Health Affairs January 1, 2025
Paige Nong, Julia Adler-Milstein, Nate C. Apathy, A. Jay Holmgren, Jordan Everson

Abstract

Effective evaluation and governance of predictive models used in health care, particularly those driven by artificial intelligence (AI) and machine learning, are needed to ensure that models are fair, appropriate, valid, effective, and safe, or FAVES. We analyzed data from the 2023 American Hospital Association Annual Survey Information Technology Supplement to identify how AI and predictive models are used and evaluated for accuracy and bias in hospitals. Hospitals use AI and predictive models to predict health trajectories or risks for inpatients, identify high-risk outpatients to inform follow-up care, monitor health, recommend treatments, simplify or automate billing procedures, and facilitate scheduling. We found that 65 percent...

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Topics: AI (Artificial Intelligence), Health System / Hospital, Provider, Technology
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