Comparing HEDIS performance of Dual Eligible Special Needs Plans with other coverage types for dually eligible people.

People eligible for both Medicare and Medicaid coverage ("dually eligible individuals") have lower levels of income and assets and often higher health care needs and costs than those eligible for Medicare but not Medicaid coverage. Their 3 most common Medicare coverage options are Medicare Advantage (MA) Dual Eligible Special Needs Plans (D-SNPs), non-D-SNP MA plans, and fee-for-service (FFS) Medicare with a stand-alone prescription drug plan. No prior study has examined clinical quality of care for dually eligible individuals across these 3 coverage types. To fill that void, we used logistic regression to compare these coverage types on 6 HEDIS measures of clinical quality of care that were available for both MA and FFS (constructed from claims files). D-SNPs and non-D-SNP MA plans significantly outperformed FFS for all 6 measures for dually eligible individuals, by approximately 5 percentage points for 2 measures and by 18-34 percentage points for the other 4 measures. For the 4 measures with the greatest advantage over FFS, performance was 3-8 percentage points higher in D-SNPs than in non-D-SNP MA plans.

Income-related disparities in Medicare advantage behavioral health care quality.

OBJECTIVE: To inform efforts to improve equity in the quality of behavioral health care by examining income-related differences in performance on HEDIS behavioral health measures in Medicare Advantage (MA) plans. DATA SOURCES AND STUDY SETTING: Reporting Year 2019 MA HEDIS data were obtained and analyzed. STUDY DESIGN: Logistic regression models were used to estimate differences in performance related to enrollee income, adjusting for sex, age, and race-and-ethnicity. Low-income enrollees were identified by Dual Eligibility for Medicare and Medicaid or receipt of the Low-Income Subsidy (DE/LIS). Models without and with random effects for plans were used to estimate overall and within-plan differences in measure performance. Heterogeneity by race-and-ethnicity in the associations of low-income with behavioral health quality were examined using models with interaction terms. DATA COLLECTION/EXTRACTION METHODS: Data were included for all MA contracts in the 50 states and the District of Columbia that collect HEDIS data. PRINCIPAL FINDINGS: For six of the eight measures, enrollees with DE/LIS coverage were more likely to have behavioral health conditions that qualify for HEDIS measures than higher income enrollees. In mixed-effects logistic regression models, DE/LIS coverage was associated with statistically significantly worse overall performance on five measures, with four large (>5 percentage point) differences (-7.5 to -11.1 percentage points) related to follow-up after hospitalization and avoidance of drug-disease interactions. Where the differences were large, they were primarily within-plan rather than between-plan. Interactions between DE/LIS and race-and-ethnicity were statistically significant (p < 0.05) for all measures; income-based quality gaps were larger for White enrollees than for Black or Hispanic enrollees. CONCLUSIONS: Low income is associated with lower performance on behavioral health HEDIS measures in MA, but these associations differ across racial-and-ethnic groups. Improving care integration and addressing barriers to care for low-income enrollees may improve equity across income levels in behavioral health care.