Race as a Risk Marker, Not a Risk Factor: Revising Race-Based Algorithms to Protect Racially Oppressed Patients

Abstract

Emerging consensus in the medical and public health spheres encourages removing race and ethnicity from algorithms used in clinical decision-making. Although clinical algorithms remain appealing given their promise to lighten the cognitive load of medical practice and save time for providers, they risk exacerbating existing health disparities. Race is a strong risk marker of health outcomes, yet it is not a risk factor. The use of race as a factor in medical algorithms suggests that the effect of race is intrinsic to the patient or that its effects can be distinct or separated from other social and environmental variables. By contrast, incisive public health analysis coupled with a race-conscious perspective recognizes that race serves as a marker of countless other dynamic variables and that structural racism, rather than race, compromises the health of racially oppressed individuals. This perspective offers a historical and theoretical context for the current debates regarding the use of race in clinical algorithms, clinical and epidemiologic perspectives on “risk,” and future directions for research and policy interventions that combat color-evasive racism and follow the principles of race-conscious medicine.