Medicare may ease path to coverage for ´breakthrough´ artificial intelligence medical devices

If passed, new legislation could grant many Artificial Intelligence-based healthcare devices swift Medicare reimbursement, but some experts question if the evidence will keep pace with rapid adoption.

Medical device lobbyists and lawmakers are rallying behind new legislation designed to simplify Medicare reimbursement for artificial intelligence-based devices in healthcare. The momentum reflects broad industry frustration: many algorithm-powered medical tools have received Food and Drug Administration clearance but have struggled to win coverage from Medicare. Advocates hope that fresh legislative proposals will make it easier for so-called ´algorithm-based health services´ to be widely used in clinical practice, overcoming reimbursement hurdles that have slowed adoption to date.

Some products could go even further if a particular regulatory track is realized. Since the first Trump administration, the idea of automatic Medicare coverage for ´breakthrough´ devices—those designated by the FDA as innovations addressing unmet medical needs—has been floated by both policy makers and regulators. The Centers for Medicare and Medicaid Services (CMS) once proposed granting up to four years of coverage for such FDA-authorized breakthrough devices, though that rule was later withdrawn. The idea is surfacing again in recent bills, enjoying support from key health agency leaders.

FDA commissioner Marty Makary and CMS administrator Mehmet Oz have both signaled their interest in coordination between the two agencies. Their aim is to launch immediate Medicare reimbursement for FDA-cleared ´breakthrough´ devices—especially those powered by artificial intelligence—thus allowing firms to bypass duplicative and lengthy separate CMS evaluation processes. This shift is designed to ensure prompt patient access to innovative diagnostics and treatments. However, critics warn that such a streamlined path may grant coverage to devices lacking robust evidence of real-world clinical benefit. As the field of artificial intelligence in healthcare continues to expand—with recent examples including an algorithm for detecting aortic stenosis and an artificial intelligence urine test for early bladder cancer—the debate over clinical validation versus rapid deployment only grows more urgent.

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