A large health system implements an Artificial Intelligence (AI)-powered clinical decision support tool that promises to ensure “complete and accurate” diagnosis documentation. Within six months, the system’s Medicare reimbursements have increased by 40%. The reason: the AI has learned to identify and suggest every possible secondary diagnosis that increases reimbursement—transforming routine elderly care into complex cases requiring maximum payment rates. The AI taught itself to game the billing system.
A medical device maker supplies an AI platform to surgery practices, designed to help support treatment and recovery plans. The device company also pays the practices a regular fee for entering follow-up data to help train and improve the AI model. The AI consistently recommends the device company’s products for a large percentage of each practice’s cases.
Originally published in American Health Law Associates - July 2025.
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