Racial Bias in Algorithms Used to Identify Patients Who Need Special Attention

Many U.S. health systems use proprietary algorithms that analyze electronic medical record data to identify patients who are particularly at risk for adverse health outcomes in hopes of intervening to prevent those outcomes. To examine potential racial disparities in algorithms' recommendations, investigators obtained a medical record dataset from a large health system that covered more than 100,000 patient-years. The dataset included elements used to predict outcomes and the outcomes themselves. Investigators also were given the algorithms' inputs (e.g., demographics not including race, insurance type, diagnosis and procedure codes, medications, and detailed costs) and outputs.

The algorithm assumed that patients who were projected to have …