Current use and evaluation of artificial intelligence and predictive models in US hospitals

Current use and evaluation of artificial intelligence and predictive models in US hospitals
Health Affairs; by Paige Nong, Julia Adler-Milstein, Nate C. Apathy, A. Jay Holmgren, Jordan Everson; 1/25
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 of US hospitals used predictive models, and 79 percent of those used models from their electronic health record developer.
Publisher's note: It would be interesting if hospices collected and reported similar information.