Patient-centered appraisal of race-free clinical risk assessment

Charles F. Manski*

*Corresponding author for this work

Research output: Contribution to journalEditorialpeer-review

Abstract

Until recently, there has been a consensus that clinicians seeking to assess patient risks of illness should condition 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 health risks contributes to racial disparities and inequities in health care. In some medical fields, leading institutions have recommended race-free risk assessment. An important open question is how race-free risk assessment 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.

Original languageEnglish (US)
Pages (from-to)2109-2114
Number of pages6
JournalHealth Economics (United Kingdom)
Volume31
Issue number10
DOIs
StatePublished - Oct 2022

Keywords

  • predicting illness risk
  • racial health disparities
  • risk assessment algorithms

ASJC Scopus subject areas

  • Health Policy

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