Racial differences in laboratory testing as a potential mechanism for bias in AI: A matched cohort analysis in emergency department visits.

ABSTRACT: AI models are often trained using available laboratory test results. Racial differences in laboratory testing may bias AI models for clinical decision support, amplifying existing inequities. This study aims to measure the extent of racial differences in laboratory testing in adult emergency department (ED) visits. We conducted a retrospective 1:1 exact-matched cohort study of Black and White adult patients seen in the ED, matching on age, biological sex, chief complaint, and ED triage score, using ED visits at two U.S. teaching hospitals: Michigan Medicine, Ann Arbor, MI (U-M, 2015-2022), and Beth Israel Deaconess Medical Center, Boston, MA (BIDMC, 2011-2019). Post-matching, White patients had significantly higher testing rates than Black patients for complete blood count (BIDMC differenc

SUBMITTER: Chang T 

PROVIDER: S-EPMC11524489 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature