Background/Objectives The race-sex differences in emergency department (ED) disposition decisions have been reported widely. Our objective is to identify demographic and clinical subgroups for which this disparity is most pronounced, which will facilitate future targeted research and potential interventions. Methods We performed a retrospective analysis of 93,987 Caucasian and African-American adults assigned an Emergency Severity Index of 3 at three large EDs from January 2019 to February 2020. Using random forests, we identified the Elixhauser comorbidity score, age, and insurance status as important variables to divide data into subpopulations. Logistic regression models were then fitted to test race-sex disparities within each subpopulation while controlling for other patient characteristics and ED conditions. Results In each subpopulation, African-American women were less likely to be admitted than Caucasian men with odds ratios as low as 0.304 (95% confidence interval (CI): [0.229, 0.404]). African-American men had smaller admission odds compared to Caucasian men in subpopulations of 41+ years of age or with very low/high Elixhauser scores, odds ratios being as low as 0.652 (CI: [0.590, 0.747]). Caucasian women were less likely to be admitted than Caucasian men in subpopulations of 18-40 or 41-64 years of age, with low Elixhauser scores, or with Self-Pay or Medicaid insurance status with odds ratios as low as 0.574 (CI: [0.421, 0.784]). Conclusions African-American women faced disparities in all subgroups while disparities were lessened by younger age for African-American men, and by older age, higher Elixhauser score, and Medicare or Commercial insurance for Caucasian women. In general, patients of age 64 years or younger, with low comorbidity scores, or with Medicaid or no insurance appeared most prone to disparities in admissions.

The authors have declared no competing interest.

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This study was approved by the IRB at the University of North Carolina at Chapel Hill.

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Partial deidentifed patient-level data files and data dictionary are available upon request from 8/1/2024 by contacting Dr. Argon at nilay@unc.edu to investigators with an IRB letter of approval and fully executed Carolina Data Warehouse for Health data use agreement with UNC Health.