Using measures of race to make clinical predictions: Decision making, patient health, and fairness

Charles F. Manski, John Mullahy, Atheendar S. Venkataramani

Research output: Contribution to journalArticlepeer-review

Abstract

The use of race measures in clinical prediction models is contentious. We seek to inform the discourse by evaluating the inclusion of race in probabilistic predictions of illness that support clinical decision making. Adopting a static utilitarian framework to formalize social welfare, we show that patients of all races benefit when clinical decisions are jointly guided by patient race and other observable covariates. Similar conclusions emerge when the model is extended to a two-period setting where prevention activities target systemic drivers of disease. We also discuss non-utilitarian concepts that have been proposed to guide allocation of health care resources.

Original languageEnglish (US)
Pages (from-to)e2303370120
JournalProceedings of the National Academy of Sciences of the United States of America
Volume120
Issue number35
DOIs
StatePublished - Aug 29 2023

Keywords

  • clinical prediction
  • patient care
  • race
  • utilitarian welfare analysis

ASJC Scopus subject areas

  • General

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