Unless payment models are updated, AI could drive up healthcare costs without boosting patient outcomes, a researcher at Philadelphia-based University of Pennsylvania says.
To avoid overspending and ensure benefits, policymakers may need new frameworks that tie AI reimbursement more closely to proven clinical effectiveness rather than just usage or cost, according to Amol Navathe, MD, PhD, a senior fellow at the Penn Leonard Davis Institute of Health Economics and professor of medical ethics, health policy and healthcare management at Penn. He co-wrote a commentary on the topic in January for Health Affairs.
“In these many situations where AI increases productivity without necessarily improving accuracy or outcomes, or when AI can perform services autonomously, current payment paradigms that reimburse based on human labor inputs like time and skill just don’t fit well,” he said in an April 8 blog post. “This may lead to overspending and overuse, which must be balanced with the health benefits of access to the technologies.”
Hospitals are currently paid a fixed price under the Outpatient Prospective Payment System and the Inpatient Prospective Payment System, based on healthcare services delivered, including those assisted by AI, Dr. Navathe stated. Technologies also receive supplemental reimbursement through the pass-through payment system for outpatient care and a new technology add-on payment for inpatient care. But he said policymakers need to find more permanent solutions, either through current Medicare policy or by granting CMS new authority to consider clinical effectiveness for AI-related reimbursement.
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