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Overcoming Medical Overuse with AI Assistance: An Experimental Investigation

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  • Ziyi Wang
  • Lijia Wei
  • Lian Xue

Abstract

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. Diagnostic accuracy improved by 17% to 37%, depending on the incentive scheme. Adoption of AI advice was high, with approximately half of the participants modifying their decisions based on AI input across all settings. For policy implications, we quantified the monetary (57%) and non-monetary (43%) incentives of overtreatment and highlighted AI's potential to mitigate non-monetary incentives and enhance social welfare. Our results provide valuable insights for healthcare administrators considering AI integration into healthcare systems.

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  • Ziyi Wang & Lijia Wei & Lian Xue, 2024. "Overcoming Medical Overuse with AI Assistance: An Experimental Investigation," Papers 2405.10539, arXiv.org.
    • Handle: RePEc:arx:papers:2405.10539
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    1. Kohei Kawaguchi, 2021. "When Will Workers Follow an Algorithm? A Field Experiment with a Retail Business," Management Science, INFORMS, vol. 67(3), pages 1670-1695, March.
    2. Ann-Kathrin Heider & Harald Mang, 2020. "Effects of Monetary Incentives in Physician Groups: A Systematic Review of Reviews," Applied Health Economics and Health Policy, Springer, vol. 18(5), pages 655-667, October.
    3. Shane Frederick, 2005. "Cognitive Reflection and Decision Making," Journal of Economic Perspectives, American Economic Association, vol. 19(4), pages 25-42, Fall.
    4. Jeffrey Clemens & Joshua D. Gottlieb, 2014. "Do Physicians' Financial Incentives Affect Medical Treatment and Patient Health?," American Economic Review, American Economic Association, vol. 104(4), pages 1320-1349, April.
    5. Liran Einav & Amy Finkelstein & Neale Mahoney, 2018. "Provider Incentives and Healthcare Costs: Evidence From Long‐Term Care Hospitals," Econometrica, Econometric Society, vol. 86(6), pages 2161-2219, November.
    6. Lu, Fangwen, 2014. "Insurance coverage and agency problems in doctor prescriptions: Evidence from a field experiment in China," Journal of Development Economics, Elsevier, vol. 106(C), pages 156-167.
    7. Carolina Lopez & Anja Sautmann & Simone Schaner, 2018. "The Contribution of Patients and Providers to the Overuse of Prescription Drugs," NBER Working Papers 25284, National Bureau of Economic Research, Inc.
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