# Alternative Approaches to Characterizing Disparate Care by Race, Ethnicity, and Insurance Between Hospitals

**Authors:** Alina Kung, Yingtong Chen, Bian Liu, Louisa W. Holaday, Karen McKendrick, Albert L. Siu

PMC · DOI: 10.3390/ijerph22101514 · 2025-10-02

## TL;DR

This study proposes a new way to identify hospitals that disproportionately serve minority and publicly insured patients by combining multiple measures.

## Contribution

The study introduces a combined measure that accounts for multiple characteristics to better identify hospitals with disproportionate patient populations.

## Key findings

- The combined measure identified 28.1% of hospitals as disproportionately serving minority or publicly insured patients.
- Hospitals identified by the combined measure had lower quality ratings and served smaller, rural populations.
- The combined measure detected significant differences in hospital quality ratings compared to traditional methods.

## Abstract

Identifying hospitals that disproportionately serve minority and publicly insured patients is important because patients at these hospitals often experience worse outcomes. Studies commonly identify disproportion by using the top decile of hospitals with the greatest proportion of Black discharges nationally. Our study aimed to identify a broader measure that accounts for disproportion by multiple characteristics. Using fee-for-service Medicare data, we classified hospitals as either serving disproportionately or not, examined overlaps in classification, and assessed differences in hospital quality. We found that using a combined measure for any hospitals in the top decile or above a threshold of twice their local healthcare market average of Black, Hispanic, minority, or dual-eligible discharges classified 28.1% (n = 680/2420) of hospitals as serving disproportionately, compared to only 10% (n = 242/2420) when using the top decile of a single characteristic. The combined measure detected moderate differences in hospital star quality ratings (mean difference of 0.57–0.87, all p-values < 0.001; standardized mean difference: 0.50–0.79, 95% CIs all above 0). The combined measure identified hospitals that were smaller, more rural, and served other minorities, namely, Asian and American Indian populations. Future work should consider using this combined measure to more comprehensively identify hospitals that disproportionately serve minority or publicly insured patients.

## Full-text entities

- **Diseases:** Disparate Care (MESH:D011019)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Figures

6 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12562512/full.md

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Source: https://tomesphere.com/paper/PMC12562512