Background: Although racial and ethnic minorities disproportionately use some hospitals, hospital-based racial and ethnic composition relative to geographic region and its association with quality indicators has not been systematically analyzed. Methods: We used four race and ethnicity categories: non-Hispanic white (NHW), non-Hispanic black (NHB), Hispanic, and Asian/Pacific Islander/Alaskan Native/American Indian (API/AIAN), as well as a combined non-NHW category, from the 2010 (latest year publicly available) Medicare Institutional Provider & Beneficiary Summary public use file for 84 hospitals in the New York City region. We assessed the relative distribution of race and ethnicity across hospitals grouped at different geographic levels (region, county, hospital referral region [HRR], or hospital service areas [HSA]) using the dissimilarity index. Hospital characteristics included quality star ratings, essential professional services and diagnostic/treatment equipment, bed size, total expenses, and patients with dual Medicare and Medicaid enrollment. We assessed Spearman’s rank correlation between hospital-based racial and ethnic composition and quality/structural measures. Results: Dissimilarity Index decreases from region (range 30.3–40.1%) to county (range 13.7–23.5%), HRR (range 10.5–27.5%), and HSA (range 12.0–16.9%) levels. Hospitals with larger non-NHW patients tended to have lower hospital ratings and higher proportions of dually-enrolled patients. They were also more likely to be safety net hospitals and non-federal governmental hospitals. Conclusions: In the NYC metropolitan region, there is considerable hospital-based racial and ethnic segregation of Medicare patients among non-NHW populations, extending previous research limited to NHB. Availability of data on racial and ethnic composition of hospitals should be made publicly available for researchers and consumers.

Original languageEnglish
Article number1021
JournalBMC Health Services Research
Issue number1
StatePublished - Dec 2022


  • Disparities
  • Dissimilarity index
  • Health systems
  • Medicare
  • Race and ethnicity
  • Segregation


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