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

Author

Listed:
  • Charles F. Manski

    (b Institute for Policy Research, Northwestern University , Evanston , IL 60208)

  • John Mullahy

    (c Department of Population Health Sciences, University of Wisconsin–Madison , Madison , WI 53726)

  • Atheendar S. Venkataramani

    (d Department of Medical Ethics & Health Policy, University of Pennsylvania , Philadelphia , PA 19104)

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.

Suggested Citation

  • Charles F. Manski & John Mullahy & Atheendar S. Venkataramani, 2023. "Using measures of race to make clinical predictions: Decision making, patient health, and fairness," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 120(35), pages 2303370120-, August.
    • Handle: RePEc:nas:journl:v:120:y:2023:p:e2303370120
    DOI: 10.1073/pnas.2303370120
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    Keywords

    clinical prediction; patient care; utilitarian welfare analysis; race;
    All these keywords.

    JEL classification:

    • I10 - Health, Education, and Welfare - - Health - - - General
    • I14 - Health, Education, and Welfare - - Health - - - Health and Inequality

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