Mitigating Racial Bias in Health Care Algorithms: Improving Fairness in Access to Supportive Housing.

Autor:	Noam KR; Carelon Behavioral Health, Rocky Hill, Connecticut (Noam); Department of Psychiatry, School of Medicine, Yale University, New Haven (Schmutte); Mathematica, Princeton, New Jersey (Bory); private practice, Middlefield, Connecticut (Plant)., Schmutte T; Carelon Behavioral Health, Rocky Hill, Connecticut (Noam); Department of Psychiatry, School of Medicine, Yale University, New Haven (Schmutte); Mathematica, Princeton, New Jersey (Bory); private practice, Middlefield, Connecticut (Plant)., Bory C; Carelon Behavioral Health, Rocky Hill, Connecticut (Noam); Department of Psychiatry, School of Medicine, Yale University, New Haven (Schmutte); Mathematica, Princeton, New Jersey (Bory); private practice, Middlefield, Connecticut (Plant)., Plant RW; Carelon Behavioral Health, Rocky Hill, Connecticut (Noam); Department of Psychiatry, School of Medicine, Yale University, New Haven (Schmutte); Mathematica, Princeton, New Jersey (Bory); private practice, Middlefield, Connecticut (Plant).
Jazyk:	angličtina
Zdroj:	Psychiatric services (Washington, D.C.) [Psychiatr Serv] 2024 Nov 01; Vol. 75 (11), pp. 1167-1171. Date of Electronic Publication: 2024 Jun 28.
DOI:	10.1176/appi.ps.20230359
Abstrakt:	Algorithms for guiding health care decisions have come under increasing scrutiny for being unfair to certain racial and ethnic groups. The authors describe their multistep process, using data from 3,465 individuals, to reduce racial and ethnic bias in an algorithm developed to identify state Medicaid beneficiaries experiencing homelessness and chronic health needs who were eligible for coordinated health care and housing supports. Through an iterative process of adjusting inputs, reviewing outputs with diverse stakeholders, and performing quality assurance, the authors developed an algorithm that achieved racial and ethnic parity in the selection of eligible Medicaid beneficiaries. Competing Interests: The authors report no financial relationships with commercial interests.
Databáze:	MEDLINE
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