2 Overview (Gilmore-Bykovskyi et al)

Objective: To examine the association between race and 30-day readmissions in Black and non-Hispanic White Medicare beneficiaries with dementia.

Design: This was a retrospective cohort study that used 100% Medicare fee-for service claims data from all hospitalizations between January 1, 2014, and November 30, 2014, for all enrollees with a dementia diagnosis. The claims data were linked to the patient, hospital stay, and hospital factors. Patients with dementia were identified using a validated algorithm that requires an inpatient, skilled nursing facility, home health, or Part B institutional or noninstitutional claim with a qualifying diagnostic code during a 3-year period. Persons enrolled in a health maintenance organization plan were excluded.

Main outcome measures: The primary outcome examined in this study was 30-day all-cause readmission. Self-reported race and ethnic identity was a baseline covariate. Persons who self-reported Black or non-Hispanic White race were included in the study; other categories of race and ethnicity were excluded because of prior evidence suggesting low accuracy of these categories in Medicare claims data. Other covariates included neighborhood disadvantage, measured using the Area Deprivation Index (ADI), and rurality; hospital-level and hospital stay–level characteristics such as for-profit status and number of annual discharges; and individual demographic characteristics and comorbidities. The ADI is constructed using variables of poverty, education, housing, and employment and is represented as a percentile ranking of level of disadvantage. Unadjusted and adjusted analyses of 30-day hospital readmission were conducted. Models using various levels of adjustment were constructed to examine the contributions of the identified covariates to the estimated association between 30-day readmission and race.

Main results: A total of 1,523,142 index hospital stays among 945,481 beneficiaries were included; 215,815 episodes were among Black beneficiaries and 1,307,327 episodes were among non-Hispanic White beneficiaries. Mean age was 81.5 years, and approximately 61% of beneficiaries were female. Black beneficiaries were younger but had higher rates of dual Medicare/Medicaid eligibility and disability; they were also more likely to reside in disadvantaged neighborhoods. Black beneficiaries had a 30-day readmission rate of 24.1% compared with 18.5% in non-Hispanic White beneficiaries (unadjusted OR, 1.37; 95% CI, 1.35-1.39). The differences in outcomes persisted after adjusting for geographic factors, social factors, hospital characteristics, hospital stay factors, demographics, and comorbidities, suggesting that unmeasured underlying racial disparities not included in this model accounted for the differences. The effects of certain variables, such as neighborhood, differed by race; for example, the protective effect of living in a less disadvantaged neighborhood was observed among White beneficiaries but not Black beneficiaries.

Conclusion: Racial and geographic disparities in 30-day readmission rates were observed among Medicare beneficiaries with dementia. Protective effects associated with neighborhood advantage may confer different levels of benefit for people of different race.

Commentary

Adults living with dementia are at higher risk of adverse outcomes across settings. In the first study, by Park et al, among adults who underwent a cardiac procedure (PCI), those with dementia were more likely to experience adverse events compared to those without dementia. These outcomes include increased rates of 30-day readmissions, delirium, cardiac arrest, and falls. These findings are consistent with other studies that found a similar association among patients who underwent other cardiac procedures, such as transcatheter aortic valve replacement.¹ Because dementia is a strong predisposing factor for delirium, it is not surprising that delirium is observed across patients who underwent different procedures or hospitalization episodes.² Because of the potential hazards for inpatients with dementia, hospitals have developed risk-reduction programs, such as those that promote recognition of dementia, and management strategies that reduce the risk of delirium.³ Delirium prevention may also impact other adverse outcomes, such as falls, discharge to institutional care, and readmissions.

Racial disparities in care outcomes have been documented across settings, including hospital⁴ and hospice care settings.⁵ In study 2, by Gilmore-Bykovskyi et al, the findings of higher rates of hospital readmission among Black patients when compared to non-Hispanic White patients were not surprising. The central finding of this study is that even when accounting for various levels of factors, including hospital-level, hospital stay–level, individual (demographics, comorbidities), and neighborhood characteristics (disadvantage), the observed disparity diminished but persisted, suggesting that while these various levels of factors contributed to the observed disparity, other unmeasured factors also contributed. Another key finding is that the effect of the various factors examined in this study may affect different subgroups in different ways, suggesting underlying factors, and thus potential solutions to reduce disparities in care outcomes, could differ among subgroups.

Applications for Clinical Practice and System Implementation

These 2 studies add to the literature on factors that can affect 30-day hospital readmission rates in patients with dementia. These data could allow for more robust discussions of what to anticipate when adults with dementia undergo specific procedures, and also further build the case that improvements in care, such as delirium prevention programs, could offer benefits. The observation about racial and ethnic disparities in care outcomes among patients with dementia highlights the continued need to better understand the drivers of these disparities so that hospital systems and policy makers can consider and test possible solutions. Future studies should further disentangle the relationships among the various levels of factors and observed disparities in outcomes, especially for this vulnerable population of adults living with dementia.

Practice Points

• Clinicians should be aware of the additional risks for poor outcomes that dementia confers.
• Awareness of this increased risk will inform discussions of risks and benefits for older adults considered for procedures.

–William W. Hung, MD, MPH

Study 1 Overview (Park et al)

Objective: To compare rates of adverse events and 30-day readmission among patients with dementia who undergo percutaneous coronary intervention (PCI) with those without dementia.

Design: This cohort study used a national database of hospital readmissions developed by the Agency for Healthcare Research and Quality.

Setting and participants: Data from State Inpatient Databases were used to derive this national readmissions database representing 80% of hospitals from 28 states that contribute data. The study included all individuals aged 18 years and older who were identified to have had a PCI procedure in the years 2017 and 2018. International Classification of Diseases, Tenth Revision (ICD-10) codes were used to identify PCI procedures, including drug-eluting stent placement, bare-metal stent placement, and balloon angioplasty, performed in patients who presented with myocardial infarction and unstable angina and those with stable ischemic heart disease. Patients were stratified into those with or without dementia, also defined using ICD-10 codes. A total of 755,406 index hospitalizations were included; 2.3% of the patients had dementia.

Main outcome measures: The primary study outcome was 30-day all-cause readmission, with the cause classified as cardiovascular or noncardiovascular. Secondary outcome measures examined were delirium, in-hospital mortality, cardiac arrest, blood transfusion, acute kidney injury, fall in hospital, length of hospital stay, and other adverse outcomes. Location at discharge was also examined. Other covariates included in the analysis were age, sex, comorbidities, hospital characteristics, primary payer, and median income. For analysis, a propensity score matching algorithm was applied to match patients with and without dementia. Kaplan-Meier curves were used to examine 30-day readmission rates, and a Cox proportional hazards model was used to calculate hazard ratios (HR) for those with and without dementia. For secondary outcomes, logistic regression models were used to calculate odds ratios (OR) of outcomes between those with and without dementia.

Main results: The average age of those with dementia was 78.8 years vs 64.9 years in those without dementia. Women made up 42.8% of those with dementia and 31.3% of those without dementia. Those with dementia also had higher rates of comorbidities, such as heart failure, renal failure, and depression. After propensity score matching, 17,309 and 17,187 patients with and without dementia, respectively, were included. Covariates were balanced between the 2 groups after matching. For the primary outcome, patients with dementia were more likely to be readmitted at 30 days (HR, 1.11; 95% CI, 1.05-1.18; P < .01) when compared to those without dementia. For other adverse outcomes, delirium was significantly more likely to occur for those with dementia (OR, 4.37; 95% CI, 3.69-5.16; P < .01). Patients with dementia were also more likely to die in hospital (OR, 1.15; 95% CI, 1.01-1.30; P = .03), have cardiac arrest (OR, 1.19; 95% CI, 1.01-1.39; P = .04), receive a blood transfusion (OR, 1.17; 95% CI, 1.00-1.36; P = .05), experience acute kidney injury (OR, 1.30; 95% CI, 1.21-1.39; P < .01), and fall in hospital (OR, 2.51; 95% CI, 2.06-3.07; P < .01). Hospital length of stay was higher for those with dementia, with a mean difference of 1.43 days. For discharge location, patients with dementia were more likely to be sent to a skilled nursing facility (30.1% vs 12.2%) and less likely to be discharged home.

Conclusion: Patients with dementia are more likely to experience adverse events, including delirium, mortality, kidney injury, and falls after PCI, and are more likely to be readmitted to the hospital in 30 days compared to those without dementia.

Study 2 Overview (Gilmore-Bykovskyi et al)

Objective: To examine the association between race and 30-day readmissions in Black and non-Hispanic White Medicare beneficiaries with dementia.

Design: This was a retrospective cohort study that used 100% Medicare fee-for service claims data from all hospitalizations between January 1, 2014, and November 30, 2014, for all enrollees with a dementia diagnosis. The claims data were linked to the patient, hospital stay, and hospital factors. Patients with dementia were identified using a validated algorithm that requires an inpatient, skilled nursing facility, home health, or Part B institutional or noninstitutional claim with a qualifying diagnostic code during a 3-year period. Persons enrolled in a health maintenance organization plan were excluded.

Main outcome measures: The primary outcome examined in this study was 30-day all-cause readmission. Self-reported race and ethnic identity was a baseline covariate. Persons who self-reported Black or non-Hispanic White race were included in the study; other categories of race and ethnicity were excluded because of prior evidence suggesting low accuracy of these categories in Medicare claims data. Other covariates included neighborhood disadvantage, measured using the Area Deprivation Index (ADI), and rurality; hospital-level and hospital stay–level characteristics such as for-profit status and number of annual discharges; and individual demographic characteristics and comorbidities. The ADI is constructed using variables of poverty, education, housing, and employment and is represented as a percentile ranking of level of disadvantage. Unadjusted and adjusted analyses of 30-day hospital readmission were conducted. Models using various levels of adjustment were constructed to examine the contributions of the identified covariates to the estimated association between 30-day readmission and race.

Main results: A total of 1,523,142 index hospital stays among 945,481 beneficiaries were included; 215,815 episodes were among Black beneficiaries and 1,307,327 episodes were among non-Hispanic White beneficiaries. Mean age was 81.5 years, and approximately 61% of beneficiaries were female. Black beneficiaries were younger but had higher rates of dual Medicare/Medicaid eligibility and disability; they were also more likely to reside in disadvantaged neighborhoods. Black beneficiaries had a 30-day readmission rate of 24.1% compared with 18.5% in non-Hispanic White beneficiaries (unadjusted OR, 1.37; 95% CI, 1.35-1.39). The differences in outcomes persisted after adjusting for geographic factors, social factors, hospital characteristics, hospital stay factors, demographics, and comorbidities, suggesting that unmeasured underlying racial disparities not included in this model accounted for the differences. The effects of certain variables, such as neighborhood, differed by race; for example, the protective effect of living in a less disadvantaged neighborhood was observed among White beneficiaries but not Black beneficiaries.

Conclusion: Racial and geographic disparities in 30-day readmission rates were observed among Medicare beneficiaries with dementia. Protective effects associated with neighborhood advantage may confer different levels of benefit for people of different race.

Commentary

Adults living with dementia are at higher risk of adverse outcomes across settings. In the first study, by Park et al, among adults who underwent a cardiac procedure (PCI), those with dementia were more likely to experience adverse events compared to those without dementia. These outcomes include increased rates of 30-day readmissions, delirium, cardiac arrest, and falls. These findings are consistent with other studies that found a similar association among patients who underwent other cardiac procedures, such as transcatheter aortic valve replacement.¹ Because dementia is a strong predisposing factor for delirium, it is not surprising that delirium is observed across patients who underwent different procedures or hospitalization episodes.² Because of the potential hazards for inpatients with dementia, hospitals have developed risk-reduction programs, such as those that promote recognition of dementia, and management strategies that reduce the risk of delirium.³ Delirium prevention may also impact other adverse outcomes, such as falls, discharge to institutional care, and readmissions.

Racial disparities in care outcomes have been documented across settings, including hospital⁴ and hospice care settings.⁵ In study 2, by Gilmore-Bykovskyi et al, the findings of higher rates of hospital readmission among Black patients when compared to non-Hispanic White patients were not surprising. The central finding of this study is that even when accounting for various levels of factors, including hospital-level, hospital stay–level, individual (demographics, comorbidities), and neighborhood characteristics (disadvantage), the observed disparity diminished but persisted, suggesting that while these various levels of factors contributed to the observed disparity, other unmeasured factors also contributed. Another key finding is that the effect of the various factors examined in this study may affect different subgroups in different ways, suggesting underlying factors, and thus potential solutions to reduce disparities in care outcomes, could differ among subgroups.

Applications for Clinical Practice and System Implementation

These 2 studies add to the literature on factors that can affect 30-day hospital readmission rates in patients with dementia. These data could allow for more robust discussions of what to anticipate when adults with dementia undergo specific procedures, and also further build the case that improvements in care, such as delirium prevention programs, could offer benefits. The observation about racial and ethnic disparities in care outcomes among patients with dementia highlights the continued need to better understand the drivers of these disparities so that hospital systems and policy makers can consider and test possible solutions. Future studies should further disentangle the relationships among the various levels of factors and observed disparities in outcomes, especially for this vulnerable population of adults living with dementia.

Practice Points

• Clinicians should be aware of the additional risks for poor outcomes that dementia confers.
• Awareness of this increased risk will inform discussions of risks and benefits for older adults considered for procedures.

–William W. Hung, MD, MPH

Study 1 Overview (Park et al)

Objective: To compare rates of adverse events and 30-day readmission among patients with dementia who undergo percutaneous coronary intervention (PCI) with those without dementia.

Design: This cohort study used a national database of hospital readmissions developed by the Agency for Healthcare Research and Quality.

Setting and participants: Data from State Inpatient Databases were used to derive this national readmissions database representing 80% of hospitals from 28 states that contribute data. The study included all individuals aged 18 years and older who were identified to have had a PCI procedure in the years 2017 and 2018. International Classification of Diseases, Tenth Revision (ICD-10) codes were used to identify PCI procedures, including drug-eluting stent placement, bare-metal stent placement, and balloon angioplasty, performed in patients who presented with myocardial infarction and unstable angina and those with stable ischemic heart disease. Patients were stratified into those with or without dementia, also defined using ICD-10 codes. A total of 755,406 index hospitalizations were included; 2.3% of the patients had dementia.

Main outcome measures: The primary study outcome was 30-day all-cause readmission, with the cause classified as cardiovascular or noncardiovascular. Secondary outcome measures examined were delirium, in-hospital mortality, cardiac arrest, blood transfusion, acute kidney injury, fall in hospital, length of hospital stay, and other adverse outcomes. Location at discharge was also examined. Other covariates included in the analysis were age, sex, comorbidities, hospital characteristics, primary payer, and median income. For analysis, a propensity score matching algorithm was applied to match patients with and without dementia. Kaplan-Meier curves were used to examine 30-day readmission rates, and a Cox proportional hazards model was used to calculate hazard ratios (HR) for those with and without dementia. For secondary outcomes, logistic regression models were used to calculate odds ratios (OR) of outcomes between those with and without dementia.

Main results: The average age of those with dementia was 78.8 years vs 64.9 years in those without dementia. Women made up 42.8% of those with dementia and 31.3% of those without dementia. Those with dementia also had higher rates of comorbidities, such as heart failure, renal failure, and depression. After propensity score matching, 17,309 and 17,187 patients with and without dementia, respectively, were included. Covariates were balanced between the 2 groups after matching. For the primary outcome, patients with dementia were more likely to be readmitted at 30 days (HR, 1.11; 95% CI, 1.05-1.18; P < .01) when compared to those without dementia. For other adverse outcomes, delirium was significantly more likely to occur for those with dementia (OR, 4.37; 95% CI, 3.69-5.16; P < .01). Patients with dementia were also more likely to die in hospital (OR, 1.15; 95% CI, 1.01-1.30; P = .03), have cardiac arrest (OR, 1.19; 95% CI, 1.01-1.39; P = .04), receive a blood transfusion (OR, 1.17; 95% CI, 1.00-1.36; P = .05), experience acute kidney injury (OR, 1.30; 95% CI, 1.21-1.39; P < .01), and fall in hospital (OR, 2.51; 95% CI, 2.06-3.07; P < .01). Hospital length of stay was higher for those with dementia, with a mean difference of 1.43 days. For discharge location, patients with dementia were more likely to be sent to a skilled nursing facility (30.1% vs 12.2%) and less likely to be discharged home.

Conclusion: Patients with dementia are more likely to experience adverse events, including delirium, mortality, kidney injury, and falls after PCI, and are more likely to be readmitted to the hospital in 30 days compared to those without dementia.

Study 2 Overview (Gilmore-Bykovskyi et al)

Objective: To examine the association between race and 30-day readmissions in Black and non-Hispanic White Medicare beneficiaries with dementia.

Design: This was a retrospective cohort study that used 100% Medicare fee-for service claims data from all hospitalizations between January 1, 2014, and November 30, 2014, for all enrollees with a dementia diagnosis. The claims data were linked to the patient, hospital stay, and hospital factors. Patients with dementia were identified using a validated algorithm that requires an inpatient, skilled nursing facility, home health, or Part B institutional or noninstitutional claim with a qualifying diagnostic code during a 3-year period. Persons enrolled in a health maintenance organization plan were excluded.

Main outcome measures: The primary outcome examined in this study was 30-day all-cause readmission. Self-reported race and ethnic identity was a baseline covariate. Persons who self-reported Black or non-Hispanic White race were included in the study; other categories of race and ethnicity were excluded because of prior evidence suggesting low accuracy of these categories in Medicare claims data. Other covariates included neighborhood disadvantage, measured using the Area Deprivation Index (ADI), and rurality; hospital-level and hospital stay–level characteristics such as for-profit status and number of annual discharges; and individual demographic characteristics and comorbidities. The ADI is constructed using variables of poverty, education, housing, and employment and is represented as a percentile ranking of level of disadvantage. Unadjusted and adjusted analyses of 30-day hospital readmission were conducted. Models using various levels of adjustment were constructed to examine the contributions of the identified covariates to the estimated association between 30-day readmission and race.

Main results: A total of 1,523,142 index hospital stays among 945,481 beneficiaries were included; 215,815 episodes were among Black beneficiaries and 1,307,327 episodes were among non-Hispanic White beneficiaries. Mean age was 81.5 years, and approximately 61% of beneficiaries were female. Black beneficiaries were younger but had higher rates of dual Medicare/Medicaid eligibility and disability; they were also more likely to reside in disadvantaged neighborhoods. Black beneficiaries had a 30-day readmission rate of 24.1% compared with 18.5% in non-Hispanic White beneficiaries (unadjusted OR, 1.37; 95% CI, 1.35-1.39). The differences in outcomes persisted after adjusting for geographic factors, social factors, hospital characteristics, hospital stay factors, demographics, and comorbidities, suggesting that unmeasured underlying racial disparities not included in this model accounted for the differences. The effects of certain variables, such as neighborhood, differed by race; for example, the protective effect of living in a less disadvantaged neighborhood was observed among White beneficiaries but not Black beneficiaries.

Conclusion: Racial and geographic disparities in 30-day readmission rates were observed among Medicare beneficiaries with dementia. Protective effects associated with neighborhood advantage may confer different levels of benefit for people of different race.

Commentary

Adults living with dementia are at higher risk of adverse outcomes across settings. In the first study, by Park et al, among adults who underwent a cardiac procedure (PCI), those with dementia were more likely to experience adverse events compared to those without dementia. These outcomes include increased rates of 30-day readmissions, delirium, cardiac arrest, and falls. These findings are consistent with other studies that found a similar association among patients who underwent other cardiac procedures, such as transcatheter aortic valve replacement.¹ Because dementia is a strong predisposing factor for delirium, it is not surprising that delirium is observed across patients who underwent different procedures or hospitalization episodes.² Because of the potential hazards for inpatients with dementia, hospitals have developed risk-reduction programs, such as those that promote recognition of dementia, and management strategies that reduce the risk of delirium.³ Delirium prevention may also impact other adverse outcomes, such as falls, discharge to institutional care, and readmissions.

Racial disparities in care outcomes have been documented across settings, including hospital⁴ and hospice care settings.⁵ In study 2, by Gilmore-Bykovskyi et al, the findings of higher rates of hospital readmission among Black patients when compared to non-Hispanic White patients were not surprising. The central finding of this study is that even when accounting for various levels of factors, including hospital-level, hospital stay–level, individual (demographics, comorbidities), and neighborhood characteristics (disadvantage), the observed disparity diminished but persisted, suggesting that while these various levels of factors contributed to the observed disparity, other unmeasured factors also contributed. Another key finding is that the effect of the various factors examined in this study may affect different subgroups in different ways, suggesting underlying factors, and thus potential solutions to reduce disparities in care outcomes, could differ among subgroups.

Applications for Clinical Practice and System Implementation

These 2 studies add to the literature on factors that can affect 30-day hospital readmission rates in patients with dementia. These data could allow for more robust discussions of what to anticipate when adults with dementia undergo specific procedures, and also further build the case that improvements in care, such as delirium prevention programs, could offer benefits. The observation about racial and ethnic disparities in care outcomes among patients with dementia highlights the continued need to better understand the drivers of these disparities so that hospital systems and policy makers can consider and test possible solutions. Future studies should further disentangle the relationships among the various levels of factors and observed disparities in outcomes, especially for this vulnerable population of adults living with dementia.

Practice Points

• Clinicians should be aware of the additional risks for poor outcomes that dementia confers.
• Awareness of this increased risk will inform discussions of risks and benefits for older adults considered for procedures.

–William W. Hung, MD, MPH

Study 1 Overview (Trivedi et al)

Objective: This observational quality improvement study aimed to evaluate the discharge communication practices in internal medicine services at 2 urban academic teaching hospitals, specifically focusing on patient education and counseling in 6 key discharge communication domains.

Design: Observations were conducted over a 13-month period from September 2018 through October 2019, following the Standards for Quality Improvement Reporting Excellence (SQUIRE) guidelines.

Setting and participants: The study involved a total of 33 English- and Spanish-speaking patients purposefully selected from the “discharge before noon” list at 2 urban tertiary-care teaching hospitals. A total of 155 observation hours were accumulated, with an average observation time of 4.7 hours per patient on the day of discharge.

Main outcome measures: The study assessed 6 discharge communication domains: (1) the name and function of medication changes, (2) the purpose of postdischarge appointments, (3) disease self-management, (4) red flags or warning signs for complications, (5) teach-back techniques to confirm patient understanding, and (6) staff solicitation of patient questions or concerns.

Main results: The study found several gaps in discharge communication practices. Among the 29 patients with medication changes, 28% were not informed about the name and basic function of the changes, while 59% did not receive counseling on the purpose for the medication change. In terms of postdischarge appointments, 48% of patients were not told the purpose of these appointments. Moreover, 54% of patients did not receive counseling on self-management of their primary discharge diagnosis or other diagnoses, and 73% were not informed about symptom expectations or the expected course of their illness after leaving the hospital. Most patients (82%) were not counseled on red-flag signs and symptoms that should prompt immediate return to care.

Teach-back techniques, which are critical for ensuring patient understanding, were used in only 3% of cases, and 85% of patients were not asked by health care providers if there might be barriers to following the care plan. Less than half (42%) of the patients were asked if they had any questions, with most questions being logistical and often deferred to another team member or met with uncertainty. Of note, among the 33 patients, only 2 patients received extensive information that covered 5 or 6 out of 6 discharge communication domains.

The study found variable roles in who communicated what aspects of discharge education, with most domains being communicated in an ad hoc manner and no clear pattern of responsibility. However, 2 exceptions were observed: nurses were more likely to provide information about new or changed medications and follow-up appointments, and the only example of teach-back was conducted by an attending physician.

Conclusion: The study highlights a significant need for improved discharge techniques to enhance patient safety and quality of care upon leaving the hospital. Interventions should focus on increasing transparency in patient education and understanding, clarifying assumptions of roles among the interprofessional team, and implementing effective communication strategies and system redesigns that foster patient-centered discharge education. Also, the study revealed that some patients received more robust discharge education than others, indicating systemic inequality in the patient experience. Further studies are needed to explore the development and assessment of such interventions to ensure optimal patient outcomes and equal care following hospital discharge.

Study 2 Overview (Marks et al)

Objective: This study aimed to investigate the impact of a nurse-led discharge medication education program, Teaching Important Medication Effects (TIME), on patients’ new medication knowledge at discharge and 48 to 72 hours post discharge. The specific objectives were to identify patients’ priority learning needs, evaluate the influence of TIME on patients’ new medication knowledge before and after discharge, and assess the effect of TIME on patients’ experience and satisfaction with medication education.

Design: The study employed a longitudinal pretest/post-test, 2-group design involving 107 randomly selected medical-surgical patients from an academic hospital. Participants were interviewed before and within 72 hours after discharge following administration of medication instructions. Bivariate analyses were performed to assess demographic and outcome variable differences between groups.

Setting and participants: Conducted on a 24-bed medical-surgical unit at a large Magnet^® hospital over 18 months (2018-2019), the study included patients with at least 1 new medication, aged 18 years or older, able to read and speak English or Spanish, admitted from home with a minimum 1 overnight stay, and planning to return home post discharge. Excluded were cognitively impaired patients, those assigned to a resource pool nurse without TIME training, and those having a research team member assigned. Participants were randomly selected from a computerized list of patients scheduled for discharge.

Main outcome measures: Primary outcome measures included patients’ new medication knowledge before and after discharge and patients’ experience and satisfaction with medication education.

Main results: The usual care (n = 52) and TIME (n = 55) patients had similar baseline demographic characteristics. The study revealed that almost all patients in both usual care and TIME groups were aware of their new medication and its purpose at discharge. However, differences were observed in medication side effect responses, with 72.5% of the usual-care group knowing side effects compared to 94.3% of the TIME group (P = .003). Additionally, 81.5% of the usual-care group understood the medication purpose compared to 100% of the TIME group (P = .02). During the 48- to 72-hour postdischarge calls, consistent responses were found from both groups regarding knowledge of new medication, medication name, and medication purpose. Similar to discharge results, differences in medication side effect responses were observed, with 75.8% of the usual care group correctly identifying at least 1 medication side effect compared to 93.9% of the TIME group (P = .04). TIME was associated with higher satisfaction with medication education compared to usual care (97% vs. 46.9%, P < .001).

Conclusion: The nurse-led discharge medication education program TIME effectively enhanced patients’ new medication knowledge at discharge and 48 to 72 hours after discharge. The program also significantly improved patients’ experience and satisfaction with medication education. These findings indicate that TIME is a valuable tool for augmenting patient education and medication adherence in a hospital setting. By incorporating the teach-back method, TIME offers a structured approach to educating patients about their medications at hospital discharge, leading to improved care transitions.

Commentary

Suboptimal communication between patients, caregivers, and providers upon hospital discharge is a major contributor to patients’ inadequate understanding of postdischarge care plans. This inadequate understanding leads to preventable harms, such as medication errors, adverse events, emergency room visits, and costly hospital readmissions.¹ The issue is further exacerbated by a lack of clarity among health care team members’ respective roles in providing information that optimizes care transitions during the discharge communication process. Moreover, low health literacy, particularly prevalent among seniors, those from disadvantaged backgrouds, and those with lower education attainment or chronic illnesses, create additional barriers to effective discharge communication. A potential solution to this problem is the adoption of effective teaching strategies, specifically the teach-back method. This method employs techniques that ensure patients’ understanding and recall of new information regardless of health literacy, and places accountability on clinicians rather than patients. By closing communication gaps between clinicians and patients, the teach-back method can reduce hospital readmissions, hospital-acquired conditions, and mortality rates, while improving patient satisfaction with health care instructions and the overall hospital experience.²

Study 1, by Trivedi et al, and study 2, by Marks et al, aimed to identify and address problems related to poor communication between patients and health care team members at hospital discharge. Specifically, study 1 examined routine discharge communication practices to determine communication gaps, while study 2 evaluated a nurse-led teach-back intervention program designed to improve patients’ medication knowledge and satisfaction. These distinct objectives and designs reflected the unique ways each study approached the challenges associated with care transitions at the time of hospital discharge.

Study 1 used direct observation of patient-practitioner interactions to evaluate routine discharge communication practices in internal medicine services at 2 urban academic teaching hospitals. In the 33 patients observed, significant gaps in discharge communication practices were identified in the domains of medication changes, postdischarge appointments, disease self-management, and red flags or warning signs. Unsurprisingly, most of these domains were communicated in an ad hoc manner by members of the health care team without a clear pattern of responsibility in reference to patient discharge education, and teach-back was seldom used. These findings underscore the need for improved discharge techniques, effective communication strategies, and clarification of roles among the interprofessional team to enhance the safety, quality of care, and overall patient experience during hospital discharge.

Study 2 aimed to augment the hospital discharge communication process by implementing a nurse-led discharge medication education program (TIME), which targeted patients’ priority learning needs, new medication knowledge, and satisfaction with medication education. In the 107 patients assessed, this teach-back method enhanced patients’ new medication knowledge at discharge and 48 to 72 hours after discharge, as well as improved patients’ experience and satisfaction with medication education. These results suggest that a teach-back method such as the TIME program could be a solution to care transition problems identified in the Trivedi et al study by providing a structured approach to patient education and enhancing communication practices during the hospital discharge process. Thus, by implementing the TIME program, hospitals may improve patient outcomes, safety, and overall quality of care upon leaving the hospital.

Applications for Clinical Practice and System Implementation

Care transition at the time of hospital discharge is a particularly pivotal period in the care of vulnerable individuals. There is growing literature, including studies discussed in this review, to indicate that by focusing on improving patient-practitioner communication during the discharge process and using strategies such as the teach-back method, health care professionals can better prepare patients for self-management in the post-acute period and help them make informed decisions about their care. This emphasis on care-transition communication strategies may lead to a reduction in medication errors, adverse events, and hospital readmissions, ultimately improving patient outcomes and satisfaction. Barriers to system implementation of such strategies may include competing demands and responsibilities of busy practitioners as well as the inherent complexities associated with hospital discharge. Creative solutions, such as the utilization of telehealth and early transition-of-care visits, represent some potential approaches to counter these barriers.

While both studies illustrated barriers and facilitators of hospital discharge communication, each study had limitations that impacted their generalizability to real-world clinical practice. Limitations in study 1 included a small sample size, purposive sampling method, and a focus on planned discharges in a teaching hospital, which may introduce selection bias. The study’s findings may not be generalizable to unplanned discharges, patients who do not speak English or Spanish, or nonteaching hospitals. Additionally, the data were collected before the COVID-19 pandemic, which could have further impacted discharge education practices. The study also revealed that some patients received more robust discharge education than others, which indicated systemic inequality in the patient experience. Further research is required to address this discrepancy. Limitations in study 2 included a relatively small and homogeneous sample, with most participants being younger, non-Hispanic White, English-speaking, and well-educated. This lack of diversity may limit the generalizability of the findings. Furthermore, the study did not evaluate the patients’ knowledge of medication dosage and focused only on new medications. Future studies should examine the effect of teach-back on a broader range of self-management topics in preparation for discharge, while also including a more diverse population to account for factors related to social determinants of health. Taken together, further research is needed to address these limitations and ensure more generalizable results that can more broadly improve discharge education and care transitions that bridge acute and post-acute care.

Practice Points

• There is a significant need for improved discharge strategies to enhance patient safety and quality of care upon leaving the hospital.
• Teach-back method may offer a structured approach to educating patients about their medications at hospital discharge and improve care transitions.

–Yuka Shichijo, MD, and Fred Ko, MD, Mount Sinai Beth Israel Hospital, New York, NY

Study 1 Overview (Trivedi et al)

Objective: This observational quality improvement study aimed to evaluate the discharge communication practices in internal medicine services at 2 urban academic teaching hospitals, specifically focusing on patient education and counseling in 6 key discharge communication domains.

Design: Observations were conducted over a 13-month period from September 2018 through October 2019, following the Standards for Quality Improvement Reporting Excellence (SQUIRE) guidelines.

Setting and participants: The study involved a total of 33 English- and Spanish-speaking patients purposefully selected from the “discharge before noon” list at 2 urban tertiary-care teaching hospitals. A total of 155 observation hours were accumulated, with an average observation time of 4.7 hours per patient on the day of discharge.

Main outcome measures: The study assessed 6 discharge communication domains: (1) the name and function of medication changes, (2) the purpose of postdischarge appointments, (3) disease self-management, (4) red flags or warning signs for complications, (5) teach-back techniques to confirm patient understanding, and (6) staff solicitation of patient questions or concerns.

Main results: The study found several gaps in discharge communication practices. Among the 29 patients with medication changes, 28% were not informed about the name and basic function of the changes, while 59% did not receive counseling on the purpose for the medication change. In terms of postdischarge appointments, 48% of patients were not told the purpose of these appointments. Moreover, 54% of patients did not receive counseling on self-management of their primary discharge diagnosis or other diagnoses, and 73% were not informed about symptom expectations or the expected course of their illness after leaving the hospital. Most patients (82%) were not counseled on red-flag signs and symptoms that should prompt immediate return to care.

Teach-back techniques, which are critical for ensuring patient understanding, were used in only 3% of cases, and 85% of patients were not asked by health care providers if there might be barriers to following the care plan. Less than half (42%) of the patients were asked if they had any questions, with most questions being logistical and often deferred to another team member or met with uncertainty. Of note, among the 33 patients, only 2 patients received extensive information that covered 5 or 6 out of 6 discharge communication domains.

The study found variable roles in who communicated what aspects of discharge education, with most domains being communicated in an ad hoc manner and no clear pattern of responsibility. However, 2 exceptions were observed: nurses were more likely to provide information about new or changed medications and follow-up appointments, and the only example of teach-back was conducted by an attending physician.

Conclusion: The study highlights a significant need for improved discharge techniques to enhance patient safety and quality of care upon leaving the hospital. Interventions should focus on increasing transparency in patient education and understanding, clarifying assumptions of roles among the interprofessional team, and implementing effective communication strategies and system redesigns that foster patient-centered discharge education. Also, the study revealed that some patients received more robust discharge education than others, indicating systemic inequality in the patient experience. Further studies are needed to explore the development and assessment of such interventions to ensure optimal patient outcomes and equal care following hospital discharge.

Study 2 Overview (Marks et al)

Objective: This study aimed to investigate the impact of a nurse-led discharge medication education program, Teaching Important Medication Effects (TIME), on patients’ new medication knowledge at discharge and 48 to 72 hours post discharge. The specific objectives were to identify patients’ priority learning needs, evaluate the influence of TIME on patients’ new medication knowledge before and after discharge, and assess the effect of TIME on patients’ experience and satisfaction with medication education.

Design: The study employed a longitudinal pretest/post-test, 2-group design involving 107 randomly selected medical-surgical patients from an academic hospital. Participants were interviewed before and within 72 hours after discharge following administration of medication instructions. Bivariate analyses were performed to assess demographic and outcome variable differences between groups.

Setting and participants: Conducted on a 24-bed medical-surgical unit at a large Magnet^® hospital over 18 months (2018-2019), the study included patients with at least 1 new medication, aged 18 years or older, able to read and speak English or Spanish, admitted from home with a minimum 1 overnight stay, and planning to return home post discharge. Excluded were cognitively impaired patients, those assigned to a resource pool nurse without TIME training, and those having a research team member assigned. Participants were randomly selected from a computerized list of patients scheduled for discharge.

Main outcome measures: Primary outcome measures included patients’ new medication knowledge before and after discharge and patients’ experience and satisfaction with medication education.

Main results: The usual care (n = 52) and TIME (n = 55) patients had similar baseline demographic characteristics. The study revealed that almost all patients in both usual care and TIME groups were aware of their new medication and its purpose at discharge. However, differences were observed in medication side effect responses, with 72.5% of the usual-care group knowing side effects compared to 94.3% of the TIME group (P = .003). Additionally, 81.5% of the usual-care group understood the medication purpose compared to 100% of the TIME group (P = .02). During the 48- to 72-hour postdischarge calls, consistent responses were found from both groups regarding knowledge of new medication, medication name, and medication purpose. Similar to discharge results, differences in medication side effect responses were observed, with 75.8% of the usual care group correctly identifying at least 1 medication side effect compared to 93.9% of the TIME group (P = .04). TIME was associated with higher satisfaction with medication education compared to usual care (97% vs. 46.9%, P < .001).

Conclusion: The nurse-led discharge medication education program TIME effectively enhanced patients’ new medication knowledge at discharge and 48 to 72 hours after discharge. The program also significantly improved patients’ experience and satisfaction with medication education. These findings indicate that TIME is a valuable tool for augmenting patient education and medication adherence in a hospital setting. By incorporating the teach-back method, TIME offers a structured approach to educating patients about their medications at hospital discharge, leading to improved care transitions.

Commentary

Suboptimal communication between patients, caregivers, and providers upon hospital discharge is a major contributor to patients’ inadequate understanding of postdischarge care plans. This inadequate understanding leads to preventable harms, such as medication errors, adverse events, emergency room visits, and costly hospital readmissions.¹ The issue is further exacerbated by a lack of clarity among health care team members’ respective roles in providing information that optimizes care transitions during the discharge communication process. Moreover, low health literacy, particularly prevalent among seniors, those from disadvantaged backgrouds, and those with lower education attainment or chronic illnesses, create additional barriers to effective discharge communication. A potential solution to this problem is the adoption of effective teaching strategies, specifically the teach-back method. This method employs techniques that ensure patients’ understanding and recall of new information regardless of health literacy, and places accountability on clinicians rather than patients. By closing communication gaps between clinicians and patients, the teach-back method can reduce hospital readmissions, hospital-acquired conditions, and mortality rates, while improving patient satisfaction with health care instructions and the overall hospital experience.²

Study 1, by Trivedi et al, and study 2, by Marks et al, aimed to identify and address problems related to poor communication between patients and health care team members at hospital discharge. Specifically, study 1 examined routine discharge communication practices to determine communication gaps, while study 2 evaluated a nurse-led teach-back intervention program designed to improve patients’ medication knowledge and satisfaction. These distinct objectives and designs reflected the unique ways each study approached the challenges associated with care transitions at the time of hospital discharge.

Study 1 used direct observation of patient-practitioner interactions to evaluate routine discharge communication practices in internal medicine services at 2 urban academic teaching hospitals. In the 33 patients observed, significant gaps in discharge communication practices were identified in the domains of medication changes, postdischarge appointments, disease self-management, and red flags or warning signs. Unsurprisingly, most of these domains were communicated in an ad hoc manner by members of the health care team without a clear pattern of responsibility in reference to patient discharge education, and teach-back was seldom used. These findings underscore the need for improved discharge techniques, effective communication strategies, and clarification of roles among the interprofessional team to enhance the safety, quality of care, and overall patient experience during hospital discharge.

Study 2 aimed to augment the hospital discharge communication process by implementing a nurse-led discharge medication education program (TIME), which targeted patients’ priority learning needs, new medication knowledge, and satisfaction with medication education. In the 107 patients assessed, this teach-back method enhanced patients’ new medication knowledge at discharge and 48 to 72 hours after discharge, as well as improved patients’ experience and satisfaction with medication education. These results suggest that a teach-back method such as the TIME program could be a solution to care transition problems identified in the Trivedi et al study by providing a structured approach to patient education and enhancing communication practices during the hospital discharge process. Thus, by implementing the TIME program, hospitals may improve patient outcomes, safety, and overall quality of care upon leaving the hospital.

Applications for Clinical Practice and System Implementation

Care transition at the time of hospital discharge is a particularly pivotal period in the care of vulnerable individuals. There is growing literature, including studies discussed in this review, to indicate that by focusing on improving patient-practitioner communication during the discharge process and using strategies such as the teach-back method, health care professionals can better prepare patients for self-management in the post-acute period and help them make informed decisions about their care. This emphasis on care-transition communication strategies may lead to a reduction in medication errors, adverse events, and hospital readmissions, ultimately improving patient outcomes and satisfaction. Barriers to system implementation of such strategies may include competing demands and responsibilities of busy practitioners as well as the inherent complexities associated with hospital discharge. Creative solutions, such as the utilization of telehealth and early transition-of-care visits, represent some potential approaches to counter these barriers.

While both studies illustrated barriers and facilitators of hospital discharge communication, each study had limitations that impacted their generalizability to real-world clinical practice. Limitations in study 1 included a small sample size, purposive sampling method, and a focus on planned discharges in a teaching hospital, which may introduce selection bias. The study’s findings may not be generalizable to unplanned discharges, patients who do not speak English or Spanish, or nonteaching hospitals. Additionally, the data were collected before the COVID-19 pandemic, which could have further impacted discharge education practices. The study also revealed that some patients received more robust discharge education than others, which indicated systemic inequality in the patient experience. Further research is required to address this discrepancy. Limitations in study 2 included a relatively small and homogeneous sample, with most participants being younger, non-Hispanic White, English-speaking, and well-educated. This lack of diversity may limit the generalizability of the findings. Furthermore, the study did not evaluate the patients’ knowledge of medication dosage and focused only on new medications. Future studies should examine the effect of teach-back on a broader range of self-management topics in preparation for discharge, while also including a more diverse population to account for factors related to social determinants of health. Taken together, further research is needed to address these limitations and ensure more generalizable results that can more broadly improve discharge education and care transitions that bridge acute and post-acute care.

Practice Points

• There is a significant need for improved discharge strategies to enhance patient safety and quality of care upon leaving the hospital.
• Teach-back method may offer a structured approach to educating patients about their medications at hospital discharge and improve care transitions.

–Yuka Shichijo, MD, and Fred Ko, MD, Mount Sinai Beth Israel Hospital, New York, NY

Study 1 Overview (Trivedi et al)

Objective: This observational quality improvement study aimed to evaluate the discharge communication practices in internal medicine services at 2 urban academic teaching hospitals, specifically focusing on patient education and counseling in 6 key discharge communication domains.

Design: Observations were conducted over a 13-month period from September 2018 through October 2019, following the Standards for Quality Improvement Reporting Excellence (SQUIRE) guidelines.

Setting and participants: The study involved a total of 33 English- and Spanish-speaking patients purposefully selected from the “discharge before noon” list at 2 urban tertiary-care teaching hospitals. A total of 155 observation hours were accumulated, with an average observation time of 4.7 hours per patient on the day of discharge.

Main outcome measures: The study assessed 6 discharge communication domains: (1) the name and function of medication changes, (2) the purpose of postdischarge appointments, (3) disease self-management, (4) red flags or warning signs for complications, (5) teach-back techniques to confirm patient understanding, and (6) staff solicitation of patient questions or concerns.

Main results: The study found several gaps in discharge communication practices. Among the 29 patients with medication changes, 28% were not informed about the name and basic function of the changes, while 59% did not receive counseling on the purpose for the medication change. In terms of postdischarge appointments, 48% of patients were not told the purpose of these appointments. Moreover, 54% of patients did not receive counseling on self-management of their primary discharge diagnosis or other diagnoses, and 73% were not informed about symptom expectations or the expected course of their illness after leaving the hospital. Most patients (82%) were not counseled on red-flag signs and symptoms that should prompt immediate return to care.

Teach-back techniques, which are critical for ensuring patient understanding, were used in only 3% of cases, and 85% of patients were not asked by health care providers if there might be barriers to following the care plan. Less than half (42%) of the patients were asked if they had any questions, with most questions being logistical and often deferred to another team member or met with uncertainty. Of note, among the 33 patients, only 2 patients received extensive information that covered 5 or 6 out of 6 discharge communication domains.

The study found variable roles in who communicated what aspects of discharge education, with most domains being communicated in an ad hoc manner and no clear pattern of responsibility. However, 2 exceptions were observed: nurses were more likely to provide information about new or changed medications and follow-up appointments, and the only example of teach-back was conducted by an attending physician.

Conclusion: The study highlights a significant need for improved discharge techniques to enhance patient safety and quality of care upon leaving the hospital. Interventions should focus on increasing transparency in patient education and understanding, clarifying assumptions of roles among the interprofessional team, and implementing effective communication strategies and system redesigns that foster patient-centered discharge education. Also, the study revealed that some patients received more robust discharge education than others, indicating systemic inequality in the patient experience. Further studies are needed to explore the development and assessment of such interventions to ensure optimal patient outcomes and equal care following hospital discharge.

Study 2 Overview (Marks et al)

Objective: This study aimed to investigate the impact of a nurse-led discharge medication education program, Teaching Important Medication Effects (TIME), on patients’ new medication knowledge at discharge and 48 to 72 hours post discharge. The specific objectives were to identify patients’ priority learning needs, evaluate the influence of TIME on patients’ new medication knowledge before and after discharge, and assess the effect of TIME on patients’ experience and satisfaction with medication education.

Design: The study employed a longitudinal pretest/post-test, 2-group design involving 107 randomly selected medical-surgical patients from an academic hospital. Participants were interviewed before and within 72 hours after discharge following administration of medication instructions. Bivariate analyses were performed to assess demographic and outcome variable differences between groups.

Setting and participants: Conducted on a 24-bed medical-surgical unit at a large Magnet^® hospital over 18 months (2018-2019), the study included patients with at least 1 new medication, aged 18 years or older, able to read and speak English or Spanish, admitted from home with a minimum 1 overnight stay, and planning to return home post discharge. Excluded were cognitively impaired patients, those assigned to a resource pool nurse without TIME training, and those having a research team member assigned. Participants were randomly selected from a computerized list of patients scheduled for discharge.

Main outcome measures: Primary outcome measures included patients’ new medication knowledge before and after discharge and patients’ experience and satisfaction with medication education.

Main results: The usual care (n = 52) and TIME (n = 55) patients had similar baseline demographic characteristics. The study revealed that almost all patients in both usual care and TIME groups were aware of their new medication and its purpose at discharge. However, differences were observed in medication side effect responses, with 72.5% of the usual-care group knowing side effects compared to 94.3% of the TIME group (P = .003). Additionally, 81.5% of the usual-care group understood the medication purpose compared to 100% of the TIME group (P = .02). During the 48- to 72-hour postdischarge calls, consistent responses were found from both groups regarding knowledge of new medication, medication name, and medication purpose. Similar to discharge results, differences in medication side effect responses were observed, with 75.8% of the usual care group correctly identifying at least 1 medication side effect compared to 93.9% of the TIME group (P = .04). TIME was associated with higher satisfaction with medication education compared to usual care (97% vs. 46.9%, P < .001).

Conclusion: The nurse-led discharge medication education program TIME effectively enhanced patients’ new medication knowledge at discharge and 48 to 72 hours after discharge. The program also significantly improved patients’ experience and satisfaction with medication education. These findings indicate that TIME is a valuable tool for augmenting patient education and medication adherence in a hospital setting. By incorporating the teach-back method, TIME offers a structured approach to educating patients about their medications at hospital discharge, leading to improved care transitions.

Commentary

Suboptimal communication between patients, caregivers, and providers upon hospital discharge is a major contributor to patients’ inadequate understanding of postdischarge care plans. This inadequate understanding leads to preventable harms, such as medication errors, adverse events, emergency room visits, and costly hospital readmissions.¹ The issue is further exacerbated by a lack of clarity among health care team members’ respective roles in providing information that optimizes care transitions during the discharge communication process. Moreover, low health literacy, particularly prevalent among seniors, those from disadvantaged backgrouds, and those with lower education attainment or chronic illnesses, create additional barriers to effective discharge communication. A potential solution to this problem is the adoption of effective teaching strategies, specifically the teach-back method. This method employs techniques that ensure patients’ understanding and recall of new information regardless of health literacy, and places accountability on clinicians rather than patients. By closing communication gaps between clinicians and patients, the teach-back method can reduce hospital readmissions, hospital-acquired conditions, and mortality rates, while improving patient satisfaction with health care instructions and the overall hospital experience.²

Study 1, by Trivedi et al, and study 2, by Marks et al, aimed to identify and address problems related to poor communication between patients and health care team members at hospital discharge. Specifically, study 1 examined routine discharge communication practices to determine communication gaps, while study 2 evaluated a nurse-led teach-back intervention program designed to improve patients’ medication knowledge and satisfaction. These distinct objectives and designs reflected the unique ways each study approached the challenges associated with care transitions at the time of hospital discharge.

Study 1 used direct observation of patient-practitioner interactions to evaluate routine discharge communication practices in internal medicine services at 2 urban academic teaching hospitals. In the 33 patients observed, significant gaps in discharge communication practices were identified in the domains of medication changes, postdischarge appointments, disease self-management, and red flags or warning signs. Unsurprisingly, most of these domains were communicated in an ad hoc manner by members of the health care team without a clear pattern of responsibility in reference to patient discharge education, and teach-back was seldom used. These findings underscore the need for improved discharge techniques, effective communication strategies, and clarification of roles among the interprofessional team to enhance the safety, quality of care, and overall patient experience during hospital discharge.

Study 2 aimed to augment the hospital discharge communication process by implementing a nurse-led discharge medication education program (TIME), which targeted patients’ priority learning needs, new medication knowledge, and satisfaction with medication education. In the 107 patients assessed, this teach-back method enhanced patients’ new medication knowledge at discharge and 48 to 72 hours after discharge, as well as improved patients’ experience and satisfaction with medication education. These results suggest that a teach-back method such as the TIME program could be a solution to care transition problems identified in the Trivedi et al study by providing a structured approach to patient education and enhancing communication practices during the hospital discharge process. Thus, by implementing the TIME program, hospitals may improve patient outcomes, safety, and overall quality of care upon leaving the hospital.

Applications for Clinical Practice and System Implementation

Care transition at the time of hospital discharge is a particularly pivotal period in the care of vulnerable individuals. There is growing literature, including studies discussed in this review, to indicate that by focusing on improving patient-practitioner communication during the discharge process and using strategies such as the teach-back method, health care professionals can better prepare patients for self-management in the post-acute period and help them make informed decisions about their care. This emphasis on care-transition communication strategies may lead to a reduction in medication errors, adverse events, and hospital readmissions, ultimately improving patient outcomes and satisfaction. Barriers to system implementation of such strategies may include competing demands and responsibilities of busy practitioners as well as the inherent complexities associated with hospital discharge. Creative solutions, such as the utilization of telehealth and early transition-of-care visits, represent some potential approaches to counter these barriers.

While both studies illustrated barriers and facilitators of hospital discharge communication, each study had limitations that impacted their generalizability to real-world clinical practice. Limitations in study 1 included a small sample size, purposive sampling method, and a focus on planned discharges in a teaching hospital, which may introduce selection bias. The study’s findings may not be generalizable to unplanned discharges, patients who do not speak English or Spanish, or nonteaching hospitals. Additionally, the data were collected before the COVID-19 pandemic, which could have further impacted discharge education practices. The study also revealed that some patients received more robust discharge education than others, which indicated systemic inequality in the patient experience. Further research is required to address this discrepancy. Limitations in study 2 included a relatively small and homogeneous sample, with most participants being younger, non-Hispanic White, English-speaking, and well-educated. This lack of diversity may limit the generalizability of the findings. Furthermore, the study did not evaluate the patients’ knowledge of medication dosage and focused only on new medications. Future studies should examine the effect of teach-back on a broader range of self-management topics in preparation for discharge, while also including a more diverse population to account for factors related to social determinants of health. Taken together, further research is needed to address these limitations and ensure more generalizable results that can more broadly improve discharge education and care transitions that bridge acute and post-acute care.

Practice Points

• There is a significant need for improved discharge strategies to enhance patient safety and quality of care upon leaving the hospital.
• Teach-back method may offer a structured approach to educating patients about their medications at hospital discharge and improve care transitions.

–Yuka Shichijo, MD, and Fred Ko, MD, Mount Sinai Beth Israel Hospital, New York, NY

AURORA, COLO. – Artificial Intelligence has arrived at medical offices, whether or not clinicians feel ready for it.

AI might result in more accurate, efficient, and cost-effective care. But it’s possible it could cause harm. That’s according to Benjamin Collins, MD, at Vanderbilt University Medical Center, Nashville, Tenn., who spoke on the subject at the annual meeting of the Society of General Internal Medicine.

Understanding the nuances of AI is even more important because of the quick development of the algorithms.

“When I submitted this workshop, there was no ChatGPT,” said Dr. Collins, referring to Chat Generative Pre-trained Transformer, a recently released natural language processing model. “A lot has already changed.”
 

Biased data

Biased data are perhaps the biggest pitfall of AI algorithms, Dr. Collins said. If garbage data go in, garbage predictions come out.

If the dataset that trains the algorithm underrepresents a particular gender or ethnic group, for example, the algorithm may not respond accurately to prompts. When an AI tool compounds existing inequalities related to socioeconomic status, ethnicity, or sexual orientation, the algorithm is biased, according to Harvard researchers.

“People often assume that artificial intelligence is free of bias due to the use of scientific processes and its development,” he said. “But whatever flaws exist in data collection and old data can lead to poor representation or underrepresentation in the data used to train the AI tool.”

Racial minorities are underrepresented in studies; therefore, data input into an AI tool might skew results for these patients.

The Framingham Heart Study, for example, which began in 1948, examined heart disease in mainly White participants. The findings from the study resulted in the creation of a sex-specific algorithm that was used to estimate the 10-year cardiovascular risk of a patient. While the cardiovascular risk score was accurate for White persons, it was less accurate for Black patients.

A study published in Science in 2019 revealed bias in an algorithm that used health care costs as a proxy for health needs. Because less money was spent on Black patients who had the same level of need as their White counterparts, the output inaccurately showed that Black patients were healthier and thus did not require extra care.

Developers can also be a source of bias, inasmuch as AI often reflects preexisting human biases, Dr. Collins said.

“Algorithmic bias presents a clear risk of harm that clinicians must play against the benefits of using AI,” Dr. Collins said. “That risk of harm is often disproportionately distributed to marginalized populations.”

As clinicians use AI algorithms to diagnose and detect disease, predict outcomes, and guide treatment, trouble comes when those algorithms perform well for some patients and poorly for others. This gap can exacerbate existing disparities in health care outcomes.

Dr. Collins advised clinicians to push to find out what data were used to train AI algorithms to determine how bias could have influenced the model and whether the developers risk-adjusted for bias. If the training data are not available, clinicians should ask their employers and AI developers to know more about the system.

Clinicians may face the so-called black box phenomenon, which occurs when developers cannot or will not explain what data went into an AI model, Dr. Collins said.

According to Stanford (Calif.) University, AI must be trained on large datasets of images that have been annotated by human experts. Those datasets can cost millions of dollars to create, meaning corporations often fund them and do not always share the data publicly.

Some groups, such as Stanford’s Center for Artificial Intelligence in Medicine and Imaging, are working to acquire annotated datasets so researchers who train AI models can know where the data came from.

Paul Haidet, MD, MPH, an internist at Penn State College of Medicine, Hershey, sees the technology as a tool that requires careful handling.

“It takes a while to learn how to use a stethoscope, and AI is like that,” Dr. Haidet said. “The thing about AI, though, is that it can be just dropped into a system and no one knows how it works.”

Dr. Haidet said he likes knowing how the sausage is made, something AI developers are often reticent to make known.

“If you’re just putting blind faith in a tool, that’s scary,” Dr. Haidet said.
 

Transparency and ‘explainability’

The ability to explain what goes into tools is essential to maintaining trust in the health care system, Dr. Collins said.

“Part of knowing how much trust to place in the system is the transparency of those systems and the ability to audit how well the algorithm is performing,” Dr. Collins said. “The system should also regularly report to users the level of certainty with which it is providing an output rather than providing a simple binary output.”

Dr. Collins recommends that providers develop an understanding of the limits of AI regulations as well, which might including learning how the system was approved and how it is monitored.

“The FDA has oversight over some applications of AI and health care for software as a medical device, but there’s currently no dedicated process to evaluate the systems for the presence of bias,” Dr. Collins said. “The gaps in regulation leave the door open for the use of AI in clinical care that contain significant biases.”

Dr. Haidet likened AI tools to the Global Positioning System: A good GPS system will let users see alternate routes, opt out of toll roads or highways, and will highlight why routes have changed. But users need to understand how to read the map so they can tell when something seems amiss.

Dr. Collins and Dr. Haidet report no relevant financial relationships

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

AURORA, COLO. – Artificial Intelligence has arrived at medical offices, whether or not clinicians feel ready for it.

AI might result in more accurate, efficient, and cost-effective care. But it’s possible it could cause harm. That’s according to Benjamin Collins, MD, at Vanderbilt University Medical Center, Nashville, Tenn., who spoke on the subject at the annual meeting of the Society of General Internal Medicine.

Understanding the nuances of AI is even more important because of the quick development of the algorithms.

“When I submitted this workshop, there was no ChatGPT,” said Dr. Collins, referring to Chat Generative Pre-trained Transformer, a recently released natural language processing model. “A lot has already changed.”
 

Biased data

Biased data are perhaps the biggest pitfall of AI algorithms, Dr. Collins said. If garbage data go in, garbage predictions come out.

If the dataset that trains the algorithm underrepresents a particular gender or ethnic group, for example, the algorithm may not respond accurately to prompts. When an AI tool compounds existing inequalities related to socioeconomic status, ethnicity, or sexual orientation, the algorithm is biased, according to Harvard researchers.

“People often assume that artificial intelligence is free of bias due to the use of scientific processes and its development,” he said. “But whatever flaws exist in data collection and old data can lead to poor representation or underrepresentation in the data used to train the AI tool.”

Racial minorities are underrepresented in studies; therefore, data input into an AI tool might skew results for these patients.

The Framingham Heart Study, for example, which began in 1948, examined heart disease in mainly White participants. The findings from the study resulted in the creation of a sex-specific algorithm that was used to estimate the 10-year cardiovascular risk of a patient. While the cardiovascular risk score was accurate for White persons, it was less accurate for Black patients.

A study published in Science in 2019 revealed bias in an algorithm that used health care costs as a proxy for health needs. Because less money was spent on Black patients who had the same level of need as their White counterparts, the output inaccurately showed that Black patients were healthier and thus did not require extra care.

Developers can also be a source of bias, inasmuch as AI often reflects preexisting human biases, Dr. Collins said.

“Algorithmic bias presents a clear risk of harm that clinicians must play against the benefits of using AI,” Dr. Collins said. “That risk of harm is often disproportionately distributed to marginalized populations.”

As clinicians use AI algorithms to diagnose and detect disease, predict outcomes, and guide treatment, trouble comes when those algorithms perform well for some patients and poorly for others. This gap can exacerbate existing disparities in health care outcomes.

Dr. Collins advised clinicians to push to find out what data were used to train AI algorithms to determine how bias could have influenced the model and whether the developers risk-adjusted for bias. If the training data are not available, clinicians should ask their employers and AI developers to know more about the system.

Clinicians may face the so-called black box phenomenon, which occurs when developers cannot or will not explain what data went into an AI model, Dr. Collins said.

According to Stanford (Calif.) University, AI must be trained on large datasets of images that have been annotated by human experts. Those datasets can cost millions of dollars to create, meaning corporations often fund them and do not always share the data publicly.

Some groups, such as Stanford’s Center for Artificial Intelligence in Medicine and Imaging, are working to acquire annotated datasets so researchers who train AI models can know where the data came from.

Paul Haidet, MD, MPH, an internist at Penn State College of Medicine, Hershey, sees the technology as a tool that requires careful handling.

“It takes a while to learn how to use a stethoscope, and AI is like that,” Dr. Haidet said. “The thing about AI, though, is that it can be just dropped into a system and no one knows how it works.”

Dr. Haidet said he likes knowing how the sausage is made, something AI developers are often reticent to make known.

“If you’re just putting blind faith in a tool, that’s scary,” Dr. Haidet said.
 

Transparency and ‘explainability’

The ability to explain what goes into tools is essential to maintaining trust in the health care system, Dr. Collins said.

“Part of knowing how much trust to place in the system is the transparency of those systems and the ability to audit how well the algorithm is performing,” Dr. Collins said. “The system should also regularly report to users the level of certainty with which it is providing an output rather than providing a simple binary output.”

Dr. Collins recommends that providers develop an understanding of the limits of AI regulations as well, which might including learning how the system was approved and how it is monitored.

“The FDA has oversight over some applications of AI and health care for software as a medical device, but there’s currently no dedicated process to evaluate the systems for the presence of bias,” Dr. Collins said. “The gaps in regulation leave the door open for the use of AI in clinical care that contain significant biases.”

Dr. Haidet likened AI tools to the Global Positioning System: A good GPS system will let users see alternate routes, opt out of toll roads or highways, and will highlight why routes have changed. But users need to understand how to read the map so they can tell when something seems amiss.

Dr. Collins and Dr. Haidet report no relevant financial relationships

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

AURORA, COLO. – Artificial Intelligence has arrived at medical offices, whether or not clinicians feel ready for it.

AI might result in more accurate, efficient, and cost-effective care. But it’s possible it could cause harm. That’s according to Benjamin Collins, MD, at Vanderbilt University Medical Center, Nashville, Tenn., who spoke on the subject at the annual meeting of the Society of General Internal Medicine.

Understanding the nuances of AI is even more important because of the quick development of the algorithms.

“When I submitted this workshop, there was no ChatGPT,” said Dr. Collins, referring to Chat Generative Pre-trained Transformer, a recently released natural language processing model. “A lot has already changed.”
 

Biased data

Biased data are perhaps the biggest pitfall of AI algorithms, Dr. Collins said. If garbage data go in, garbage predictions come out.

If the dataset that trains the algorithm underrepresents a particular gender or ethnic group, for example, the algorithm may not respond accurately to prompts. When an AI tool compounds existing inequalities related to socioeconomic status, ethnicity, or sexual orientation, the algorithm is biased, according to Harvard researchers.

“People often assume that artificial intelligence is free of bias due to the use of scientific processes and its development,” he said. “But whatever flaws exist in data collection and old data can lead to poor representation or underrepresentation in the data used to train the AI tool.”

Racial minorities are underrepresented in studies; therefore, data input into an AI tool might skew results for these patients.

The Framingham Heart Study, for example, which began in 1948, examined heart disease in mainly White participants. The findings from the study resulted in the creation of a sex-specific algorithm that was used to estimate the 10-year cardiovascular risk of a patient. While the cardiovascular risk score was accurate for White persons, it was less accurate for Black patients.

A study published in Science in 2019 revealed bias in an algorithm that used health care costs as a proxy for health needs. Because less money was spent on Black patients who had the same level of need as their White counterparts, the output inaccurately showed that Black patients were healthier and thus did not require extra care.

Developers can also be a source of bias, inasmuch as AI often reflects preexisting human biases, Dr. Collins said.

“Algorithmic bias presents a clear risk of harm that clinicians must play against the benefits of using AI,” Dr. Collins said. “That risk of harm is often disproportionately distributed to marginalized populations.”

As clinicians use AI algorithms to diagnose and detect disease, predict outcomes, and guide treatment, trouble comes when those algorithms perform well for some patients and poorly for others. This gap can exacerbate existing disparities in health care outcomes.

Dr. Collins advised clinicians to push to find out what data were used to train AI algorithms to determine how bias could have influenced the model and whether the developers risk-adjusted for bias. If the training data are not available, clinicians should ask their employers and AI developers to know more about the system.

Clinicians may face the so-called black box phenomenon, which occurs when developers cannot or will not explain what data went into an AI model, Dr. Collins said.

According to Stanford (Calif.) University, AI must be trained on large datasets of images that have been annotated by human experts. Those datasets can cost millions of dollars to create, meaning corporations often fund them and do not always share the data publicly.

Some groups, such as Stanford’s Center for Artificial Intelligence in Medicine and Imaging, are working to acquire annotated datasets so researchers who train AI models can know where the data came from.

Paul Haidet, MD, MPH, an internist at Penn State College of Medicine, Hershey, sees the technology as a tool that requires careful handling.

“It takes a while to learn how to use a stethoscope, and AI is like that,” Dr. Haidet said. “The thing about AI, though, is that it can be just dropped into a system and no one knows how it works.”

Dr. Haidet said he likes knowing how the sausage is made, something AI developers are often reticent to make known.

“If you’re just putting blind faith in a tool, that’s scary,” Dr. Haidet said.
 

Transparency and ‘explainability’

The ability to explain what goes into tools is essential to maintaining trust in the health care system, Dr. Collins said.

“Part of knowing how much trust to place in the system is the transparency of those systems and the ability to audit how well the algorithm is performing,” Dr. Collins said. “The system should also regularly report to users the level of certainty with which it is providing an output rather than providing a simple binary output.”

Dr. Collins recommends that providers develop an understanding of the limits of AI regulations as well, which might including learning how the system was approved and how it is monitored.

“The FDA has oversight over some applications of AI and health care for software as a medical device, but there’s currently no dedicated process to evaluate the systems for the presence of bias,” Dr. Collins said. “The gaps in regulation leave the door open for the use of AI in clinical care that contain significant biases.”

Dr. Haidet likened AI tools to the Global Positioning System: A good GPS system will let users see alternate routes, opt out of toll roads or highways, and will highlight why routes have changed. But users need to understand how to read the map so they can tell when something seems amiss.

Dr. Collins and Dr. Haidet report no relevant financial relationships

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

Many of the persistent problems that breast cancer survivors experience after treatment are not part of the conversation with oncologists during treatment, said Patricia A. Ganz, MD, during a presentation at the European Society for Medical Oncology Breast Cancer annual congress.

Several studies suggest that many breast cancer patients are not well prepared to move forward after a breast cancer diagnosis and subsequent treatments, continued Dr. Ganz, who works at the UCLA Jonsson Comprehensive Cancer Center, Los Angeles.

Meeting the survivorship needs of breast cancer patients requires addressing both their physical and psychosocial needs, Dr. Ganz said. She explained how to achieve that, but first pointed to research elaborating on what's missing from some breast cancer survivors' care and barriers to these patients having their variety of health-related needs met.

In a 2021 study published in the Journal of Cancer Survivorship, Dr. Ganz and colleagues conducted a survey of approximately 200 medical oncologists in the United States. They determined that less than 50% provide survivorship care plans to patients at the end of treatment or communicate with patients’ other physicians about follow-up care.

In a secondary analysis of data from the same survey published in 2022 in Breast Cancer Research and Treatment, Dr. Ganz and colleagues examined medical oncologists’ perceived barriers to addressing both physical and psychosocial long-term effects in breast cancer survivors. For both, lack of time was the greatest perceived barrier, cited by nearly two-thirds of oncologists. Other barriers to addressing physical effects included lack of evidence-based, effective interventions, lack of clinical algorithms to guide care, and ambiguity regarding professional responsibility at the end of treatment. Other top barriers to addressing psychosocial issues included lack of mental health providers, lack of psychosocial resources, and lack of clinician knowledge and skills.

Data from additional studies suggest that, overall, cancer patients with greater physical burdens, such as more complex and lengthy treatment regimens, also have greater psychosocial needs, Dr. Ganz noted. Plus, approximately 15%-20% of cancer survivors have ongoing anxiety and depressive symptoms.

Shift to primary care

As more breast cancer and other cancer patients survive for longer periods, more care will likely occur in general medical settings, Dr. Ganz said. Issues to be addressed will include the potential increased risk of comorbid conditions for these survivors, and whether survivorship interventions earlier in the disease trajectory will impact survivorship. For cancer patients who achieve remission after treatment, the first 5 years after a diagnosis involves treatment and short-term surveillance for late effects. Beyond 5 years, care for cancer survivors mainly involves primary care and management of any comorbid conditions, as well as surveillance for late effects and recurrences, and awareness of new research.

A patient consultation early in the process after diagnosis is the start of a continuum of care, Dr. Ganz said. A patient consultation should address symptoms related to initial treatments, such as neuropathy, pain, fatigue, and insomnia, as well as the psychological symptoms of anxiety and depression. An early consultation also should evaluate adherence to endocrine therapy and management of symptoms, if needed, with the larger goal of preparing patients for recovery and the transition to survivorship, and what to expect for long-term follow-up.
 

Delivering the three P’s

The “Three P’s” of survivor care for breast cancer patients are palliation, prevention, and promotion of health, according to Dr. Ganz .

The first “P,” for palliative, is a key part of survivorship care, said Dr. Ganz. Palliative care is defined as care that focuses on reducing symptom severity and improving quality of life. The biological effects of cancer treatment can be associated with physical effects, such as functional limitations and frailty, and behavioral/cognitive effects such as depression, fatigue, and cognitive deficits, she said. To manage these effects and provide palliative care, consultation is needed with specialists in relevant areas including mental health, pain management, physical medicine/rehabilitation, endocrinology, cardiology, and neurology.

The second “P,” which is for prevention in survivorship care, refers to ongoing follow-up screening to identify any potentially serious late-onset complications such as osteoporosis or cardiac disease so they can be addressed, said Dr. Ganz. Other considerations include chemoprevention if available and genetic counseling for patients with hereditary cancers. Prevention also includes counseling patients about lifestyle modifications to help prevent additional cancer.

The goal of the third “P,” which is for health promotion, is to promote risk reduction for the health problems associated with accelerated aging that may arise in cancer survivors, said Dr. Ganz.

Health promotion strategies include maintaining a healthy weight, increasing physical activity, and avoiding harmful exposures, she said. Healthy lifestyle interventions can also reduce the risk of other chronic diseases such as diabetes and heart disease.

To that end, Dr. Ganz outlined several behavioral interventions that may mitigate the effects of cancer treatment on the accelerated aging process, including stress reduction in the form of meditation or yoga, cognitive behavioral therapy, improving sleep, increasing physical activity, reducing obesity, and decreasing tobacco and alcohol use. These interventions may help reduce inflammation and promote tissue repair and healing.

For cancer survivors, the life span may be longer than the health span, and these patients may benefit from an integrated model of care, with systematic screening and consolidated appointments, rather than a fragmented model in which departments and referrals are siloed, which may result in conflicting advice or redundancy, said Dr. Ganz.

Looking ahead, more research is needed to explore models of care delivery, as requirements for survivor care will vary among patients and care settings, Dr. Ganz said.

However, regardless of setting, treatment plans and shared decision-making can help reduce potential long-term or late-emerging effects, she said. Developing a survivorship care plan can help patients learn how to enhance their recovery.

During a question and answer session, Dr. Ganz was asked about whether hormone therapy could be used for patients with hormone negative breast cancer. “I think vaginal estrogen can be used if someone is on tamoxifen,” she said. However, “we need to be cautious” in case there are remaining estrogen positive cells, in order to avoid potential metastases, and use of hormone therapy in breast cancer survivors is an individualized decision based in part on quality of life.
 

Engaging a patient’s partner early can be helpful

If possible, engage the patient’s partner in survivorship discussions, said Luzia Travado, PhD, head of psycho-oncology at the Champalimaud Foundation, Lisbon, who presented on the topic of sexuality and commented on survivorship during the discussion. For those women with partners, engaging the partner early in treatment often means they are more likely to play a larger role in the post treatment and long term by providing stability and emotional support.

“Make sure partners are engaged and understand that they have a role, and that this role is valued,” she said. Unfortunately, there are a lot of divorced women with breast cancer, as the disease can take a toll on relationships. However, remember “sexuality is not just sex; it is caring, loving, and intimacy.”

“To end on a positive note, it is important to empower patients, and to give them self-management skills so they can make things even better in their survivorship,” said Dr. Ganz. In spite of discussing difficulties and challenges, one of the goals of the session was to offer potential solutions and answers.

Dr. Ganz disclosed serving as editor of the cancer survivorship section on Up-to-Date, and serving as a consultant for Blue Note Therapeutics, GRAIL, InformedDNA, and Roche-Genentech. Dr. Travado had no relevant financial conflicts to disclose.

Many of the persistent problems that breast cancer survivors experience after treatment are not part of the conversation with oncologists during treatment, said Patricia A. Ganz, MD, during a presentation at the European Society for Medical Oncology Breast Cancer annual congress.

Several studies suggest that many breast cancer patients are not well prepared to move forward after a breast cancer diagnosis and subsequent treatments, continued Dr. Ganz, who works at the UCLA Jonsson Comprehensive Cancer Center, Los Angeles.

Meeting the survivorship needs of breast cancer patients requires addressing both their physical and psychosocial needs, Dr. Ganz said. She explained how to achieve that, but first pointed to research elaborating on what's missing from some breast cancer survivors' care and barriers to these patients having their variety of health-related needs met.

In a 2021 study published in the Journal of Cancer Survivorship, Dr. Ganz and colleagues conducted a survey of approximately 200 medical oncologists in the United States. They determined that less than 50% provide survivorship care plans to patients at the end of treatment or communicate with patients’ other physicians about follow-up care.

In a secondary analysis of data from the same survey published in 2022 in Breast Cancer Research and Treatment, Dr. Ganz and colleagues examined medical oncologists’ perceived barriers to addressing both physical and psychosocial long-term effects in breast cancer survivors. For both, lack of time was the greatest perceived barrier, cited by nearly two-thirds of oncologists. Other barriers to addressing physical effects included lack of evidence-based, effective interventions, lack of clinical algorithms to guide care, and ambiguity regarding professional responsibility at the end of treatment. Other top barriers to addressing psychosocial issues included lack of mental health providers, lack of psychosocial resources, and lack of clinician knowledge and skills.

Data from additional studies suggest that, overall, cancer patients with greater physical burdens, such as more complex and lengthy treatment regimens, also have greater psychosocial needs, Dr. Ganz noted. Plus, approximately 15%-20% of cancer survivors have ongoing anxiety and depressive symptoms.

Shift to primary care

As more breast cancer and other cancer patients survive for longer periods, more care will likely occur in general medical settings, Dr. Ganz said. Issues to be addressed will include the potential increased risk of comorbid conditions for these survivors, and whether survivorship interventions earlier in the disease trajectory will impact survivorship. For cancer patients who achieve remission after treatment, the first 5 years after a diagnosis involves treatment and short-term surveillance for late effects. Beyond 5 years, care for cancer survivors mainly involves primary care and management of any comorbid conditions, as well as surveillance for late effects and recurrences, and awareness of new research.

A patient consultation early in the process after diagnosis is the start of a continuum of care, Dr. Ganz said. A patient consultation should address symptoms related to initial treatments, such as neuropathy, pain, fatigue, and insomnia, as well as the psychological symptoms of anxiety and depression. An early consultation also should evaluate adherence to endocrine therapy and management of symptoms, if needed, with the larger goal of preparing patients for recovery and the transition to survivorship, and what to expect for long-term follow-up.
 

Delivering the three P’s

The “Three P’s” of survivor care for breast cancer patients are palliation, prevention, and promotion of health, according to Dr. Ganz .

The first “P,” for palliative, is a key part of survivorship care, said Dr. Ganz. Palliative care is defined as care that focuses on reducing symptom severity and improving quality of life. The biological effects of cancer treatment can be associated with physical effects, such as functional limitations and frailty, and behavioral/cognitive effects such as depression, fatigue, and cognitive deficits, she said. To manage these effects and provide palliative care, consultation is needed with specialists in relevant areas including mental health, pain management, physical medicine/rehabilitation, endocrinology, cardiology, and neurology.

The second “P,” which is for prevention in survivorship care, refers to ongoing follow-up screening to identify any potentially serious late-onset complications such as osteoporosis or cardiac disease so they can be addressed, said Dr. Ganz. Other considerations include chemoprevention if available and genetic counseling for patients with hereditary cancers. Prevention also includes counseling patients about lifestyle modifications to help prevent additional cancer.

The goal of the third “P,” which is for health promotion, is to promote risk reduction for the health problems associated with accelerated aging that may arise in cancer survivors, said Dr. Ganz.

Health promotion strategies include maintaining a healthy weight, increasing physical activity, and avoiding harmful exposures, she said. Healthy lifestyle interventions can also reduce the risk of other chronic diseases such as diabetes and heart disease.

To that end, Dr. Ganz outlined several behavioral interventions that may mitigate the effects of cancer treatment on the accelerated aging process, including stress reduction in the form of meditation or yoga, cognitive behavioral therapy, improving sleep, increasing physical activity, reducing obesity, and decreasing tobacco and alcohol use. These interventions may help reduce inflammation and promote tissue repair and healing.

For cancer survivors, the life span may be longer than the health span, and these patients may benefit from an integrated model of care, with systematic screening and consolidated appointments, rather than a fragmented model in which departments and referrals are siloed, which may result in conflicting advice or redundancy, said Dr. Ganz.

Looking ahead, more research is needed to explore models of care delivery, as requirements for survivor care will vary among patients and care settings, Dr. Ganz said.

However, regardless of setting, treatment plans and shared decision-making can help reduce potential long-term or late-emerging effects, she said. Developing a survivorship care plan can help patients learn how to enhance their recovery.

During a question and answer session, Dr. Ganz was asked about whether hormone therapy could be used for patients with hormone negative breast cancer. “I think vaginal estrogen can be used if someone is on tamoxifen,” she said. However, “we need to be cautious” in case there are remaining estrogen positive cells, in order to avoid potential metastases, and use of hormone therapy in breast cancer survivors is an individualized decision based in part on quality of life.
 

Engaging a patient’s partner early can be helpful

If possible, engage the patient’s partner in survivorship discussions, said Luzia Travado, PhD, head of psycho-oncology at the Champalimaud Foundation, Lisbon, who presented on the topic of sexuality and commented on survivorship during the discussion. For those women with partners, engaging the partner early in treatment often means they are more likely to play a larger role in the post treatment and long term by providing stability and emotional support.

“Make sure partners are engaged and understand that they have a role, and that this role is valued,” she said. Unfortunately, there are a lot of divorced women with breast cancer, as the disease can take a toll on relationships. However, remember “sexuality is not just sex; it is caring, loving, and intimacy.”

“To end on a positive note, it is important to empower patients, and to give them self-management skills so they can make things even better in their survivorship,” said Dr. Ganz. In spite of discussing difficulties and challenges, one of the goals of the session was to offer potential solutions and answers.

Dr. Ganz disclosed serving as editor of the cancer survivorship section on Up-to-Date, and serving as a consultant for Blue Note Therapeutics, GRAIL, InformedDNA, and Roche-Genentech. Dr. Travado had no relevant financial conflicts to disclose.

Many of the persistent problems that breast cancer survivors experience after treatment are not part of the conversation with oncologists during treatment, said Patricia A. Ganz, MD, during a presentation at the European Society for Medical Oncology Breast Cancer annual congress.

Several studies suggest that many breast cancer patients are not well prepared to move forward after a breast cancer diagnosis and subsequent treatments, continued Dr. Ganz, who works at the UCLA Jonsson Comprehensive Cancer Center, Los Angeles.

Meeting the survivorship needs of breast cancer patients requires addressing both their physical and psychosocial needs, Dr. Ganz said. She explained how to achieve that, but first pointed to research elaborating on what's missing from some breast cancer survivors' care and barriers to these patients having their variety of health-related needs met.

In a 2021 study published in the Journal of Cancer Survivorship, Dr. Ganz and colleagues conducted a survey of approximately 200 medical oncologists in the United States. They determined that less than 50% provide survivorship care plans to patients at the end of treatment or communicate with patients’ other physicians about follow-up care.

In a secondary analysis of data from the same survey published in 2022 in Breast Cancer Research and Treatment, Dr. Ganz and colleagues examined medical oncologists’ perceived barriers to addressing both physical and psychosocial long-term effects in breast cancer survivors. For both, lack of time was the greatest perceived barrier, cited by nearly two-thirds of oncologists. Other barriers to addressing physical effects included lack of evidence-based, effective interventions, lack of clinical algorithms to guide care, and ambiguity regarding professional responsibility at the end of treatment. Other top barriers to addressing psychosocial issues included lack of mental health providers, lack of psychosocial resources, and lack of clinician knowledge and skills.

Data from additional studies suggest that, overall, cancer patients with greater physical burdens, such as more complex and lengthy treatment regimens, also have greater psychosocial needs, Dr. Ganz noted. Plus, approximately 15%-20% of cancer survivors have ongoing anxiety and depressive symptoms.

Shift to primary care

As more breast cancer and other cancer patients survive for longer periods, more care will likely occur in general medical settings, Dr. Ganz said. Issues to be addressed will include the potential increased risk of comorbid conditions for these survivors, and whether survivorship interventions earlier in the disease trajectory will impact survivorship. For cancer patients who achieve remission after treatment, the first 5 years after a diagnosis involves treatment and short-term surveillance for late effects. Beyond 5 years, care for cancer survivors mainly involves primary care and management of any comorbid conditions, as well as surveillance for late effects and recurrences, and awareness of new research.

A patient consultation early in the process after diagnosis is the start of a continuum of care, Dr. Ganz said. A patient consultation should address symptoms related to initial treatments, such as neuropathy, pain, fatigue, and insomnia, as well as the psychological symptoms of anxiety and depression. An early consultation also should evaluate adherence to endocrine therapy and management of symptoms, if needed, with the larger goal of preparing patients for recovery and the transition to survivorship, and what to expect for long-term follow-up.
 

Delivering the three P’s

The “Three P’s” of survivor care for breast cancer patients are palliation, prevention, and promotion of health, according to Dr. Ganz .

The first “P,” for palliative, is a key part of survivorship care, said Dr. Ganz. Palliative care is defined as care that focuses on reducing symptom severity and improving quality of life. The biological effects of cancer treatment can be associated with physical effects, such as functional limitations and frailty, and behavioral/cognitive effects such as depression, fatigue, and cognitive deficits, she said. To manage these effects and provide palliative care, consultation is needed with specialists in relevant areas including mental health, pain management, physical medicine/rehabilitation, endocrinology, cardiology, and neurology.

The second “P,” which is for prevention in survivorship care, refers to ongoing follow-up screening to identify any potentially serious late-onset complications such as osteoporosis or cardiac disease so they can be addressed, said Dr. Ganz. Other considerations include chemoprevention if available and genetic counseling for patients with hereditary cancers. Prevention also includes counseling patients about lifestyle modifications to help prevent additional cancer.

The goal of the third “P,” which is for health promotion, is to promote risk reduction for the health problems associated with accelerated aging that may arise in cancer survivors, said Dr. Ganz.

Health promotion strategies include maintaining a healthy weight, increasing physical activity, and avoiding harmful exposures, she said. Healthy lifestyle interventions can also reduce the risk of other chronic diseases such as diabetes and heart disease.

To that end, Dr. Ganz outlined several behavioral interventions that may mitigate the effects of cancer treatment on the accelerated aging process, including stress reduction in the form of meditation or yoga, cognitive behavioral therapy, improving sleep, increasing physical activity, reducing obesity, and decreasing tobacco and alcohol use. These interventions may help reduce inflammation and promote tissue repair and healing.

For cancer survivors, the life span may be longer than the health span, and these patients may benefit from an integrated model of care, with systematic screening and consolidated appointments, rather than a fragmented model in which departments and referrals are siloed, which may result in conflicting advice or redundancy, said Dr. Ganz.

Looking ahead, more research is needed to explore models of care delivery, as requirements for survivor care will vary among patients and care settings, Dr. Ganz said.

However, regardless of setting, treatment plans and shared decision-making can help reduce potential long-term or late-emerging effects, she said. Developing a survivorship care plan can help patients learn how to enhance their recovery.

During a question and answer session, Dr. Ganz was asked about whether hormone therapy could be used for patients with hormone negative breast cancer. “I think vaginal estrogen can be used if someone is on tamoxifen,” she said. However, “we need to be cautious” in case there are remaining estrogen positive cells, in order to avoid potential metastases, and use of hormone therapy in breast cancer survivors is an individualized decision based in part on quality of life.
 

Engaging a patient’s partner early can be helpful

If possible, engage the patient’s partner in survivorship discussions, said Luzia Travado, PhD, head of psycho-oncology at the Champalimaud Foundation, Lisbon, who presented on the topic of sexuality and commented on survivorship during the discussion. For those women with partners, engaging the partner early in treatment often means they are more likely to play a larger role in the post treatment and long term by providing stability and emotional support.

“Make sure partners are engaged and understand that they have a role, and that this role is valued,” she said. Unfortunately, there are a lot of divorced women with breast cancer, as the disease can take a toll on relationships. However, remember “sexuality is not just sex; it is caring, loving, and intimacy.”

“To end on a positive note, it is important to empower patients, and to give them self-management skills so they can make things even better in their survivorship,” said Dr. Ganz. In spite of discussing difficulties and challenges, one of the goals of the session was to offer potential solutions and answers.

Dr. Ganz disclosed serving as editor of the cancer survivorship section on Up-to-Date, and serving as a consultant for Blue Note Therapeutics, GRAIL, InformedDNA, and Roche-Genentech. Dr. Travado had no relevant financial conflicts to disclose.

“What am I allowed to do?” radiation oncologist Vivek Kavadi, MD, asked the business manager at Texas Oncology in Sugar Land, Tex.

Dr. Kavadi wanted to give his patient with early-stage breast cancer a standard radiation treatment – hypofractionated 3D conformal radiation therapy – following her lumpectomy.

But his hands were tied.

Dr. Kavadi had submitted a prior authorization request, but the patient’s health insurance was dragging its feet. And without prior authorization, Dr. Kavadi couldn’t schedule his patient’s first treatment.

“I chose the most cost-effective, standard treatment, but nothing could begin without the insurance company’s permission,” he said.

One of the most challenging aspects of the delay was explaining to his patient why he couldn’t schedule her treatment. “We would love to start, but your insurance company has not given us approval. The best I can do is give you a tentative appointment,” he recalled telling her.

After a few days with no word, calls to the insurance company began. “My patient called, I called, my office called,” Dr. Kavadi said. “It was a week or more of aggravation, stress, and time wasted for my patient and my team.”

This type of delay has become increasingly common in radiation oncology. One recent analysis estimated that 97% of radiation oncology services now require prior authorization under Medicare Advantage. And another analysis found that almost all radiation oncologists said prior authorization delays life-saving care for their patients.

The rise of prior authorization requirements may boil down to the fact that prior authorization is no longer reserved for uncertain or high-cost care. Terrence Cunningham, director of administrative simplification policy for the American Hospital Association, told this news organization last year that “prior authorization used to be applied only to new, costly, or high-risk services,” but now “many insurers require authorizations for even routine care, which is inappropriate.”

The growth of prior authorization requirements has forced many doctors, nurses, and pharmacists to dedicate part of their workday to handling requests and appealing denials and has forced many practices to hire staff exclusively for prior authorizations.

This additional work is costly.

One recent study found that the radiation oncology department of Vanderbilt University, Nashville, Tenn., spent nearly $500,000 annually in employee time to obtain prior authorization for radiation therapy treatments. Extrapolated nationally, the researchers estimated that physicians’ annual compensation for prior authorization duties came to an estimated $46 million. Overall, 86% of these costs were for treatments that were ultimately approved, the majority on initial request and some on appeal.

Dr. Kavadi has five full-time employees dedicated to managing prior authorization requests and challenges.

And after a week of delays and hours on the phone with the insurer, his patient’s radiation treatment was ultimately approved.

Dr. Kavadi wondered why something so simple needed to be so onerous.

Stretching out an approval for a standard radiation treatment “feels like a means of intentionally delaying care,” Dr. Kavadi said. “This is an example of a process that has run so far amok. It’s just a burden across the board.”

And even with his 30 years of experience, “I still have to ask my business supervisor what I am allowed to do,” he said. “I can’t just proceed with what’s best for my patient, what the patient has consented to, and what also happens to be the least expensive option.”

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

“What am I allowed to do?” radiation oncologist Vivek Kavadi, MD, asked the business manager at Texas Oncology in Sugar Land, Tex.

Dr. Kavadi wanted to give his patient with early-stage breast cancer a standard radiation treatment – hypofractionated 3D conformal radiation therapy – following her lumpectomy.

But his hands were tied.

Dr. Kavadi had submitted a prior authorization request, but the patient’s health insurance was dragging its feet. And without prior authorization, Dr. Kavadi couldn’t schedule his patient’s first treatment.

“I chose the most cost-effective, standard treatment, but nothing could begin without the insurance company’s permission,” he said.

One of the most challenging aspects of the delay was explaining to his patient why he couldn’t schedule her treatment. “We would love to start, but your insurance company has not given us approval. The best I can do is give you a tentative appointment,” he recalled telling her.

After a few days with no word, calls to the insurance company began. “My patient called, I called, my office called,” Dr. Kavadi said. “It was a week or more of aggravation, stress, and time wasted for my patient and my team.”

This type of delay has become increasingly common in radiation oncology. One recent analysis estimated that 97% of radiation oncology services now require prior authorization under Medicare Advantage. And another analysis found that almost all radiation oncologists said prior authorization delays life-saving care for their patients.

The rise of prior authorization requirements may boil down to the fact that prior authorization is no longer reserved for uncertain or high-cost care. Terrence Cunningham, director of administrative simplification policy for the American Hospital Association, told this news organization last year that “prior authorization used to be applied only to new, costly, or high-risk services,” but now “many insurers require authorizations for even routine care, which is inappropriate.”

The growth of prior authorization requirements has forced many doctors, nurses, and pharmacists to dedicate part of their workday to handling requests and appealing denials and has forced many practices to hire staff exclusively for prior authorizations.

This additional work is costly.

One recent study found that the radiation oncology department of Vanderbilt University, Nashville, Tenn., spent nearly $500,000 annually in employee time to obtain prior authorization for radiation therapy treatments. Extrapolated nationally, the researchers estimated that physicians’ annual compensation for prior authorization duties came to an estimated $46 million. Overall, 86% of these costs were for treatments that were ultimately approved, the majority on initial request and some on appeal.

Dr. Kavadi has five full-time employees dedicated to managing prior authorization requests and challenges.

And after a week of delays and hours on the phone with the insurer, his patient’s radiation treatment was ultimately approved.

Dr. Kavadi wondered why something so simple needed to be so onerous.

Stretching out an approval for a standard radiation treatment “feels like a means of intentionally delaying care,” Dr. Kavadi said. “This is an example of a process that has run so far amok. It’s just a burden across the board.”

And even with his 30 years of experience, “I still have to ask my business supervisor what I am allowed to do,” he said. “I can’t just proceed with what’s best for my patient, what the patient has consented to, and what also happens to be the least expensive option.”

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

“What am I allowed to do?” radiation oncologist Vivek Kavadi, MD, asked the business manager at Texas Oncology in Sugar Land, Tex.

Dr. Kavadi wanted to give his patient with early-stage breast cancer a standard radiation treatment – hypofractionated 3D conformal radiation therapy – following her lumpectomy.

But his hands were tied.

Dr. Kavadi had submitted a prior authorization request, but the patient’s health insurance was dragging its feet. And without prior authorization, Dr. Kavadi couldn’t schedule his patient’s first treatment.

“I chose the most cost-effective, standard treatment, but nothing could begin without the insurance company’s permission,” he said.

One of the most challenging aspects of the delay was explaining to his patient why he couldn’t schedule her treatment. “We would love to start, but your insurance company has not given us approval. The best I can do is give you a tentative appointment,” he recalled telling her.

After a few days with no word, calls to the insurance company began. “My patient called, I called, my office called,” Dr. Kavadi said. “It was a week or more of aggravation, stress, and time wasted for my patient and my team.”

This type of delay has become increasingly common in radiation oncology. One recent analysis estimated that 97% of radiation oncology services now require prior authorization under Medicare Advantage. And another analysis found that almost all radiation oncologists said prior authorization delays life-saving care for their patients.

The rise of prior authorization requirements may boil down to the fact that prior authorization is no longer reserved for uncertain or high-cost care. Terrence Cunningham, director of administrative simplification policy for the American Hospital Association, told this news organization last year that “prior authorization used to be applied only to new, costly, or high-risk services,” but now “many insurers require authorizations for even routine care, which is inappropriate.”

The growth of prior authorization requirements has forced many doctors, nurses, and pharmacists to dedicate part of their workday to handling requests and appealing denials and has forced many practices to hire staff exclusively for prior authorizations.

This additional work is costly.

One recent study found that the radiation oncology department of Vanderbilt University, Nashville, Tenn., spent nearly $500,000 annually in employee time to obtain prior authorization for radiation therapy treatments. Extrapolated nationally, the researchers estimated that physicians’ annual compensation for prior authorization duties came to an estimated $46 million. Overall, 86% of these costs were for treatments that were ultimately approved, the majority on initial request and some on appeal.

Dr. Kavadi has five full-time employees dedicated to managing prior authorization requests and challenges.

And after a week of delays and hours on the phone with the insurer, his patient’s radiation treatment was ultimately approved.

Dr. Kavadi wondered why something so simple needed to be so onerous.

Stretching out an approval for a standard radiation treatment “feels like a means of intentionally delaying care,” Dr. Kavadi said. “This is an example of a process that has run so far amok. It’s just a burden across the board.”

And even with his 30 years of experience, “I still have to ask my business supervisor what I am allowed to do,” he said. “I can’t just proceed with what’s best for my patient, what the patient has consented to, and what also happens to be the least expensive option.”

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

Inpatient dermatology consultation services are becoming increasingly prevalent in hospital institutions.^1-3 Although often underutilized as a consulting service, dermatology-related admissions cost hundreds of millions of dollars for the health care system.^1,2 Misdiagnosis, prolonged hospital stays, and incorrect treatment are common results of lack of involvement by a skin expert.^1-3 The importance of consultative inpatient dermatology cannot be understated. Accreditation Council for Graduate Medical Education requirements for proficiency in dermatology residency include exposure to inpatient dermatology, and it is our duty as residents to aid our colleagues in the management and treatment of cutaneous disease.

Although exposure to inpatient dermatology varies across residency programs, nearly every dermatology resident is bound to perform a consultation and be involved in the care of a hospitalized patient. At our program at the University of Utah (Salt Lake City), we have robust inpatient exposure, and after numerous hours spent on the forefront of inpatient dermatology, I have accrued a list of specific tips and techniques that have aided me as a resident clinician.

Pre-Rounding More Thoroughly

When I started as a postgraduate year 2 (PGY-2) on the inpatient dermatology rotation, I found myself perplexed. I had learned how to round in internal medicine but was unaccustomed to the nuances of specialty rounds. My list included calciphylaxis, small vessel vasculitis, cellulitis, stasis dermatitis, toxic epidermal necrolysis, and atypical mycobacterial infection. The first few days of service were undeniably difficult due to the daily consultations, complexity of admitted patients, and need for efficiency. I sometimes overlooked important laboratory test results, medication changes, and interdisciplinary discussions that prolonged rounding. As dermatologists, we are responsible for the largest organ of the body, and it is important to approach patients in a comprehensive manner. Pre-rounding should include reviewing interdisciplinary notes, laboratory values/results, and medications, and performing a focused skin examination with a review of systems during the encounter. Importantly, most electronic medical record systems offer an automated rounding sheet. In Epic (Epic Systems Corporation), I would use the bone marrow transplant rounding sheet, which includes laboratory test results, vitals, and medications. After printing out the rounding sheet, I would note important updates for each patient. Although pre-rounding and chart review requires time and effort, it aided me in providing elevated patient care and becoming more efficient during rounds. Over time I have come to strongly appreciate the term dermatology hospitalist. Cutaneous manifestations of systemic disease require thoughtful consideration and workup.

New Patient Consultations: Must-Ask Questions

Holding the university inpatient pager can be stressful. At the University of Utah, we often carry 5 to 10 patients on our list and receive 3 to 4 new consultations a day, sometimes right before 5 pm. When receiving new consultations, it is important to obtain the whole story from the requesting provider. Some of the questions may seem obvious, but I am frequently reminded of the inefficiencies I encountered as a first-year dermatology resident. Remember to always be kind to your consulting colleagues. Dermatology is a difficult discipline, and describing rashes is no easy task. Here is my systematic approach to questions that should be asked of the requesting provider during each new patient consultation:

• What is the patient’s name, room number, and medical record number?
• Is this patient getting admitted or admitted currently?
• Is the rash the reason for admission? (This can greatly help with triaging the urgency of evaluation.)
• Is the rash painful?
• Is this patient ill?
• How would you describe the rash?

When evaluating new patients, it is crucial to remember the morphology camps. Formulating a differential diagnosis on a complex patient can be difficult; however, remembering the morphology camps of acneiform, dermal, eczematous, erythematous, subcutaneous, vasculitic, vasculopathic, and vesiculobullous lesions can be extremely helpful. Additionally, it is crucial to perform a thorough and complete skin examination on every patient. When emphasizing the importance of this, I often am reminded of a humbling moment early in my training. Our team was consulted on a patient with cellulitis and stasis dermatitis. It was a busy day, and my examination was quick and focused on the lower and upper extremities, chest, and back. The patient improved from a cutaneous standpoint and was discharged. At follow-up the next week, one of my attending providers biopsied an atypical macule on the retroauricular region, which was found to be consistent with a stage 1A melanoma. Even on the longest and most tiring hospital days, it is important to perform a full-body skin examination on each patient. You may end up saving a life.

An Organized Toolbox: What to Carry

Similar to our ophthalmology colleagues who are seen carrying around a suitcase in the hospital, I highly recommend some form of a toolbox or bag for performing inpatient biopsies (Table). Carrying around an organized bag, albeit bulky and unfashionable, has saved me numerous trips back to clinic for unexpected complications including fixing leaky vessels, closing stubborn ulcers, and coordinating sedated biopsies in the operating room.

Final Thoughts

As I near the completion of my residency journey, I hope these tips will aid budding and current dermatology residents at excelling as dermatology hospitalists during inpatient rotations. Dermatologists can make a profound impact on a variety of patients, especially when treating hospitalized patients on the clinical forefront. Our role extends beyond the skin, as cutaneous manifestations of internal disease are not uncommon.

Inpatient dermatology consultation services are becoming increasingly prevalent in hospital institutions.^1-3 Although often underutilized as a consulting service, dermatology-related admissions cost hundreds of millions of dollars for the health care system.^1,2 Misdiagnosis, prolonged hospital stays, and incorrect treatment are common results of lack of involvement by a skin expert.^1-3 The importance of consultative inpatient dermatology cannot be understated. Accreditation Council for Graduate Medical Education requirements for proficiency in dermatology residency include exposure to inpatient dermatology, and it is our duty as residents to aid our colleagues in the management and treatment of cutaneous disease.

Although exposure to inpatient dermatology varies across residency programs, nearly every dermatology resident is bound to perform a consultation and be involved in the care of a hospitalized patient. At our program at the University of Utah (Salt Lake City), we have robust inpatient exposure, and after numerous hours spent on the forefront of inpatient dermatology, I have accrued a list of specific tips and techniques that have aided me as a resident clinician.

Pre-Rounding More Thoroughly

When I started as a postgraduate year 2 (PGY-2) on the inpatient dermatology rotation, I found myself perplexed. I had learned how to round in internal medicine but was unaccustomed to the nuances of specialty rounds. My list included calciphylaxis, small vessel vasculitis, cellulitis, stasis dermatitis, toxic epidermal necrolysis, and atypical mycobacterial infection. The first few days of service were undeniably difficult due to the daily consultations, complexity of admitted patients, and need for efficiency. I sometimes overlooked important laboratory test results, medication changes, and interdisciplinary discussions that prolonged rounding. As dermatologists, we are responsible for the largest organ of the body, and it is important to approach patients in a comprehensive manner. Pre-rounding should include reviewing interdisciplinary notes, laboratory values/results, and medications, and performing a focused skin examination with a review of systems during the encounter. Importantly, most electronic medical record systems offer an automated rounding sheet. In Epic (Epic Systems Corporation), I would use the bone marrow transplant rounding sheet, which includes laboratory test results, vitals, and medications. After printing out the rounding sheet, I would note important updates for each patient. Although pre-rounding and chart review requires time and effort, it aided me in providing elevated patient care and becoming more efficient during rounds. Over time I have come to strongly appreciate the term dermatology hospitalist. Cutaneous manifestations of systemic disease require thoughtful consideration and workup.

New Patient Consultations: Must-Ask Questions

Holding the university inpatient pager can be stressful. At the University of Utah, we often carry 5 to 10 patients on our list and receive 3 to 4 new consultations a day, sometimes right before 5 pm. When receiving new consultations, it is important to obtain the whole story from the requesting provider. Some of the questions may seem obvious, but I am frequently reminded of the inefficiencies I encountered as a first-year dermatology resident. Remember to always be kind to your consulting colleagues. Dermatology is a difficult discipline, and describing rashes is no easy task. Here is my systematic approach to questions that should be asked of the requesting provider during each new patient consultation:

• What is the patient’s name, room number, and medical record number?
• Is this patient getting admitted or admitted currently?
• Is the rash the reason for admission? (This can greatly help with triaging the urgency of evaluation.)
• Is the rash painful?
• Is this patient ill?
• How would you describe the rash?

When evaluating new patients, it is crucial to remember the morphology camps. Formulating a differential diagnosis on a complex patient can be difficult; however, remembering the morphology camps of acneiform, dermal, eczematous, erythematous, subcutaneous, vasculitic, vasculopathic, and vesiculobullous lesions can be extremely helpful. Additionally, it is crucial to perform a thorough and complete skin examination on every patient. When emphasizing the importance of this, I often am reminded of a humbling moment early in my training. Our team was consulted on a patient with cellulitis and stasis dermatitis. It was a busy day, and my examination was quick and focused on the lower and upper extremities, chest, and back. The patient improved from a cutaneous standpoint and was discharged. At follow-up the next week, one of my attending providers biopsied an atypical macule on the retroauricular region, which was found to be consistent with a stage 1A melanoma. Even on the longest and most tiring hospital days, it is important to perform a full-body skin examination on each patient. You may end up saving a life.

An Organized Toolbox: What to Carry

Similar to our ophthalmology colleagues who are seen carrying around a suitcase in the hospital, I highly recommend some form of a toolbox or bag for performing inpatient biopsies (Table). Carrying around an organized bag, albeit bulky and unfashionable, has saved me numerous trips back to clinic for unexpected complications including fixing leaky vessels, closing stubborn ulcers, and coordinating sedated biopsies in the operating room.

Final Thoughts

As I near the completion of my residency journey, I hope these tips will aid budding and current dermatology residents at excelling as dermatology hospitalists during inpatient rotations. Dermatologists can make a profound impact on a variety of patients, especially when treating hospitalized patients on the clinical forefront. Our role extends beyond the skin, as cutaneous manifestations of internal disease are not uncommon.

Inpatient dermatology consultation services are becoming increasingly prevalent in hospital institutions.^1-3 Although often underutilized as a consulting service, dermatology-related admissions cost hundreds of millions of dollars for the health care system.^1,2 Misdiagnosis, prolonged hospital stays, and incorrect treatment are common results of lack of involvement by a skin expert.^1-3 The importance of consultative inpatient dermatology cannot be understated. Accreditation Council for Graduate Medical Education requirements for proficiency in dermatology residency include exposure to inpatient dermatology, and it is our duty as residents to aid our colleagues in the management and treatment of cutaneous disease.

Although exposure to inpatient dermatology varies across residency programs, nearly every dermatology resident is bound to perform a consultation and be involved in the care of a hospitalized patient. At our program at the University of Utah (Salt Lake City), we have robust inpatient exposure, and after numerous hours spent on the forefront of inpatient dermatology, I have accrued a list of specific tips and techniques that have aided me as a resident clinician.

Pre-Rounding More Thoroughly

When I started as a postgraduate year 2 (PGY-2) on the inpatient dermatology rotation, I found myself perplexed. I had learned how to round in internal medicine but was unaccustomed to the nuances of specialty rounds. My list included calciphylaxis, small vessel vasculitis, cellulitis, stasis dermatitis, toxic epidermal necrolysis, and atypical mycobacterial infection. The first few days of service were undeniably difficult due to the daily consultations, complexity of admitted patients, and need for efficiency. I sometimes overlooked important laboratory test results, medication changes, and interdisciplinary discussions that prolonged rounding. As dermatologists, we are responsible for the largest organ of the body, and it is important to approach patients in a comprehensive manner. Pre-rounding should include reviewing interdisciplinary notes, laboratory values/results, and medications, and performing a focused skin examination with a review of systems during the encounter. Importantly, most electronic medical record systems offer an automated rounding sheet. In Epic (Epic Systems Corporation), I would use the bone marrow transplant rounding sheet, which includes laboratory test results, vitals, and medications. After printing out the rounding sheet, I would note important updates for each patient. Although pre-rounding and chart review requires time and effort, it aided me in providing elevated patient care and becoming more efficient during rounds. Over time I have come to strongly appreciate the term dermatology hospitalist. Cutaneous manifestations of systemic disease require thoughtful consideration and workup.

New Patient Consultations: Must-Ask Questions

Holding the university inpatient pager can be stressful. At the University of Utah, we often carry 5 to 10 patients on our list and receive 3 to 4 new consultations a day, sometimes right before 5 pm. When receiving new consultations, it is important to obtain the whole story from the requesting provider. Some of the questions may seem obvious, but I am frequently reminded of the inefficiencies I encountered as a first-year dermatology resident. Remember to always be kind to your consulting colleagues. Dermatology is a difficult discipline, and describing rashes is no easy task. Here is my systematic approach to questions that should be asked of the requesting provider during each new patient consultation:

• What is the patient’s name, room number, and medical record number?
• Is this patient getting admitted or admitted currently?
• Is the rash the reason for admission? (This can greatly help with triaging the urgency of evaluation.)
• Is the rash painful?
• Is this patient ill?
• How would you describe the rash?

When evaluating new patients, it is crucial to remember the morphology camps. Formulating a differential diagnosis on a complex patient can be difficult; however, remembering the morphology camps of acneiform, dermal, eczematous, erythematous, subcutaneous, vasculitic, vasculopathic, and vesiculobullous lesions can be extremely helpful. Additionally, it is crucial to perform a thorough and complete skin examination on every patient. When emphasizing the importance of this, I often am reminded of a humbling moment early in my training. Our team was consulted on a patient with cellulitis and stasis dermatitis. It was a busy day, and my examination was quick and focused on the lower and upper extremities, chest, and back. The patient improved from a cutaneous standpoint and was discharged. At follow-up the next week, one of my attending providers biopsied an atypical macule on the retroauricular region, which was found to be consistent with a stage 1A melanoma. Even on the longest and most tiring hospital days, it is important to perform a full-body skin examination on each patient. You may end up saving a life.

An Organized Toolbox: What to Carry

Similar to our ophthalmology colleagues who are seen carrying around a suitcase in the hospital, I highly recommend some form of a toolbox or bag for performing inpatient biopsies (Table). Carrying around an organized bag, albeit bulky and unfashionable, has saved me numerous trips back to clinic for unexpected complications including fixing leaky vessels, closing stubborn ulcers, and coordinating sedated biopsies in the operating room.

Final Thoughts

As I near the completion of my residency journey, I hope these tips will aid budding and current dermatology residents at excelling as dermatology hospitalists during inpatient rotations. Dermatologists can make a profound impact on a variety of patients, especially when treating hospitalized patients on the clinical forefront. Our role extends beyond the skin, as cutaneous manifestations of internal disease are not uncommon.

Leaders of medical student groups and legislators in a few states are trying to convince medical schools to end a century-old practice of legacy admissions, which they say offer preferential treatment to applicants based on their association with donors or alumni.

While an estimated 25% of public colleges and universities still use legacy admissions, a growing list of top medical schools have moved away from the practice over the last decade, including Johns Hopkins University, Baltimore, and Tufts University, Medford, Mass.

Legacy admissions contradict schools’ more inclusive policies, Senila Yasmin, MPH, a second-year medical student at Tufts University, said in an interview. While Tufts maintains legacy admissions for its undergraduate applicants, the medical school stopped the practice in 2021, said Ms. Yasmin, a member of a student group that lobbied against the school’s legacy preferences.

Describing herself as a low-income, first-generation Muslim-Pakistani American, Ms. Yasmin wants to use her experience at Tufts to improve accessibility for students like herself.

As a member of the American Medical Association (AMA) Medical Student Section, she coauthored a resolution stating that legacy admissions go against the AMA’s strategic plan to advance racial justice and health equity. The Student Section passed the resolution in November, and in June, the AMA House of Delegates will vote on whether to adopt the policy. 

Along with a Supreme Court decision that could strike down race-conscious college admissions, an AMA policy could convince medical schools to rethink legacy admissions and how to maintain diverse student bodies. In June, the court is expected to issue a decision in the Students for Fair Admissions lawsuit against Harvard University, Cambridge, Mass., and the University of North Carolina, Chapel Hill, which alleges that considering race in holistic admissions constitutes racial discrimination and violates the Equal Protection Clause.

Opponents of legacy admissions, like Ms. Yasmin, say it penalizes students from racial minorities and lower socioeconomic backgrounds, hampering a fair and equitable admissions process that attracts diverse medical school admissions.
 

Diversity of medical applicants

Diversity in medical schools  continued to increase last year with more Black, Hispanic, and female students applying and enrolling, according to a recent report by the Association of American Medical Colleges (AAMC). However, universities often include nonacademic criteria in their admission assessments to improve educational access for underrepresented minorities.

Medical schools carefully consider each applicant’s background “to yield a diverse class of students,” Geoffrey Young, PhD, AAMC’s senior director of transforming the health care workforce, told this news organization.

Some schools, such as Morehouse School of Medicine, Atlanta, the University of Virginia School of Medicine, Charlottesville, and the University of Arizona College of Medicine, Tucson, perform a thorough review of candidates while offering admissions practices designed specifically for legacy applicants. The schools assert that legacy designation doesn’t factor into the student’s likelihood of acceptance.

The arrangement may show that schools want to commit to equity and fairness but have trouble moving away from entrenched traditions, two professors from Penn State College of Medicine, Hershey, Pa., who sit on separate medical admissions subcommittees, wrote last year in Bioethics Today.
 

Legislation may hasten legacies’ end

In December, Ms. Yasmin and a group of Massachusetts Medical Society student-members presented another resolution to the state medical society, which adopted it.

The society’s new policy opposes the use of legacy status in medical school admissions and supports mechanisms to eliminate its inclusion from the application process, Theodore Calianos II, MD, FACS, president of the Massachusetts Medical Society, said in an interview.

“Legacy preferences limit racial and socioeconomic diversity on campuses, so we asked, ‘What can we do so that everyone has equal access to medical education?’ It is exciting to see the students and young physicians – the future of medicine – become involved in policymaking.”

Proposed laws may also hasten the end of legacy admissions. Last year, the U.S. Senate began considering a bill prohibiting colleges receiving federal financial aid from giving preferential treatment to students based on their relations to donors or alumni. However, the bill allows the Department of Education to make exceptions for institutions serving historically underrepresented groups.

The New York State Senate and the New York State Assembly also are reviewing bills that ban legacy and early admissions policies at public and private universities. Connecticut announced similar legislation last year. Massachusetts legislators are considering two bills: one that would ban the practice at the state’s public universities and another that would require all schools using legacy status to pay a “public service fee” equal to a percentage of its endowment. Colleges with endowment assets exceeding $2 billion must pay at least $2 million, according to the bill’s text.

At schools like Harvard,  whose endowment surpasses $50 billion, the option to pay the penalty will make the law moot, Michael Walls, DO, MPH, president of the American Medical Student Association (AMSA), said in an interview. “Smaller schools wouldn’t be able to afford the fine and are less likely to be doing [legacy admissions] anyway,” he said. “The schools that want to continue doing it could just pay the fine.”

Dr. Walls said AMSA supports race-conscious admissions processes and anything that increases fairness for medical school applicants. “Whatever [fair] means is up for interpretation, but it would be great to eliminate legacy admissions,” he said.   
 

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

Leaders of medical student groups and legislators in a few states are trying to convince medical schools to end a century-old practice of legacy admissions, which they say offer preferential treatment to applicants based on their association with donors or alumni.

While an estimated 25% of public colleges and universities still use legacy admissions, a growing list of top medical schools have moved away from the practice over the last decade, including Johns Hopkins University, Baltimore, and Tufts University, Medford, Mass.

Legacy admissions contradict schools’ more inclusive policies, Senila Yasmin, MPH, a second-year medical student at Tufts University, said in an interview. While Tufts maintains legacy admissions for its undergraduate applicants, the medical school stopped the practice in 2021, said Ms. Yasmin, a member of a student group that lobbied against the school’s legacy preferences.

Describing herself as a low-income, first-generation Muslim-Pakistani American, Ms. Yasmin wants to use her experience at Tufts to improve accessibility for students like herself.

As a member of the American Medical Association (AMA) Medical Student Section, she coauthored a resolution stating that legacy admissions go against the AMA’s strategic plan to advance racial justice and health equity. The Student Section passed the resolution in November, and in June, the AMA House of Delegates will vote on whether to adopt the policy. 

Along with a Supreme Court decision that could strike down race-conscious college admissions, an AMA policy could convince medical schools to rethink legacy admissions and how to maintain diverse student bodies. In June, the court is expected to issue a decision in the Students for Fair Admissions lawsuit against Harvard University, Cambridge, Mass., and the University of North Carolina, Chapel Hill, which alleges that considering race in holistic admissions constitutes racial discrimination and violates the Equal Protection Clause.

Opponents of legacy admissions, like Ms. Yasmin, say it penalizes students from racial minorities and lower socioeconomic backgrounds, hampering a fair and equitable admissions process that attracts diverse medical school admissions.
 

Diversity of medical applicants

Diversity in medical schools  continued to increase last year with more Black, Hispanic, and female students applying and enrolling, according to a recent report by the Association of American Medical Colleges (AAMC). However, universities often include nonacademic criteria in their admission assessments to improve educational access for underrepresented minorities.

Medical schools carefully consider each applicant’s background “to yield a diverse class of students,” Geoffrey Young, PhD, AAMC’s senior director of transforming the health care workforce, told this news organization.

Some schools, such as Morehouse School of Medicine, Atlanta, the University of Virginia School of Medicine, Charlottesville, and the University of Arizona College of Medicine, Tucson, perform a thorough review of candidates while offering admissions practices designed specifically for legacy applicants. The schools assert that legacy designation doesn’t factor into the student’s likelihood of acceptance.

The arrangement may show that schools want to commit to equity and fairness but have trouble moving away from entrenched traditions, two professors from Penn State College of Medicine, Hershey, Pa., who sit on separate medical admissions subcommittees, wrote last year in Bioethics Today.
 

Legislation may hasten legacies’ end

In December, Ms. Yasmin and a group of Massachusetts Medical Society student-members presented another resolution to the state medical society, which adopted it.

The society’s new policy opposes the use of legacy status in medical school admissions and supports mechanisms to eliminate its inclusion from the application process, Theodore Calianos II, MD, FACS, president of the Massachusetts Medical Society, said in an interview.

“Legacy preferences limit racial and socioeconomic diversity on campuses, so we asked, ‘What can we do so that everyone has equal access to medical education?’ It is exciting to see the students and young physicians – the future of medicine – become involved in policymaking.”

Proposed laws may also hasten the end of legacy admissions. Last year, the U.S. Senate began considering a bill prohibiting colleges receiving federal financial aid from giving preferential treatment to students based on their relations to donors or alumni. However, the bill allows the Department of Education to make exceptions for institutions serving historically underrepresented groups.

The New York State Senate and the New York State Assembly also are reviewing bills that ban legacy and early admissions policies at public and private universities. Connecticut announced similar legislation last year. Massachusetts legislators are considering two bills: one that would ban the practice at the state’s public universities and another that would require all schools using legacy status to pay a “public service fee” equal to a percentage of its endowment. Colleges with endowment assets exceeding $2 billion must pay at least $2 million, according to the bill’s text.

At schools like Harvard,  whose endowment surpasses $50 billion, the option to pay the penalty will make the law moot, Michael Walls, DO, MPH, president of the American Medical Student Association (AMSA), said in an interview. “Smaller schools wouldn’t be able to afford the fine and are less likely to be doing [legacy admissions] anyway,” he said. “The schools that want to continue doing it could just pay the fine.”

Dr. Walls said AMSA supports race-conscious admissions processes and anything that increases fairness for medical school applicants. “Whatever [fair] means is up for interpretation, but it would be great to eliminate legacy admissions,” he said.   
 

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

Leaders of medical student groups and legislators in a few states are trying to convince medical schools to end a century-old practice of legacy admissions, which they say offer preferential treatment to applicants based on their association with donors or alumni.

While an estimated 25% of public colleges and universities still use legacy admissions, a growing list of top medical schools have moved away from the practice over the last decade, including Johns Hopkins University, Baltimore, and Tufts University, Medford, Mass.

Legacy admissions contradict schools’ more inclusive policies, Senila Yasmin, MPH, a second-year medical student at Tufts University, said in an interview. While Tufts maintains legacy admissions for its undergraduate applicants, the medical school stopped the practice in 2021, said Ms. Yasmin, a member of a student group that lobbied against the school’s legacy preferences.

Describing herself as a low-income, first-generation Muslim-Pakistani American, Ms. Yasmin wants to use her experience at Tufts to improve accessibility for students like herself.

As a member of the American Medical Association (AMA) Medical Student Section, she coauthored a resolution stating that legacy admissions go against the AMA’s strategic plan to advance racial justice and health equity. The Student Section passed the resolution in November, and in June, the AMA House of Delegates will vote on whether to adopt the policy. 

Along with a Supreme Court decision that could strike down race-conscious college admissions, an AMA policy could convince medical schools to rethink legacy admissions and how to maintain diverse student bodies. In June, the court is expected to issue a decision in the Students for Fair Admissions lawsuit against Harvard University, Cambridge, Mass., and the University of North Carolina, Chapel Hill, which alleges that considering race in holistic admissions constitutes racial discrimination and violates the Equal Protection Clause.

Opponents of legacy admissions, like Ms. Yasmin, say it penalizes students from racial minorities and lower socioeconomic backgrounds, hampering a fair and equitable admissions process that attracts diverse medical school admissions.
 

Diversity of medical applicants

Diversity in medical schools  continued to increase last year with more Black, Hispanic, and female students applying and enrolling, according to a recent report by the Association of American Medical Colleges (AAMC). However, universities often include nonacademic criteria in their admission assessments to improve educational access for underrepresented minorities.

Medical schools carefully consider each applicant’s background “to yield a diverse class of students,” Geoffrey Young, PhD, AAMC’s senior director of transforming the health care workforce, told this news organization.

Some schools, such as Morehouse School of Medicine, Atlanta, the University of Virginia School of Medicine, Charlottesville, and the University of Arizona College of Medicine, Tucson, perform a thorough review of candidates while offering admissions practices designed specifically for legacy applicants. The schools assert that legacy designation doesn’t factor into the student’s likelihood of acceptance.

The arrangement may show that schools want to commit to equity and fairness but have trouble moving away from entrenched traditions, two professors from Penn State College of Medicine, Hershey, Pa., who sit on separate medical admissions subcommittees, wrote last year in Bioethics Today.
 

Legislation may hasten legacies’ end

In December, Ms. Yasmin and a group of Massachusetts Medical Society student-members presented another resolution to the state medical society, which adopted it.

The society’s new policy opposes the use of legacy status in medical school admissions and supports mechanisms to eliminate its inclusion from the application process, Theodore Calianos II, MD, FACS, president of the Massachusetts Medical Society, said in an interview.

“Legacy preferences limit racial and socioeconomic diversity on campuses, so we asked, ‘What can we do so that everyone has equal access to medical education?’ It is exciting to see the students and young physicians – the future of medicine – become involved in policymaking.”

Proposed laws may also hasten the end of legacy admissions. Last year, the U.S. Senate began considering a bill prohibiting colleges receiving federal financial aid from giving preferential treatment to students based on their relations to donors or alumni. However, the bill allows the Department of Education to make exceptions for institutions serving historically underrepresented groups.

The New York State Senate and the New York State Assembly also are reviewing bills that ban legacy and early admissions policies at public and private universities. Connecticut announced similar legislation last year. Massachusetts legislators are considering two bills: one that would ban the practice at the state’s public universities and another that would require all schools using legacy status to pay a “public service fee” equal to a percentage of its endowment. Colleges with endowment assets exceeding $2 billion must pay at least $2 million, according to the bill’s text.

At schools like Harvard,  whose endowment surpasses $50 billion, the option to pay the penalty will make the law moot, Michael Walls, DO, MPH, president of the American Medical Student Association (AMSA), said in an interview. “Smaller schools wouldn’t be able to afford the fine and are less likely to be doing [legacy admissions] anyway,” he said. “The schools that want to continue doing it could just pay the fine.”

Dr. Walls said AMSA supports race-conscious admissions processes and anything that increases fairness for medical school applicants. “Whatever [fair] means is up for interpretation, but it would be great to eliminate legacy admissions,” he said.   
 

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

As the cost of malpractice insurance continues to increase in many states, physicians in private practice may want to take advantage of discounts insurers offer to reduce premiums.

Getting a better deal might simply mean taking advantage of incentives and discounts your insurer may already offer. These include claims-free, new-to-practice, and working part-time discounts.

However, if you decide to shop around, keep in mind that discounts are just one factor that can affect your premium price – insurers look at your specialty, location, and claims history.

One of the most common ways physicians can earn discounts is by participating in risk management programs. With this type of program, physicians evaluate elements of their practice and documentation practices and identify areas that might leave them at risk for a lawsuit. While they save money, physician risk management programs also are designed to reduce malpractice claims, which ultimately minimizes the potential for bigger financial losses, insurance experts say.

“It’s a win-win situation when liability insurers and physicians work together to minimize risk, and it’s a win for patients,” said Gary Price, MD, president of The Physicians Foundation.

Doctors in private practice or employed by small hospitals that are not self-insured can qualify for these discounts, said David Zetter, president of Zetter HealthCare Management Consultants.

“I do a lot of work with medical malpractice companies trying to find clients policies. All the carriers are transparent about what physicians have to do to lower their premiums. Physicians can receive the discounts if they follow through and meet the insurer’s requirements,” said Mr. Zetter.

State insurance departments regulate medical malpractice insurance, including the premium credits insurers offer. Most states cap discounts at 25%, but some go as high as 70%, according to The Doctors Company, a national physician-owned medical malpractice insurer.

Insurers typically offer doctors several ways to earn discounts. The size of the discount also can depend on whether a doctor is new to a practice, remains claims free, or takes risk management courses.

In addition to the premium discount, some online risk management classes and webinars are eligible for CME credits.

“The credits can add up and they can be used for recertification or relicensure,” said Susan Boisvert, senior patient safety risk manager at The Doctors Company.

Here are five ways you may qualify for discounts with your insurer.

1. Make use of discounts available to new doctors

Doctors can earn hefty discounts on their premiums when they are no longer interns or residents and start practicing medicine. The Doctors Company usually gives a 50% discount on member premiums the first year they’re in practice and a 25% discount credit in their second year. The discounts end after that.  

Other insurance carriers offer similar discounts to doctors starting to practice medicine. The deepest one is offered in the first year (at least 50%) and a smaller one (20%-25%) the second year, according to medical malpractice brokers.

“The new-to-practice discount is based solely on when the physician left their formal training to begin their practice for the first time; it is not based on claim-free history,” explained Mr. Zetter.

This is a very common discount used by different insurer carriers, said Dr. Price. “New physicians don’t have the same amount of risk of a lawsuit when they’re starting out. It’s unlikely they will have a claim and most liability actions have a 2-year time limit from the date of injury to be filed.”

2. Take advantage of being claims free

If you’ve been claims free for at least a few years, you may be eligible for a large discount.

“Doctors without claims are a better risk. Once a doctor has one claim, they’re likely to have a second, which the research shows,” said Mr. Zetter.

The most common credit The Doctors Company offers is 3 years of being claim free – this earns doctors up to 25%, he said. Mr. Zetter explained that the criteria and size of The Doctors Company credit may depend on the state where physicians practice.

“We allowed insurance carriers that we acquired to continue with their own claim-free discount program such as Florida’s First Professionals Insurance Company we acquired in 2011,” he said.

Doctors with other medical malpractice insurers may also be eligible for a credit up to 25%. In some instances, they may have to be claims free for 5 or 10 years, say insurance experts.

It pays to shop around before purchasing insurance.

3. If you work part time, make sure your premium reflects that

Physicians who see patients part time can receive up to a 75% discount on their medical liability insurance premiums.

The discounts are based on the hours the physician works per week. The fewer hours worked, the larger the discount. This type of discount does not vary by specialty.

According to The Doctors Company, working 10 hours or less per week may entitle doctors to a 75% discount; working 11-20 hours per week may entitle them to a 50% discount, and working 21-30 hours per week may entitle them to a 25% discount. If you are in this situation, it pays to ask your insurer if there is a discount available to you.

4. Look into your professional medical society insurance company

“I would look at your state medical association [or] state specialty society and talk to your colleagues to learn what premiums they’re paying and about any discounts they’re getting,” advised Mr. Zetter.

Some state medical societies have formed their own liability companies and offer lower premiums to their members because “they’re organized and managed by doctors, which makes their premiums more competitive,” Dr. Price said.

Other state medical societies endorse specific insurance carriers and offer their members a 5% discount for enrolling with them.

5. Enroll in a risk management program

Most insurers offer online educational activities designed to improve patient safety and reduce the risk of a lawsuit. Physicians may be eligible for both premium discounts and CME credits.

Medical Liability Mutual Insurance Company, owned by Berkshire Hathaway, operates in New York and offers physicians a premium discount of up to 5%, CME credit, and maintenance of certification credit for successfully completing its risk management program every other year.

ProAssurance members nationwide can earn 5% in premium discounts if they complete a 2-hour video series called “Back to Basics: Loss Prevention and Navigating Everyday Risks: Using Data to Drive Change.”

They can earn one credit for completing each webinar on topics such as “Medication Management: Minimizing Errors and Improving Safety” and “Opioid Prescribing: Keeping Patients Safe.”

MagMutual offers its insured physicians 1 CME credit for completing their specialty’s risk assessment and courses, which may be applied toward their premium discounts.

The Doctors Company offers its members a 5% premium discount if they complete 4 CME credits. One of its most popular courses is “How To Get Rid of a Difficult Patient.”

“Busy residents like the shorter case studies worth one-quarter credit that they can complete in 15 minutes,” said Ms. Boisvert.

“This is a good bargain from the physician’s standpoint and the fact that risk management education is offered online makes it a lot easier than going to a seminar in person,” said Dr. Price.

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

As the cost of malpractice insurance continues to increase in many states, physicians in private practice may want to take advantage of discounts insurers offer to reduce premiums.

Getting a better deal might simply mean taking advantage of incentives and discounts your insurer may already offer. These include claims-free, new-to-practice, and working part-time discounts.

However, if you decide to shop around, keep in mind that discounts are just one factor that can affect your premium price – insurers look at your specialty, location, and claims history.

One of the most common ways physicians can earn discounts is by participating in risk management programs. With this type of program, physicians evaluate elements of their practice and documentation practices and identify areas that might leave them at risk for a lawsuit. While they save money, physician risk management programs also are designed to reduce malpractice claims, which ultimately minimizes the potential for bigger financial losses, insurance experts say.

“It’s a win-win situation when liability insurers and physicians work together to minimize risk, and it’s a win for patients,” said Gary Price, MD, president of The Physicians Foundation.

Doctors in private practice or employed by small hospitals that are not self-insured can qualify for these discounts, said David Zetter, president of Zetter HealthCare Management Consultants.

“I do a lot of work with medical malpractice companies trying to find clients policies. All the carriers are transparent about what physicians have to do to lower their premiums. Physicians can receive the discounts if they follow through and meet the insurer’s requirements,” said Mr. Zetter.

State insurance departments regulate medical malpractice insurance, including the premium credits insurers offer. Most states cap discounts at 25%, but some go as high as 70%, according to The Doctors Company, a national physician-owned medical malpractice insurer.

Insurers typically offer doctors several ways to earn discounts. The size of the discount also can depend on whether a doctor is new to a practice, remains claims free, or takes risk management courses.

In addition to the premium discount, some online risk management classes and webinars are eligible for CME credits.

“The credits can add up and they can be used for recertification or relicensure,” said Susan Boisvert, senior patient safety risk manager at The Doctors Company.

Here are five ways you may qualify for discounts with your insurer.

1. Make use of discounts available to new doctors

Doctors can earn hefty discounts on their premiums when they are no longer interns or residents and start practicing medicine. The Doctors Company usually gives a 50% discount on member premiums the first year they’re in practice and a 25% discount credit in their second year. The discounts end after that.  

Other insurance carriers offer similar discounts to doctors starting to practice medicine. The deepest one is offered in the first year (at least 50%) and a smaller one (20%-25%) the second year, according to medical malpractice brokers.

“The new-to-practice discount is based solely on when the physician left their formal training to begin their practice for the first time; it is not based on claim-free history,” explained Mr. Zetter.

This is a very common discount used by different insurer carriers, said Dr. Price. “New physicians don’t have the same amount of risk of a lawsuit when they’re starting out. It’s unlikely they will have a claim and most liability actions have a 2-year time limit from the date of injury to be filed.”

2. Take advantage of being claims free

If you’ve been claims free for at least a few years, you may be eligible for a large discount.

“Doctors without claims are a better risk. Once a doctor has one claim, they’re likely to have a second, which the research shows,” said Mr. Zetter.

The most common credit The Doctors Company offers is 3 years of being claim free – this earns doctors up to 25%, he said. Mr. Zetter explained that the criteria and size of The Doctors Company credit may depend on the state where physicians practice.

“We allowed insurance carriers that we acquired to continue with their own claim-free discount program such as Florida’s First Professionals Insurance Company we acquired in 2011,” he said.

Doctors with other medical malpractice insurers may also be eligible for a credit up to 25%. In some instances, they may have to be claims free for 5 or 10 years, say insurance experts.

It pays to shop around before purchasing insurance.

3. If you work part time, make sure your premium reflects that

Physicians who see patients part time can receive up to a 75% discount on their medical liability insurance premiums.

The discounts are based on the hours the physician works per week. The fewer hours worked, the larger the discount. This type of discount does not vary by specialty.

According to The Doctors Company, working 10 hours or less per week may entitle doctors to a 75% discount; working 11-20 hours per week may entitle them to a 50% discount, and working 21-30 hours per week may entitle them to a 25% discount. If you are in this situation, it pays to ask your insurer if there is a discount available to you.

4. Look into your professional medical society insurance company

“I would look at your state medical association [or] state specialty society and talk to your colleagues to learn what premiums they’re paying and about any discounts they’re getting,” advised Mr. Zetter.

Some state medical societies have formed their own liability companies and offer lower premiums to their members because “they’re organized and managed by doctors, which makes their premiums more competitive,” Dr. Price said.

Other state medical societies endorse specific insurance carriers and offer their members a 5% discount for enrolling with them.

5. Enroll in a risk management program

Most insurers offer online educational activities designed to improve patient safety and reduce the risk of a lawsuit. Physicians may be eligible for both premium discounts and CME credits.

Medical Liability Mutual Insurance Company, owned by Berkshire Hathaway, operates in New York and offers physicians a premium discount of up to 5%, CME credit, and maintenance of certification credit for successfully completing its risk management program every other year.

ProAssurance members nationwide can earn 5% in premium discounts if they complete a 2-hour video series called “Back to Basics: Loss Prevention and Navigating Everyday Risks: Using Data to Drive Change.”

They can earn one credit for completing each webinar on topics such as “Medication Management: Minimizing Errors and Improving Safety” and “Opioid Prescribing: Keeping Patients Safe.”

MagMutual offers its insured physicians 1 CME credit for completing their specialty’s risk assessment and courses, which may be applied toward their premium discounts.

The Doctors Company offers its members a 5% premium discount if they complete 4 CME credits. One of its most popular courses is “How To Get Rid of a Difficult Patient.”

“Busy residents like the shorter case studies worth one-quarter credit that they can complete in 15 minutes,” said Ms. Boisvert.

“This is a good bargain from the physician’s standpoint and the fact that risk management education is offered online makes it a lot easier than going to a seminar in person,” said Dr. Price.

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

As the cost of malpractice insurance continues to increase in many states, physicians in private practice may want to take advantage of discounts insurers offer to reduce premiums.

Getting a better deal might simply mean taking advantage of incentives and discounts your insurer may already offer. These include claims-free, new-to-practice, and working part-time discounts.

However, if you decide to shop around, keep in mind that discounts are just one factor that can affect your premium price – insurers look at your specialty, location, and claims history.

One of the most common ways physicians can earn discounts is by participating in risk management programs. With this type of program, physicians evaluate elements of their practice and documentation practices and identify areas that might leave them at risk for a lawsuit. While they save money, physician risk management programs also are designed to reduce malpractice claims, which ultimately minimizes the potential for bigger financial losses, insurance experts say.

“It’s a win-win situation when liability insurers and physicians work together to minimize risk, and it’s a win for patients,” said Gary Price, MD, president of The Physicians Foundation.

Doctors in private practice or employed by small hospitals that are not self-insured can qualify for these discounts, said David Zetter, president of Zetter HealthCare Management Consultants.

“I do a lot of work with medical malpractice companies trying to find clients policies. All the carriers are transparent about what physicians have to do to lower their premiums. Physicians can receive the discounts if they follow through and meet the insurer’s requirements,” said Mr. Zetter.

State insurance departments regulate medical malpractice insurance, including the premium credits insurers offer. Most states cap discounts at 25%, but some go as high as 70%, according to The Doctors Company, a national physician-owned medical malpractice insurer.

Insurers typically offer doctors several ways to earn discounts. The size of the discount also can depend on whether a doctor is new to a practice, remains claims free, or takes risk management courses.

In addition to the premium discount, some online risk management classes and webinars are eligible for CME credits.

“The credits can add up and they can be used for recertification or relicensure,” said Susan Boisvert, senior patient safety risk manager at The Doctors Company.

Here are five ways you may qualify for discounts with your insurer.

1. Make use of discounts available to new doctors

Doctors can earn hefty discounts on their premiums when they are no longer interns or residents and start practicing medicine. The Doctors Company usually gives a 50% discount on member premiums the first year they’re in practice and a 25% discount credit in their second year. The discounts end after that.  

Other insurance carriers offer similar discounts to doctors starting to practice medicine. The deepest one is offered in the first year (at least 50%) and a smaller one (20%-25%) the second year, according to medical malpractice brokers.

“The new-to-practice discount is based solely on when the physician left their formal training to begin their practice for the first time; it is not based on claim-free history,” explained Mr. Zetter.

This is a very common discount used by different insurer carriers, said Dr. Price. “New physicians don’t have the same amount of risk of a lawsuit when they’re starting out. It’s unlikely they will have a claim and most liability actions have a 2-year time limit from the date of injury to be filed.”

2. Take advantage of being claims free

If you’ve been claims free for at least a few years, you may be eligible for a large discount.

“Doctors without claims are a better risk. Once a doctor has one claim, they’re likely to have a second, which the research shows,” said Mr. Zetter.

The most common credit The Doctors Company offers is 3 years of being claim free – this earns doctors up to 25%, he said. Mr. Zetter explained that the criteria and size of The Doctors Company credit may depend on the state where physicians practice.

“We allowed insurance carriers that we acquired to continue with their own claim-free discount program such as Florida’s First Professionals Insurance Company we acquired in 2011,” he said.

Doctors with other medical malpractice insurers may also be eligible for a credit up to 25%. In some instances, they may have to be claims free for 5 or 10 years, say insurance experts.

It pays to shop around before purchasing insurance.

3. If you work part time, make sure your premium reflects that

Physicians who see patients part time can receive up to a 75% discount on their medical liability insurance premiums.

The discounts are based on the hours the physician works per week. The fewer hours worked, the larger the discount. This type of discount does not vary by specialty.

According to The Doctors Company, working 10 hours or less per week may entitle doctors to a 75% discount; working 11-20 hours per week may entitle them to a 50% discount, and working 21-30 hours per week may entitle them to a 25% discount. If you are in this situation, it pays to ask your insurer if there is a discount available to you.

4. Look into your professional medical society insurance company

“I would look at your state medical association [or] state specialty society and talk to your colleagues to learn what premiums they’re paying and about any discounts they’re getting,” advised Mr. Zetter.

Some state medical societies have formed their own liability companies and offer lower premiums to their members because “they’re organized and managed by doctors, which makes their premiums more competitive,” Dr. Price said.

Other state medical societies endorse specific insurance carriers and offer their members a 5% discount for enrolling with them.

5. Enroll in a risk management program

Most insurers offer online educational activities designed to improve patient safety and reduce the risk of a lawsuit. Physicians may be eligible for both premium discounts and CME credits.

Medical Liability Mutual Insurance Company, owned by Berkshire Hathaway, operates in New York and offers physicians a premium discount of up to 5%, CME credit, and maintenance of certification credit for successfully completing its risk management program every other year.

ProAssurance members nationwide can earn 5% in premium discounts if they complete a 2-hour video series called “Back to Basics: Loss Prevention and Navigating Everyday Risks: Using Data to Drive Change.”

They can earn one credit for completing each webinar on topics such as “Medication Management: Minimizing Errors and Improving Safety” and “Opioid Prescribing: Keeping Patients Safe.”

MagMutual offers its insured physicians 1 CME credit for completing their specialty’s risk assessment and courses, which may be applied toward their premium discounts.

The Doctors Company offers its members a 5% premium discount if they complete 4 CME credits. One of its most popular courses is “How To Get Rid of a Difficult Patient.”

“Busy residents like the shorter case studies worth one-quarter credit that they can complete in 15 minutes,” said Ms. Boisvert.

“This is a good bargain from the physician’s standpoint and the fact that risk management education is offered online makes it a lot easier than going to a seminar in person,” said Dr. Price.

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

Communities with easy access to fast food were 77% more likely to have high levels of obesity-related cancer mortality, based on data from a new cross-sectional study of more than 3,000 communities.

Although increased healthy eating has been associated with reduced risk of obesity and with reduced cancer incidence and mortality, access to healthier eating remains a challenge in communities with less access to grocery stores and healthy food options (food deserts) and/or easy access to convenience stores and fast food (food swamps), Malcolm Seth Bevel, PhD, of the Medical College of Georgia, Augusta, and colleagues, wrote in their paper, published in JAMA Oncology.

In addition, data on the association between food deserts and swamps and obesity-related cancer mortality are limited, they said.

“We felt that the study was important given the fact that obesity is an epidemic in the United States, and multiple factors contribute to obesity, especially adverse food environments,” Dr. Bevel said in an interview. “Also, I lived in these areas my whole life, and saw how it affected underserved populations. There was a story that needed to be told, so we’re telling it,” he said in an interview.

In a study, the researchers analyzed food access and cancer mortality data from 3,038 counties across the United States. The food access data came from the U.S. Department of Agriculture Food Environment Atlas (FEA) for the years 2012, 2014, 2015, 2017, and 2020. Data on obesity-related cancer mortality came from the Centers for Disease Control and Prevention for the years from 2010 to 2020.

Food desert scores were calculated through data from the FEA, and food swamp scores were based on the ratio of fast-food restaurants and convenience stores to grocery stores and farmers markets in a modification of the Retail Food Environment Index score.

The researchers used an age-adjusted, multiple regression model to determine the association between food desert and food swamp scores and obesity-related cancer mortality rates. Higher food swamp and food desert scores (defined as 20.0 to 58.0 or higher) were used to classify counties as having fewer healthy food resources. The primary outcome was obesity-related cancer mortality, defined as high or low (71.8 or higher per 100,000 individuals and less than 71.8 per 100,000 individuals, respectively).

Overall, high rates of obesity-related cancer mortality were 77% more likely in the counties that met the criteria for high food swamp scores (adjusted odds ratio 1.77). In addition, researchers found a positive dose-response relationship among three levels of both food desert scores and food swamp scores and obesity-related cancer mortality.

A total of 758 counties had obesity-related cancer mortality rates in the highest quartile. Compared to counties with low rates of obesity-related cancer mortality, counties with high rates of obesity-related cancer mortality also had a higher percentage of non-Hispanic Black residents (3.26% vs. 1.77%), higher percentage of adults older than 65 years (15.71% vs. 15.40%), higher rates of adult obesity (33.0% vs. 32.10%), and higher rates of adult diabetes (12.50% vs. 10.70%).

Possible explanations for the results include the lack of interest in grocery stores in neighborhoods with a population with a lower socioeconomic status, which can create a food desert, the researchers wrote in their discussion. “Coupled with the increasing growth rate of fast-food restaurants in recent years and the intentional advertisement of unhealthy foods in urban neighborhoods with [people of lower income], the food desert may transform into a food swamp,” they said.

The findings were limited by several factors including the study design, which did not allow for showing a causal association of food deserts and food swamps with obesity-related cancer mortality, the researchers noted. Other limitations included the use of groups rather than individuals, the potential misclassification of food stores, and the use of county-level data on race, ethnicity, and income, they wrote.

The results indicate that “food swamps appear to be a growing epidemic across the U.S., likely because of systemic issues, and should draw concern and conversation from local and state officials,” the researchers concluded.
 

Community-level investments can benefit individual health

Dr. Bevel said he was not surprised by the findings, as he has seen firsthand the lack of healthy food options and growth of unhealthy food options, especially for certain populations in certain communities. “Typically, these are people who have lower socioeconomic status, primarily non-Hispanic Black or African American or Hispanic American,” he said “I have watched people have to choose between getting fruits/vegetables versus their medications or running to fast food places to feed their families. What is truly surprising is that we’re not talking about people’s lived environment enough for my taste,” he said.  

“I hope that our data and results can inform local and state policymakers to truly invest in all communities, such as funding for community gardens, and realize that adverse food environments, including the barriers in navigating these environments, have significant consequences on real people,” said Dr. Bevel. “Also, I hope that the results can help clinicians realize that a patient’s lived environment can truly affect their obesity and/or obesity-related cancer status; being cognizant of that is the first step in holistic, comprehensive care,” he said. 

“One role that oncologists might be able to play in improving patients’ access to healthier food is to create and/or implement healthy lifestyle programs with gardening components to combat the poorest food environments that their patients likely reside in,” said Dr. Bevel. Clinicians also could consider the innovative approach of “food prescriptions” to help reduce the effects of deprived, built environments, he noted.

Looking ahead, next steps for research include determining the severity of association between food swamps and obesity-related cancer by varying factors such as cancer type, and examining any potential racial disparities between people living in these environments and obesity-related cancer, Dr. Bevel added.
 

Data provide foundation for multilevel interventions

The current study findings “raise a clarion call to elevate the discussion on food availability and access to ensure an equitable emphasis on both the importance of lifestyle factors and the upstream structural, economic, and environmental contexts that shape these behaviors at the individual level,” Karriem S. Watson, DHSc, MS, MPH, of the National Institutes of Health, Bethesda, Md., and Angela Odoms-Young, PhD, of Cornell University, Ithaca, N.Y., wrote in an accompanying editorial.

The findings provide a foundation for studies of obesity-related cancer outcomes that take the community environment into consideration, they added.

The causes of both obesity and cancer are complex, and the study findings suggest that the links between unhealthy food environments and obesity-related cancer may go beyond dietary consumption alone and extend to social and psychological factors, the editorialists noted.

“Whether dealing with the lack of access to healthy foods or an overabundance of unhealthy food, there is a critical need to develop additional research that explores the associations between obesity-related cancer mortality and food inequities,” they concluded.

The study received no outside funding. The researchers and the editorialists had no financial conflicts to disclose.

Communities with easy access to fast food were 77% more likely to have high levels of obesity-related cancer mortality, based on data from a new cross-sectional study of more than 3,000 communities.

Although increased healthy eating has been associated with reduced risk of obesity and with reduced cancer incidence and mortality, access to healthier eating remains a challenge in communities with less access to grocery stores and healthy food options (food deserts) and/or easy access to convenience stores and fast food (food swamps), Malcolm Seth Bevel, PhD, of the Medical College of Georgia, Augusta, and colleagues, wrote in their paper, published in JAMA Oncology.

In addition, data on the association between food deserts and swamps and obesity-related cancer mortality are limited, they said.

“We felt that the study was important given the fact that obesity is an epidemic in the United States, and multiple factors contribute to obesity, especially adverse food environments,” Dr. Bevel said in an interview. “Also, I lived in these areas my whole life, and saw how it affected underserved populations. There was a story that needed to be told, so we’re telling it,” he said in an interview.

In a study, the researchers analyzed food access and cancer mortality data from 3,038 counties across the United States. The food access data came from the U.S. Department of Agriculture Food Environment Atlas (FEA) for the years 2012, 2014, 2015, 2017, and 2020. Data on obesity-related cancer mortality came from the Centers for Disease Control and Prevention for the years from 2010 to 2020.

Food desert scores were calculated through data from the FEA, and food swamp scores were based on the ratio of fast-food restaurants and convenience stores to grocery stores and farmers markets in a modification of the Retail Food Environment Index score.

The researchers used an age-adjusted, multiple regression model to determine the association between food desert and food swamp scores and obesity-related cancer mortality rates. Higher food swamp and food desert scores (defined as 20.0 to 58.0 or higher) were used to classify counties as having fewer healthy food resources. The primary outcome was obesity-related cancer mortality, defined as high or low (71.8 or higher per 100,000 individuals and less than 71.8 per 100,000 individuals, respectively).

Overall, high rates of obesity-related cancer mortality were 77% more likely in the counties that met the criteria for high food swamp scores (adjusted odds ratio 1.77). In addition, researchers found a positive dose-response relationship among three levels of both food desert scores and food swamp scores and obesity-related cancer mortality.

A total of 758 counties had obesity-related cancer mortality rates in the highest quartile. Compared to counties with low rates of obesity-related cancer mortality, counties with high rates of obesity-related cancer mortality also had a higher percentage of non-Hispanic Black residents (3.26% vs. 1.77%), higher percentage of adults older than 65 years (15.71% vs. 15.40%), higher rates of adult obesity (33.0% vs. 32.10%), and higher rates of adult diabetes (12.50% vs. 10.70%).

Possible explanations for the results include the lack of interest in grocery stores in neighborhoods with a population with a lower socioeconomic status, which can create a food desert, the researchers wrote in their discussion. “Coupled with the increasing growth rate of fast-food restaurants in recent years and the intentional advertisement of unhealthy foods in urban neighborhoods with [people of lower income], the food desert may transform into a food swamp,” they said.

The findings were limited by several factors including the study design, which did not allow for showing a causal association of food deserts and food swamps with obesity-related cancer mortality, the researchers noted. Other limitations included the use of groups rather than individuals, the potential misclassification of food stores, and the use of county-level data on race, ethnicity, and income, they wrote.

The results indicate that “food swamps appear to be a growing epidemic across the U.S., likely because of systemic issues, and should draw concern and conversation from local and state officials,” the researchers concluded.
 

Community-level investments can benefit individual health

Dr. Bevel said he was not surprised by the findings, as he has seen firsthand the lack of healthy food options and growth of unhealthy food options, especially for certain populations in certain communities. “Typically, these are people who have lower socioeconomic status, primarily non-Hispanic Black or African American or Hispanic American,” he said “I have watched people have to choose between getting fruits/vegetables versus their medications or running to fast food places to feed their families. What is truly surprising is that we’re not talking about people’s lived environment enough for my taste,” he said.  

“I hope that our data and results can inform local and state policymakers to truly invest in all communities, such as funding for community gardens, and realize that adverse food environments, including the barriers in navigating these environments, have significant consequences on real people,” said Dr. Bevel. “Also, I hope that the results can help clinicians realize that a patient’s lived environment can truly affect their obesity and/or obesity-related cancer status; being cognizant of that is the first step in holistic, comprehensive care,” he said. 

“One role that oncologists might be able to play in improving patients’ access to healthier food is to create and/or implement healthy lifestyle programs with gardening components to combat the poorest food environments that their patients likely reside in,” said Dr. Bevel. Clinicians also could consider the innovative approach of “food prescriptions” to help reduce the effects of deprived, built environments, he noted.

Looking ahead, next steps for research include determining the severity of association between food swamps and obesity-related cancer by varying factors such as cancer type, and examining any potential racial disparities between people living in these environments and obesity-related cancer, Dr. Bevel added.
 

Data provide foundation for multilevel interventions

The current study findings “raise a clarion call to elevate the discussion on food availability and access to ensure an equitable emphasis on both the importance of lifestyle factors and the upstream structural, economic, and environmental contexts that shape these behaviors at the individual level,” Karriem S. Watson, DHSc, MS, MPH, of the National Institutes of Health, Bethesda, Md., and Angela Odoms-Young, PhD, of Cornell University, Ithaca, N.Y., wrote in an accompanying editorial.

The findings provide a foundation for studies of obesity-related cancer outcomes that take the community environment into consideration, they added.

The causes of both obesity and cancer are complex, and the study findings suggest that the links between unhealthy food environments and obesity-related cancer may go beyond dietary consumption alone and extend to social and psychological factors, the editorialists noted.

“Whether dealing with the lack of access to healthy foods or an overabundance of unhealthy food, there is a critical need to develop additional research that explores the associations between obesity-related cancer mortality and food inequities,” they concluded.

The study received no outside funding. The researchers and the editorialists had no financial conflicts to disclose.

Communities with easy access to fast food were 77% more likely to have high levels of obesity-related cancer mortality, based on data from a new cross-sectional study of more than 3,000 communities.

Although increased healthy eating has been associated with reduced risk of obesity and with reduced cancer incidence and mortality, access to healthier eating remains a challenge in communities with less access to grocery stores and healthy food options (food deserts) and/or easy access to convenience stores and fast food (food swamps), Malcolm Seth Bevel, PhD, of the Medical College of Georgia, Augusta, and colleagues, wrote in their paper, published in JAMA Oncology.

In addition, data on the association between food deserts and swamps and obesity-related cancer mortality are limited, they said.

“We felt that the study was important given the fact that obesity is an epidemic in the United States, and multiple factors contribute to obesity, especially adverse food environments,” Dr. Bevel said in an interview. “Also, I lived in these areas my whole life, and saw how it affected underserved populations. There was a story that needed to be told, so we’re telling it,” he said in an interview.

In a study, the researchers analyzed food access and cancer mortality data from 3,038 counties across the United States. The food access data came from the U.S. Department of Agriculture Food Environment Atlas (FEA) for the years 2012, 2014, 2015, 2017, and 2020. Data on obesity-related cancer mortality came from the Centers for Disease Control and Prevention for the years from 2010 to 2020.

Food desert scores were calculated through data from the FEA, and food swamp scores were based on the ratio of fast-food restaurants and convenience stores to grocery stores and farmers markets in a modification of the Retail Food Environment Index score.

The researchers used an age-adjusted, multiple regression model to determine the association between food desert and food swamp scores and obesity-related cancer mortality rates. Higher food swamp and food desert scores (defined as 20.0 to 58.0 or higher) were used to classify counties as having fewer healthy food resources. The primary outcome was obesity-related cancer mortality, defined as high or low (71.8 or higher per 100,000 individuals and less than 71.8 per 100,000 individuals, respectively).

Overall, high rates of obesity-related cancer mortality were 77% more likely in the counties that met the criteria for high food swamp scores (adjusted odds ratio 1.77). In addition, researchers found a positive dose-response relationship among three levels of both food desert scores and food swamp scores and obesity-related cancer mortality.

A total of 758 counties had obesity-related cancer mortality rates in the highest quartile. Compared to counties with low rates of obesity-related cancer mortality, counties with high rates of obesity-related cancer mortality also had a higher percentage of non-Hispanic Black residents (3.26% vs. 1.77%), higher percentage of adults older than 65 years (15.71% vs. 15.40%), higher rates of adult obesity (33.0% vs. 32.10%), and higher rates of adult diabetes (12.50% vs. 10.70%).

Possible explanations for the results include the lack of interest in grocery stores in neighborhoods with a population with a lower socioeconomic status, which can create a food desert, the researchers wrote in their discussion. “Coupled with the increasing growth rate of fast-food restaurants in recent years and the intentional advertisement of unhealthy foods in urban neighborhoods with [people of lower income], the food desert may transform into a food swamp,” they said.

The findings were limited by several factors including the study design, which did not allow for showing a causal association of food deserts and food swamps with obesity-related cancer mortality, the researchers noted. Other limitations included the use of groups rather than individuals, the potential misclassification of food stores, and the use of county-level data on race, ethnicity, and income, they wrote.

The results indicate that “food swamps appear to be a growing epidemic across the U.S., likely because of systemic issues, and should draw concern and conversation from local and state officials,” the researchers concluded.
 

Community-level investments can benefit individual health

Dr. Bevel said he was not surprised by the findings, as he has seen firsthand the lack of healthy food options and growth of unhealthy food options, especially for certain populations in certain communities. “Typically, these are people who have lower socioeconomic status, primarily non-Hispanic Black or African American or Hispanic American,” he said “I have watched people have to choose between getting fruits/vegetables versus their medications or running to fast food places to feed their families. What is truly surprising is that we’re not talking about people’s lived environment enough for my taste,” he said.  

“I hope that our data and results can inform local and state policymakers to truly invest in all communities, such as funding for community gardens, and realize that adverse food environments, including the barriers in navigating these environments, have significant consequences on real people,” said Dr. Bevel. “Also, I hope that the results can help clinicians realize that a patient’s lived environment can truly affect their obesity and/or obesity-related cancer status; being cognizant of that is the first step in holistic, comprehensive care,” he said. 

“One role that oncologists might be able to play in improving patients’ access to healthier food is to create and/or implement healthy lifestyle programs with gardening components to combat the poorest food environments that their patients likely reside in,” said Dr. Bevel. Clinicians also could consider the innovative approach of “food prescriptions” to help reduce the effects of deprived, built environments, he noted.

Looking ahead, next steps for research include determining the severity of association between food swamps and obesity-related cancer by varying factors such as cancer type, and examining any potential racial disparities between people living in these environments and obesity-related cancer, Dr. Bevel added.
 

Data provide foundation for multilevel interventions

The current study findings “raise a clarion call to elevate the discussion on food availability and access to ensure an equitable emphasis on both the importance of lifestyle factors and the upstream structural, economic, and environmental contexts that shape these behaviors at the individual level,” Karriem S. Watson, DHSc, MS, MPH, of the National Institutes of Health, Bethesda, Md., and Angela Odoms-Young, PhD, of Cornell University, Ithaca, N.Y., wrote in an accompanying editorial.

The findings provide a foundation for studies of obesity-related cancer outcomes that take the community environment into consideration, they added.

The causes of both obesity and cancer are complex, and the study findings suggest that the links between unhealthy food environments and obesity-related cancer may go beyond dietary consumption alone and extend to social and psychological factors, the editorialists noted.

“Whether dealing with the lack of access to healthy foods or an overabundance of unhealthy food, there is a critical need to develop additional research that explores the associations between obesity-related cancer mortality and food inequities,” they concluded.

The study received no outside funding. The researchers and the editorialists had no financial conflicts to disclose.

On January 1, 2021, the Current Procedural Terminology (CPT) evaluation and management (E/M) reporting rules changed dramatically, with “bullet counting” no longer necessary and the coding level now based on either the new medical decision making (MDM) table or time spent on all activities relating to the care of the patient on the day of the encounter.¹ This is described in the CPT Professional Edition 2023, a book every practitioner should review annually.² In particular, every provider should read and reread pages 1 to 14—and beyond if you provide services beyond standard office visits. These changes were made with the intent to simplify the process of documentation and allow a provider to spend more time with patients, though there is still a paucity of data related to whether the new system achieves these aims.

The general rule of reporting work with CPT codes can be simply stated—“Document what you did, do what you documented, and report that which is medically necessary” (David McCafferey, MD, personal communication)—and you should never have any difficulty with audits. Unfortunately, the new system does not let an auditor, who typically lacks a medical degree, audit effectively unless they have a clear understanding of diseases and their stages. Many medical societies, including the American Medical Association³ and American Academy of Dermatology,⁴ have provided education that focuses on how to report a given vignette, but specific examples of documentation with commentary are uncommon.

To make your documentation more likely to pass audits, explicitly link parts of your documentation to CPT MDM descriptors. We offer scenarios and tips. In part 1 of this series, we discuss how to approach the “spot check,” a commonly encountered chief concern (CC) within dermatology.

Scenario 1: A Funny-Looking New Spot

A 34-year-old presents with a new spot on the left cheek that seems to be growing and changing shape rapidly. You examine the patient and discuss treatment options. The documentation reads as follows:

• CC: New spot on left cheek that seems to be growing and changing shape rapidly.

• History: No family history of skin cancer; concerned about scarring, no blood thinner.

• Examination: Irregular tan to brown to black 8-mm macule. No lymphadenopathy.

• Impression: rule out melanoma.

• Plan: Consent, biopsy via shave technique. Lidocaine hydrochloride 1% with epinephrine, 1 cc, prepare and drape, hemostasis obtained, ointment and bandage applied, and care instructions provided.

As was the case before 2021, you still need a CC, along with a medically (and medicolegally) appropriate history and physical examination. A diagnostic impression and treatment plan also should be included.

In this situation, reporting is straightforward. There is no separate E/M visit; only the CPT code 11102 for tangential biopsy is reported. An International Classification of Diseases, Tenth Revision code of D48.5 (neoplasm of uncertain behavior of skin) will be included.

Why no E/M code? This is because the biopsy includes preservice and postservice time and work that would be double reported with the E/M. Remember that the preservice work would include any history and physical examination related to the area to be biopsied.

Specifically, preservice work includes:

Inspect and palpate lesion to assess surface size, subcutaneous depth and extension, and whether fixed to underlying structures. Select the most representative and appropriate site to obtain specimen. Examine draining lymph node basins. Discuss need for skin biopsy and biopsy technique options. Describe the tangential biopsy procedure method and expected result and the potential for inconclusive pathology result. Review procedural risks, including bleeding, pain, edema, infection, delayed healing, scarring, and hyper- or hypopigmentation.⁵

Postservice work includes:

Instruct patient and family on postoperative wound care and dressing changes, as well as problems such as bleeding or pain and restrictions on activities, and follow-up care. Provide prescriptions for pain and antibiotics as necessary. Advise patient and family when results will be available and how they will be communicated. The pathology request form is filled out and signed by the physician. Complete medical record and communicate procedure/results to referring physician as appropriate.⁵

The Takeaway—Procedure codes include preservice and postservice work. If additional work for the procedure is not documented beyond that, an E/M cannot be included in the encounter.

Scenario 2: What If We Don’t Biopsy?

A 34-year-old presents with a new spot on the left cheek that seems to be growing and changing shape rapidly. You examine the patient and discuss treatment options. The documentation reads as follows:

• CC: New spot on left cheek that seems to be growing and changing shape rapidly.

• History: No family history of skin cancer; concerned about scarring, no blood thinner.

• Examination: Irregular tan to brown to black 8-mm macule. No lymphadenopathy.

• Impression: rule out melanoma.

• Plan: Review risk, benefits, and alternative options. Schedule biopsy. Discuss unique risk factor of sebaceous peau d’orange skin more prone to contour defects after biopsy.

When determining the coding level for this scenario by MDM, 3 components must be considered: number and complexity of problems addressed at the encounter (column 1), amount and/or complexity of data to be reviewed and analyzed (column 2), and risk of complications and/or morbidity or mortality of patient management (column 3).¹ There are no data that are reviewed, so the auditor will assume minimal data to be reviewed and/or analyzed (level 2, row 2 in the MDM table). However, there may be a lot of variation in how an auditor would address the number and complexity of problems (level 1). Consider that you must explicitly state what you are thinking, as an auditor may not know melanoma is a life-threatening diagnosis. From the perspective of the auditor, could this be a:

• Self-limited or minor problem (level 2, or minimal problem in the MDM table)?¹

• Stable chronic illness (level 3, or low-level problem)?¹

• Undiagnosed new problem with uncertain prognosis (level 4, or moderate level problem)?¹

• Acute illness with systemic symptoms (level 4, or moderate level problem)?¹

• Acute or chronic illness or injury that poses a threat to life or bodily function (level 5, or high-level problem)?¹

• All of the above?

Similarly, there may be variation in how the risk (column 3) would be interpreted in this scenario. The treatment gives no guidance, so the auditor may assume this has a minimal risk of morbidity (level 2) or possibly a low risk of morbidity from additional diagnostic testing or treatment (level 3), as opposed to a moderate risk of morbidity (level 4).¹The Takeaway—In the auditor’s mind, this could be a straightforward (CPT codes 99202/99212) or lowlevel (99203/99213) visit as opposed to a moderate-level (99204/99214) visit. From the above documentation, an auditor would not be able to tell what you are thinking, and you can be assured they will not look further into the diagnosis or treatment to learn. That is not their job. So, let us clarify by explicitly stating what you are thinking in the context of the MDM grid.

Modified Scenario 2: A Funny-Looking New Spot With MDM Descriptors to Guide an Auditor

Below are modifications to the documentation for scenario 2 to guide an auditor:

• CC: New spot on left cheek that seems to be growing and changing shape rapidly.

• History: No family history of skin cancer; concerned about scarring, no blood thinner.

• Examination: Irregular tan to brown to black 8-mm macule. No lymphadenopathy.

• Impression: rule out melanoma (undiagnosed new problem with uncertain prognosis).

• Plan: Discuss risks, benefits, and alternatives, including biopsy (decision regarding minor surgery with identified patient or procedure risk factors) vs a noninvasive gene expression profiling melanoma rule-out test. Patient prefers the latter.

In this scenario, the level of MDM is much more clearly documented (as bolded above).

The number and complexity of problems would be an undiagnosed new problem with uncertain prognosis, which would be moderate complexity (column 1, level 4).¹ There are no data that are reviewed or analyzed, which would be straightforward (column 2, level 2). For risk, the discussion of the biopsy as part of the diagnostic choices should include discussion of possible scarring, bleeding, pain, and infection, which would be considered best described as a decision regarding minor surgery with identified patient or procedure risk factors, which would make this of moderate complexity (column 3, level 4).¹

Importantly, even if the procedure is not chosen as the final treatment plan, the discussion regarding the surgery, including the risks, benefits, and alternatives, can still count toward this category in the MDM table. Therefore, in this scenario with the updated and clarified documentation, this would be reported as CPT code 99204 for a new patient, while an established patient would be 99214.

Scenario 1 Revisited: A Funny-Looking New Spot

Below is scenario 1 with enhanced documentation, now applied to our procedure-only visit.

• CC: New spot on left cheek that seems to be growing and changing shape rapidly.

• History: No family history of skin cancer; concerned about scarring, no blood thinner.

• Examination: Irregular tan to brown to black 8-mm macule. No lymphadenopathy.

• Impression: rule out melanoma (undiagnosed new problem with uncertain prognosis).

• Plan: Discuss risks, benefits, and alternatives, including biopsy (decision regarding minor surgery with identified patient or procedure risk factors) vs a noninvasive 2 gene expression profiling melanoma rule-out test. Patient wants biopsy. Consent, biopsy via shave technique. Lidocaine hydrochloride 1% with epinephrine, 1 cc, prepare and drape, hemostasis obtained, ointment and bandage applied, and care instructions provided.

This documentation would only allow reporting the biopsy as in Scenario 1, as the decision to perform a 0- or 10-day global procedure is bundled with the procedure if performed on the same date of service.

Final Thoughts

Spot checks are commonly encountered dermatologic visits. With the updated E/M guidelines, clarifying and streamlining your documentation is crucial. In particular, utilizing language that clearly defines number and complexity of problems, amount and/or complexity of data to be reviewed and analyzed, and appropriate risk stratification is crucial to ensuring appropriate reimbursement and minimizing your pain with audits.

On January 1, 2021, the Current Procedural Terminology (CPT) evaluation and management (E/M) reporting rules changed dramatically, with “bullet counting” no longer necessary and the coding level now based on either the new medical decision making (MDM) table or time spent on all activities relating to the care of the patient on the day of the encounter.¹ This is described in the CPT Professional Edition 2023, a book every practitioner should review annually.² In particular, every provider should read and reread pages 1 to 14—and beyond if you provide services beyond standard office visits. These changes were made with the intent to simplify the process of documentation and allow a provider to spend more time with patients, though there is still a paucity of data related to whether the new system achieves these aims.

The general rule of reporting work with CPT codes can be simply stated—“Document what you did, do what you documented, and report that which is medically necessary” (David McCafferey, MD, personal communication)—and you should never have any difficulty with audits. Unfortunately, the new system does not let an auditor, who typically lacks a medical degree, audit effectively unless they have a clear understanding of diseases and their stages. Many medical societies, including the American Medical Association³ and American Academy of Dermatology,⁴ have provided education that focuses on how to report a given vignette, but specific examples of documentation with commentary are uncommon.

To make your documentation more likely to pass audits, explicitly link parts of your documentation to CPT MDM descriptors. We offer scenarios and tips. In part 1 of this series, we discuss how to approach the “spot check,” a commonly encountered chief concern (CC) within dermatology.

Scenario 1: A Funny-Looking New Spot

A 34-year-old presents with a new spot on the left cheek that seems to be growing and changing shape rapidly. You examine the patient and discuss treatment options. The documentation reads as follows:

• CC: New spot on left cheek that seems to be growing and changing shape rapidly.

• History: No family history of skin cancer; concerned about scarring, no blood thinner.

• Examination: Irregular tan to brown to black 8-mm macule. No lymphadenopathy.

• Impression: rule out melanoma.

• Plan: Consent, biopsy via shave technique. Lidocaine hydrochloride 1% with epinephrine, 1 cc, prepare and drape, hemostasis obtained, ointment and bandage applied, and care instructions provided.

As was the case before 2021, you still need a CC, along with a medically (and medicolegally) appropriate history and physical examination. A diagnostic impression and treatment plan also should be included.

In this situation, reporting is straightforward. There is no separate E/M visit; only the CPT code 11102 for tangential biopsy is reported. An International Classification of Diseases, Tenth Revision code of D48.5 (neoplasm of uncertain behavior of skin) will be included.

Why no E/M code? This is because the biopsy includes preservice and postservice time and work that would be double reported with the E/M. Remember that the preservice work would include any history and physical examination related to the area to be biopsied.

Specifically, preservice work includes:

Inspect and palpate lesion to assess surface size, subcutaneous depth and extension, and whether fixed to underlying structures. Select the most representative and appropriate site to obtain specimen. Examine draining lymph node basins. Discuss need for skin biopsy and biopsy technique options. Describe the tangential biopsy procedure method and expected result and the potential for inconclusive pathology result. Review procedural risks, including bleeding, pain, edema, infection, delayed healing, scarring, and hyper- or hypopigmentation.⁵

Postservice work includes:

Instruct patient and family on postoperative wound care and dressing changes, as well as problems such as bleeding or pain and restrictions on activities, and follow-up care. Provide prescriptions for pain and antibiotics as necessary. Advise patient and family when results will be available and how they will be communicated. The pathology request form is filled out and signed by the physician. Complete medical record and communicate procedure/results to referring physician as appropriate.⁵

The Takeaway—Procedure codes include preservice and postservice work. If additional work for the procedure is not documented beyond that, an E/M cannot be included in the encounter.

Scenario 2: What If We Don’t Biopsy?

A 34-year-old presents with a new spot on the left cheek that seems to be growing and changing shape rapidly. You examine the patient and discuss treatment options. The documentation reads as follows:

• CC: New spot on left cheek that seems to be growing and changing shape rapidly.

• History: No family history of skin cancer; concerned about scarring, no blood thinner.

• Examination: Irregular tan to brown to black 8-mm macule. No lymphadenopathy.

• Impression: rule out melanoma.

• Plan: Review risk, benefits, and alternative options. Schedule biopsy. Discuss unique risk factor of sebaceous peau d’orange skin more prone to contour defects after biopsy.

When determining the coding level for this scenario by MDM, 3 components must be considered: number and complexity of problems addressed at the encounter (column 1), amount and/or complexity of data to be reviewed and analyzed (column 2), and risk of complications and/or morbidity or mortality of patient management (column 3).¹ There are no data that are reviewed, so the auditor will assume minimal data to be reviewed and/or analyzed (level 2, row 2 in the MDM table). However, there may be a lot of variation in how an auditor would address the number and complexity of problems (level 1). Consider that you must explicitly state what you are thinking, as an auditor may not know melanoma is a life-threatening diagnosis. From the perspective of the auditor, could this be a:

• Self-limited or minor problem (level 2, or minimal problem in the MDM table)?¹

• Stable chronic illness (level 3, or low-level problem)?¹

• Undiagnosed new problem with uncertain prognosis (level 4, or moderate level problem)?¹

• Acute illness with systemic symptoms (level 4, or moderate level problem)?¹

• Acute or chronic illness or injury that poses a threat to life or bodily function (level 5, or high-level problem)?¹

• All of the above?

Similarly, there may be variation in how the risk (column 3) would be interpreted in this scenario. The treatment gives no guidance, so the auditor may assume this has a minimal risk of morbidity (level 2) or possibly a low risk of morbidity from additional diagnostic testing or treatment (level 3), as opposed to a moderate risk of morbidity (level 4).¹The Takeaway—In the auditor’s mind, this could be a straightforward (CPT codes 99202/99212) or lowlevel (99203/99213) visit as opposed to a moderate-level (99204/99214) visit. From the above documentation, an auditor would not be able to tell what you are thinking, and you can be assured they will not look further into the diagnosis or treatment to learn. That is not their job. So, let us clarify by explicitly stating what you are thinking in the context of the MDM grid.

Modified Scenario 2: A Funny-Looking New Spot With MDM Descriptors to Guide an Auditor

Below are modifications to the documentation for scenario 2 to guide an auditor:

• CC: New spot on left cheek that seems to be growing and changing shape rapidly.

• History: No family history of skin cancer; concerned about scarring, no blood thinner.

• Examination: Irregular tan to brown to black 8-mm macule. No lymphadenopathy.

• Impression: rule out melanoma (undiagnosed new problem with uncertain prognosis).

• Plan: Discuss risks, benefits, and alternatives, including biopsy (decision regarding minor surgery with identified patient or procedure risk factors) vs a noninvasive gene expression profiling melanoma rule-out test. Patient prefers the latter.

In this scenario, the level of MDM is much more clearly documented (as bolded above).

The number and complexity of problems would be an undiagnosed new problem with uncertain prognosis, which would be moderate complexity (column 1, level 4).¹ There are no data that are reviewed or analyzed, which would be straightforward (column 2, level 2). For risk, the discussion of the biopsy as part of the diagnostic choices should include discussion of possible scarring, bleeding, pain, and infection, which would be considered best described as a decision regarding minor surgery with identified patient or procedure risk factors, which would make this of moderate complexity (column 3, level 4).¹

Importantly, even if the procedure is not chosen as the final treatment plan, the discussion regarding the surgery, including the risks, benefits, and alternatives, can still count toward this category in the MDM table. Therefore, in this scenario with the updated and clarified documentation, this would be reported as CPT code 99204 for a new patient, while an established patient would be 99214.

Scenario 1 Revisited: A Funny-Looking New Spot

Below is scenario 1 with enhanced documentation, now applied to our procedure-only visit.

• CC: New spot on left cheek that seems to be growing and changing shape rapidly.

• History: No family history of skin cancer; concerned about scarring, no blood thinner.

• Examination: Irregular tan to brown to black 8-mm macule. No lymphadenopathy.

• Impression: rule out melanoma (undiagnosed new problem with uncertain prognosis).

• Plan: Discuss risks, benefits, and alternatives, including biopsy (decision regarding minor surgery with identified patient or procedure risk factors) vs a noninvasive 2 gene expression profiling melanoma rule-out test. Patient wants biopsy. Consent, biopsy via shave technique. Lidocaine hydrochloride 1% with epinephrine, 1 cc, prepare and drape, hemostasis obtained, ointment and bandage applied, and care instructions provided.

This documentation would only allow reporting the biopsy as in Scenario 1, as the decision to perform a 0- or 10-day global procedure is bundled with the procedure if performed on the same date of service.

Final Thoughts

Spot checks are commonly encountered dermatologic visits. With the updated E/M guidelines, clarifying and streamlining your documentation is crucial. In particular, utilizing language that clearly defines number and complexity of problems, amount and/or complexity of data to be reviewed and analyzed, and appropriate risk stratification is crucial to ensuring appropriate reimbursement and minimizing your pain with audits.

On January 1, 2021, the Current Procedural Terminology (CPT) evaluation and management (E/M) reporting rules changed dramatically, with “bullet counting” no longer necessary and the coding level now based on either the new medical decision making (MDM) table or time spent on all activities relating to the care of the patient on the day of the encounter.¹ This is described in the CPT Professional Edition 2023, a book every practitioner should review annually.² In particular, every provider should read and reread pages 1 to 14—and beyond if you provide services beyond standard office visits. These changes were made with the intent to simplify the process of documentation and allow a provider to spend more time with patients, though there is still a paucity of data related to whether the new system achieves these aims.

The general rule of reporting work with CPT codes can be simply stated—“Document what you did, do what you documented, and report that which is medically necessary” (David McCafferey, MD, personal communication)—and you should never have any difficulty with audits. Unfortunately, the new system does not let an auditor, who typically lacks a medical degree, audit effectively unless they have a clear understanding of diseases and their stages. Many medical societies, including the American Medical Association³ and American Academy of Dermatology,⁴ have provided education that focuses on how to report a given vignette, but specific examples of documentation with commentary are uncommon.

To make your documentation more likely to pass audits, explicitly link parts of your documentation to CPT MDM descriptors. We offer scenarios and tips. In part 1 of this series, we discuss how to approach the “spot check,” a commonly encountered chief concern (CC) within dermatology.

Scenario 1: A Funny-Looking New Spot

A 34-year-old presents with a new spot on the left cheek that seems to be growing and changing shape rapidly. You examine the patient and discuss treatment options. The documentation reads as follows:

• CC: New spot on left cheek that seems to be growing and changing shape rapidly.

• History: No family history of skin cancer; concerned about scarring, no blood thinner.

• Examination: Irregular tan to brown to black 8-mm macule. No lymphadenopathy.

• Impression: rule out melanoma.

• Plan: Consent, biopsy via shave technique. Lidocaine hydrochloride 1% with epinephrine, 1 cc, prepare and drape, hemostasis obtained, ointment and bandage applied, and care instructions provided.

As was the case before 2021, you still need a CC, along with a medically (and medicolegally) appropriate history and physical examination. A diagnostic impression and treatment plan also should be included.

In this situation, reporting is straightforward. There is no separate E/M visit; only the CPT code 11102 for tangential biopsy is reported. An International Classification of Diseases, Tenth Revision code of D48.5 (neoplasm of uncertain behavior of skin) will be included.

Why no E/M code? This is because the biopsy includes preservice and postservice time and work that would be double reported with the E/M. Remember that the preservice work would include any history and physical examination related to the area to be biopsied.

Specifically, preservice work includes:

Inspect and palpate lesion to assess surface size, subcutaneous depth and extension, and whether fixed to underlying structures. Select the most representative and appropriate site to obtain specimen. Examine draining lymph node basins. Discuss need for skin biopsy and biopsy technique options. Describe the tangential biopsy procedure method and expected result and the potential for inconclusive pathology result. Review procedural risks, including bleeding, pain, edema, infection, delayed healing, scarring, and hyper- or hypopigmentation.⁵

Postservice work includes:

Instruct patient and family on postoperative wound care and dressing changes, as well as problems such as bleeding or pain and restrictions on activities, and follow-up care. Provide prescriptions for pain and antibiotics as necessary. Advise patient and family when results will be available and how they will be communicated. The pathology request form is filled out and signed by the physician. Complete medical record and communicate procedure/results to referring physician as appropriate.⁵

The Takeaway—Procedure codes include preservice and postservice work. If additional work for the procedure is not documented beyond that, an E/M cannot be included in the encounter.

Scenario 2: What If We Don’t Biopsy?

A 34-year-old presents with a new spot on the left cheek that seems to be growing and changing shape rapidly. You examine the patient and discuss treatment options. The documentation reads as follows:

• CC: New spot on left cheek that seems to be growing and changing shape rapidly.

• History: No family history of skin cancer; concerned about scarring, no blood thinner.

• Examination: Irregular tan to brown to black 8-mm macule. No lymphadenopathy.

• Impression: rule out melanoma.

• Plan: Review risk, benefits, and alternative options. Schedule biopsy. Discuss unique risk factor of sebaceous peau d’orange skin more prone to contour defects after biopsy.

When determining the coding level for this scenario by MDM, 3 components must be considered: number and complexity of problems addressed at the encounter (column 1), amount and/or complexity of data to be reviewed and analyzed (column 2), and risk of complications and/or morbidity or mortality of patient management (column 3).¹ There are no data that are reviewed, so the auditor will assume minimal data to be reviewed and/or analyzed (level 2, row 2 in the MDM table). However, there may be a lot of variation in how an auditor would address the number and complexity of problems (level 1). Consider that you must explicitly state what you are thinking, as an auditor may not know melanoma is a life-threatening diagnosis. From the perspective of the auditor, could this be a:

• Self-limited or minor problem (level 2, or minimal problem in the MDM table)?¹

• Stable chronic illness (level 3, or low-level problem)?¹

• Undiagnosed new problem with uncertain prognosis (level 4, or moderate level problem)?¹

• Acute illness with systemic symptoms (level 4, or moderate level problem)?¹

• Acute or chronic illness or injury that poses a threat to life or bodily function (level 5, or high-level problem)?¹

• All of the above?

Similarly, there may be variation in how the risk (column 3) would be interpreted in this scenario. The treatment gives no guidance, so the auditor may assume this has a minimal risk of morbidity (level 2) or possibly a low risk of morbidity from additional diagnostic testing or treatment (level 3), as opposed to a moderate risk of morbidity (level 4).¹The Takeaway—In the auditor’s mind, this could be a straightforward (CPT codes 99202/99212) or lowlevel (99203/99213) visit as opposed to a moderate-level (99204/99214) visit. From the above documentation, an auditor would not be able to tell what you are thinking, and you can be assured they will not look further into the diagnosis or treatment to learn. That is not their job. So, let us clarify by explicitly stating what you are thinking in the context of the MDM grid.

Modified Scenario 2: A Funny-Looking New Spot With MDM Descriptors to Guide an Auditor

Below are modifications to the documentation for scenario 2 to guide an auditor:

• CC: New spot on left cheek that seems to be growing and changing shape rapidly.

• History: No family history of skin cancer; concerned about scarring, no blood thinner.

• Examination: Irregular tan to brown to black 8-mm macule. No lymphadenopathy.

• Impression: rule out melanoma (undiagnosed new problem with uncertain prognosis).

• Plan: Discuss risks, benefits, and alternatives, including biopsy (decision regarding minor surgery with identified patient or procedure risk factors) vs a noninvasive gene expression profiling melanoma rule-out test. Patient prefers the latter.

In this scenario, the level of MDM is much more clearly documented (as bolded above).

The number and complexity of problems would be an undiagnosed new problem with uncertain prognosis, which would be moderate complexity (column 1, level 4).¹ There are no data that are reviewed or analyzed, which would be straightforward (column 2, level 2). For risk, the discussion of the biopsy as part of the diagnostic choices should include discussion of possible scarring, bleeding, pain, and infection, which would be considered best described as a decision regarding minor surgery with identified patient or procedure risk factors, which would make this of moderate complexity (column 3, level 4).¹

Importantly, even if the procedure is not chosen as the final treatment plan, the discussion regarding the surgery, including the risks, benefits, and alternatives, can still count toward this category in the MDM table. Therefore, in this scenario with the updated and clarified documentation, this would be reported as CPT code 99204 for a new patient, while an established patient would be 99214.

Scenario 1 Revisited: A Funny-Looking New Spot

Below is scenario 1 with enhanced documentation, now applied to our procedure-only visit.

• CC: New spot on left cheek that seems to be growing and changing shape rapidly.

• History: No family history of skin cancer; concerned about scarring, no blood thinner.

• Examination: Irregular tan to brown to black 8-mm macule. No lymphadenopathy.

• Impression: rule out melanoma (undiagnosed new problem with uncertain prognosis).

• Plan: Discuss risks, benefits, and alternatives, including biopsy (decision regarding minor surgery with identified patient or procedure risk factors) vs a noninvasive 2 gene expression profiling melanoma rule-out test. Patient wants biopsy. Consent, biopsy via shave technique. Lidocaine hydrochloride 1% with epinephrine, 1 cc, prepare and drape, hemostasis obtained, ointment and bandage applied, and care instructions provided.

This documentation would only allow reporting the biopsy as in Scenario 1, as the decision to perform a 0- or 10-day global procedure is bundled with the procedure if performed on the same date of service.

Final Thoughts

Spot checks are commonly encountered dermatologic visits. With the updated E/M guidelines, clarifying and streamlining your documentation is crucial. In particular, utilizing language that clearly defines number and complexity of problems, amount and/or complexity of data to be reviewed and analyzed, and appropriate risk stratification is crucial to ensuring appropriate reimbursement and minimizing your pain with audits.