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Over the years, several studies have demonstrated that there existsignificant disparities in health indicators in the United States populationacross various groups. Healthcare expense is used as a proxy for health inalgorithms that drive healthcare systems and this exacerbates the existingbias. In this work, we focus on the presence of racial bias in healthindicators in the publicly available, and nationally representative MedicalExpenditure Panel Survey (MEPS) data. We show that predictive models for caremanagement trained using this data inherit this bias. Finally, we demonstratethat this inherited bias can be reduced significantly using simple mitigationtechniques.

Understanding racial bias in health using the Medical Expenditure Panel Survey data