Eliminating Algorithmic Racial Bias in Clinical Decision Support Algorithms: Use Cases from the Veterans Health Administration-Reference-Cited by-同舟云学术

Eliminating Algorithmic Racial Bias in Clinical Decision Support Algorithms: Use Cases from the Veterans Health Administration

Published:2023-11-01 Issue:1 Volume:7 Page:809-816
ISSN:2473-1242
Container-title:Health Equity
language:en
Short-container-title:Health Equity

Author:

List Justin M.¹²^ORCID,Palevsky Paul³⁴^ORCID,Tamang Suzanne⁵⁶,Crowley Susan⁷⁸,Au David⁹,Yarbrough William C.¹⁰¹¹,Navathe Amol S.¹²¹³,Kreisler Craig¹⁴,Parikh Ravi B.¹²¹⁵,Wang-Rodriguez Jessica¹⁶¹⁷,Klutts J. Stacey¹⁸¹⁹²⁰,Conlin Paul²¹²²,Pogach Leonard²³,Meerwijk Esther⁵,Moy Ernest¹

Affiliation:

1. VA Office of Health Equity, Washington, District of Columbia, USA.

2. Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut, USA.

3. Kidney Medicine Section, Medical Service, VA Pittsburgh Healthcare System, Pittsburgh, Pennsylvania, USA.

4. Renal-Electrolyte Division, Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA.

5. Department of Veterans Affairs, Palo Alto, California, USA.

6. Department of Medicine, Stanford University School of Medicine, Stanford, California, USA.

7. Nephrology Section, Department of Medicine, Yale School of Medicine, New Haven, Connecticut, USA.

8. VA Connecticut Healthcare System, West Haven, Connecticut, USA.

9. Health Services Research and Development, VA Puget Sound Health Care System, Seattle, Washington, USA.

10. Department of Internal Medicine, The University of Texas Southwestern Medical Center, Dallas, Texas, USA.

11. VA North Texas Health Care System, Dallas, Texas, USA.

12. Corporal Michael J. Crescenz VA Medical Center, Philadelphia, Pennsylvania, USA.

13. Department of Medical Ethics and Health Policy, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.

14. Analytics and Performance Integration (API), Office of Quality and Patient Safety, Veterans Health Administration, Washington, District of Columbia, USA.

15. Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.

16. VA National Pathology and Laboratory Medicine Service, Washington, District of Columbia, USA.

17. Department of Pathology, University of California San Diego School of Medicine, La Jolla, California, USA.

18. National VHA Diagnostics Office, Washington, District of Columbia, USA.

19. Iowa City VA Healthcare System, Iowa City, Iowa, USA.

20. Department of Pathology, University of Iowa Carver College of Medicine, Iowa City, Iowa, USA.

21. VA Boston Healthcare System, Boston, Massachusetts, USA.

22. Department of Medicine, Harvard Medical School, Boston, Massachusetts, USA.

23. Department of Veterans Affairs, New Jersey Health Care System, East Orange, New Jersey, USA.

Publisher

Mary Ann Liebert Inc

Subject

Health Information Management,Public Health, Environmental and Occupational Health,Health Policy,Health (social science)

Link

https://www.liebertpub.com/doi/pdf/10.1089/heq.2023.0037

Reference29 articles.

1. Hidden in Plain Sight — Reconsidering the Use of Race Correction in Clinical Algorithms

2. Reconsidering Race Adjustment in Prenatal Alpha-Fetoprotein Screening

3. 3. National Academies of Sciences, Engineering, and Medicine; Division of Behavioral and Social Sciences and Education; Health and Medicine Division; et al. Using Population Descriptors in Genetics and Genomics Research: A New Framework for an Evolving Field. National Academies Press (US): Washington, DC; 2023.

4. Race, Genotype, and Azathioprine Discontinuation

5. Big Data Analytics and the Struggle for Equity in Health Care: The Promise and Perils

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1. Reply to: [Letter to the Editor];Health Equity;2024-05-01