Overcoming Medical Overuse with AI Assistance: An Experimental Investigation

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This study evaluates the effectiveness of Artificial Intelligence (AI) in mitigating medical overtreatment, a significant issue characterized by unnecessary interventions that inflate healthcare costs and pose risks to patients.

• We conducted a lab-in-the-field experiment at a medical school, utilizing a novel medical prescription task, manipulating monetary incentives and the availability of AI assistance among medical students using a three-by-two factorial design.
• We tested three incentive schemes: Flat (constant pay regardless of treatment quantity), Progressive (pay increases with the number of treatments), and Regressive (penalties for overtreatment) to assess their influence on the adoption and effectiveness of AI assistance.
• Our findings demonstrate that AI significantly reduced overtreatment rates by up to 62% in the Regressive incentive conditions where (prospective) physician and patient interests were most aligned.