Targeting Machine Learning and Artificial Intelligence Algorithms in Health Care to Reduce Bias and Improve Population Health-Reference-Cited by-同舟云学术

Targeting Machine Learning and Artificial Intelligence Algorithms in Health Care to Reduce Bias and Improve Population Health

Published:2024-08-08 Issue: Volume: Page:
ISSN:0887-378X
Container-title:The Milbank Quarterly
language:en
Short-container-title:Milbank Quarterly

Author:

HURD THELMA C.¹²^ORCID,COBB PAYTON FAY³⁴^ORCID,HOOD DARRYL B.⁵^ORCID

Affiliation:

1. Institute on Health Disparities, Equity, and the Exposome, Meharry Medical College

2. School of Social Sciences, Humanities and Arts University of California Merced

3. School of Arts and Sciences Rutgers University–Newark

4. North Carolina State University

5. College of Public Health The Ohio State University

Abstract

Policy Points

Artificial intelligence (AI) is disruptively innovating health care and surpassing our ability to define its boundaries and roles in health care and regulate its application in legal and ethical ways. Significant progress has been made in governance in the United States and the European Union.

It is incumbent on developers, end users, the public, providers, health care systems, and policymakers to collaboratively ensure that we adopt a national AI health strategy that realizes the Quintuple Aim; minimizes race‐based medicine; prioritizes transparency, equity, and algorithmic vigilance; and integrates the patient and community voices throughout all aspects of AI development and deployment.

Publisher

Wiley

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/1468-0009.12712

Reference102 articles.

1. SchneiderEC ShahA DotyMM TikkanenR FieldsK WilliamsRDII.Mirror mirror 2021: reflecting poorly: health care in the U.S. compared to other high‐income countries.The Commonwealth Fund. August 4 2021. Accessed August 1 2024.https://commonwealthfund.org/publications/fund‐reports/2021/aug/mirror‐mirror‐2021‐reflecting‐poorly

2. GlassmanJK.Health care providers are raking in profits by exploiting programs meant for the poor.The Hill. July 18 2023. Accessed August 5 2024.https://thehill.com/opinion/healthcare/4101826‐health‐care‐providers‐are‐raking‐in‐profits‐by‐exploiting‐programs‐meant‐for‐the‐poor/

3. DallT ReynoldsR ChakrabartiR RuttingerC ZarekP ParkerO;GlobalData.The Complexities of Physician Supply and Demand: Projections from 2021 to 2036.Association of American Medical Colleges;2024.

4. GoochK.6 predictions for the future healthcare workforce.Becker's Hospital Review. December 17 2021. Accessed April 19 2024.https://beckershospitalreview.com/workforce/6‐predictions‐for‐the‐future‐healthcare‐workforce.html?oly_enc_id=9174C2123745F8T

5. NHE fact sheet.Centers for Medicare and Medicaid Services. Updated June 16 2024. Accessed July 31 2024.https://www.cms.gov/data‐research/statistics‐trends‐and‐reports/national‐health‐expenditure‐data/nhe‐fact‐sheet