报销
付款
互操作性
医疗保健
衡平法
人工智能应用
医学
计算机科学
人工智能
风险分析(工程)
业务
经济
财务
政治学
法学
经济增长
操作系统
作者
Ravi B. Parikh,Lorens A. Helmchen
标识
DOI:10.1038/s41746-022-00609-6
摘要
Over the past 7 years, regulatory agencies have approved hundreds of artificial intelligence (AI) devices for clinical use. In late 2020, payers began reimbursing clinicians and health systems for each use of select image-based AI devices. The experience with traditional medical devices has shown that per-use reimbursement may result in the overuse use of AI. We review current models of paying for AI in medicine and describe five alternative and complementary reimbursement approaches, including incentivizing outcomes instead of volume, utilizing advance market commitments and time-limited reimbursements for new AI applications, and rewarding interoperability and bias mitigation. As AI rapidly integrates into routine healthcare, careful design of payment for AI is essential for improving patient outcomes while maximizing cost-effectiveness and equity.
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