Factors Associated With Disparities in Hospital Readmission Rates Among US Adults Dually Eligible for Medicare and Medicaid.

Importance: Low-income older adults who are dually eligible (DE) for Medicare and Medicaid often experience worse outcomes following hospitalization. Among other federal policies aimed at improving health for DE patients, Medicare has recently begun reporting disparities in within-hospital readmissions. The degree to which disparities for DE patients are owing to differences in community-level factors or, conversely, are amenable to hospital quality improvement, remains heavily debated. Objective: To examine the extent to which within-hospital disparities in 30-day readmission rates for DE patients are ameliorated by state- and community-level factors. Design Setting and Participants: In this retrospective cohort study, Centers for Medicare & Medicaid Services (CMS) Disparity Methods were used to calculate within-hospital disparities in 30-day risk-adjusted readmission rates for DE vs non-DE patients in US hospitals participating in Medicare. All analyses were performed in February and March 2019. The study included Medicare patients (aged ≥65 years) hospitalized for acute myocardial infarction (AMI), heart failure (HF), or pneumonia in 2014 to 2017. Main Outcomes and Measures: Within-hospital disparities, as measured by the rate difference (RD) in 30-day readmission between DE vs non-DE patients following admission for AMI, HF, or pneumonia; variance across hospitals; and correlation of hospital RDs with and without adjustment for state Medicaid eligibility policies and community-level factors. Results: The final sample included 475 444 patients admitted for AMI, 898 395 for HF, and 1 214 282 for pneumonia, of whom 13.2%, 17.4%, and 23.0% were DE patients, respectively. Dually eligible patients had higher 30-day readmission rates relative to non-DE patients (RD >0) in 99.0% (AMI), 99.4% (HF), and 97.5% (pneumonia) of US hospitals. Across hospitals, the mean (IQR) RD between DE vs non-DE was 1.00% (0.87%-1.10%) for AMI, 0.82% (0.73%-0.96%) for HF, and 0.53% (0.37%-0.71%) for pneumonia. The mean (IQR) RD after adjustment for community-level factors was 0.87% (0.73%-0.97%) for AMI, 0.67% (0.57%-0.80%) for HF, and 0.42% (0.29%-0.57%) for pneumonia. Relative hospital rankings of corresponding within-hospital disparities before and after community-level adjustment were highly correlated (Pearson coefficient, 0.98). Conclusions and Relevance: In this cohort study, within-hospital disparities in 30-day readmission for DE patients were modestly associated with differences in state Medicaid policies and community-level factors. This suggests that remaining variation in these disparities should be the focus of hospital efforts to improve the quality of care transitions at discharge for DE patients in efforts to advance equity.

Measuring hospital-specific disparities by dual eligibility and race to reduce health inequities.

OBJECTIVE: To propose and evaluate a metric for quantifying hospital-specific disparities in health outcomes that can be used by patients and hospitals. DATA SOURCES/STUDY SETTING: Inpatient admissions for Medicare patients with acute myocardial infarction, heart failure, or pneumonia to all non-federal, short-term, acute care hospitals during 2012-2015. STUDY DESIGN: Building on the current Centers for Medicare and Medicaid Services methodology for calculating risk-standardized readmission rates, we developed models that include a hospital-specific random coefficient for either patient dual eligibility status or African American race. These coefficients quantify the difference in risk-standardized outcomes by dual eligibility and race at a given hospital after accounting for the hospital's patient case mix and proportion of dual eligible or African American patients. We demonstrate this approach and report variation and performance in hospital-specific disparities. PRINCIPAL FINDINGS: Dual eligibility and African American race were associated with higher readmission rates within hospitals for all three conditions. However, this disparity effect varied substantially across hospitals. CONCLUSION: Our models isolate a hospital-specific disparity effect and demonstrate variation in quality of care for different groups of patients across conditions and hospitals. Illuminating within-hospital disparities can incentivize hospitals to reduce inequities in health care quality.