Patient-Centered Appraisal of Race-Free Clinical Risk Assessment

TL;DR

This paper critically examines the implications of removing race from clinical risk assessments, revealing that race-free models may negatively impact patient outcomes across all racial groups from a patient-centered economic perspective.

Contribution

It provides a novel analysis of the potential adverse effects of race-free risk assessments on clinical decision quality and patient outcomes.

Findings

Race-free risk assessment could harm patient outcomes.

Using race in risk models may improve clinical decision accuracy.

Removing race may increase health disparities.

Abstract

Until recently, there has been a consensus that clinicians should condition patient risk assessments on all observed patient covariates with predictive power. The broad idea is that knowing more about patients enables more accurate predictions of their health risks and, hence, better clinical decisions. This consensus has recently unraveled with respect to a specific covariate, namely race. There have been increasing calls for race-free risk assessment, arguing that using race to predict patient outcomes contributes to racial disparities and inequities in health care. Writers calling for race-free risk assessment have not studied how it would affect the quality of clinical decisions. Considering the matter from the patient-centered perspective of medical economics yields a disturbing conclusion: Race-free risk assessment would harm patients of all races.