When the Process Is the Problem: Racial/Ethnic and Language Disparities in Care Management.

OBJECTIVES: Achieving health equity requires addressing disparities at every level of care delivery. Yet, little literature exists examining racial/ethnic disparities in processes of high-risk care management, a foundational tool for population health. This study sought to determine whether race, ethnicity, and language are associated with patient entry into and service intensity within a large care management program. DESIGN: Retrospective cohort study. METHODS: Subjects were 23,836 adult patients eligible for the program between 2015 and 2018. Adjusting for demographics, utilization, and medical risk, we analyzed the association between race/ethnicity and language and outcomes of patient selection, enrollment, care plan completion, and care management encounters. RESULTS: Among all identified as eligible by an algorithm, Asian and Spanish-speaking patients had significantly lower odds of being selected by physicians for care management [OR 0.74 (0.58-0.93), OR 0.79 (0.64-0.97)] compared with White and English-speaking patients, respectively. Once selected, Hispanic/Latino and Asian patients had significantly lower odds compared to White counterparts of having care plans completed by care managers [OR 0.69 (0.50-0.97), 0.50 (0.32-0.79), respectively]. Patients speaking languages other than English or Spanish had a lower odds of care plan completion and had fewer staff encounters than English-speaking counterparts [OR 0.62 (0.44-0.87), RR 0.87 (0.75-1.00), respectively]. CONCLUSIONS: Race/ethnicity and language-based disparities exist at every process level within a large health system's care management program, from selection to outreach. These results underscore the importance of assessing for disparities not just in outcomes but also in program processes, to prevent population health innovations from inadvertently creating new inequities.

Is the Gap Closing? Comparison of Sociodemographic Disparities in COVID-19 Hospitalizations and Outcomes Between Two Temporal Waves of Admissions.

OBJECTIVE: The COVID-19 pandemic has disproportionately impacted minority communities, yet little data exists regarding whether disparities have improved at a health system level. This study examined whether sociodemographic disparities in hospitalization and clinical outcomes changed between two temporal waves of hospitalized COVID-19 patients. METHODS: This is a retrospective cohort study of primary care patients at Mass General Brigham (a large northeastern health system serving 1.27 million primary care patients) hospitalized in-system with COVID-19 between March 1, 2020, and March 1, 2021, categorized into two 6-month "wave" periods. We used chi-square tests to compare demographics between waves, and regression analysis to characterize the association of race/ethnicity and language with in-hospital severe outcomes (death, hospice discharge, intensive unit care need). RESULTS: Hispanic/Latino, Black, and non-English-speaking patients constituted 30.3%, 12.5%, and 29.7% of COVID-19 admissions in wave 1 (N = 5844) and 22.2%, 9.0%, and 22.7% in wave 2 (N = 4007), compared to 2019 general admission proportions of 8.8%, 6.3%, and 7.7%, respectively. Admissions from highly socially vulnerable census tracts decreased between waves. Non-English speakers had significantly higher odds of severe illness during wave 1 (OR 1.35; 95% CI: 1.10, 1.66) compared to English speakers; this association was non-significant during wave 2 (OR 1.01; 95% CI: 0.76, 1.36). CONCLUSIONS: Comparing two COVID-19 temporal waves, significant sociodemographic disparities in COVID-19 admissions improved between waves but continued to persist over a year, demonstrating the need for ongoing interventions to truly close equity gaps. Non-English-speaking language status independently predicted worse hospitalization outcomes in wave 1, underscoring the importance of targeted and effective in-hospital supports for non-English speakers.