AI-driven CMS pilot model could slow ASC care despite fraud-fighting goals

Editor's Note

The Centers for Medicare & Medicaid Services (CMS) is enlisting artificial intelligence (AI) to combat wasteful spending, but ambulatory surgery centers (ASCs) warn the plan could slow care and increase administrative strain, Ambulatory Surgery Center News October 20 reports. The agency’s new Wasteful and Inappropriate Service Reduction (WISeR) Model will launch on January 1, 2026, as a 6-year voluntary test in six states: New Jersey, Ohio, Oklahoma, Texas, Arizona, and Washington.

The WISeR model targets services that CMS says are at higher risk of misuse, including skin and tissue substitutes, electrical nerve stimulator implants, and knee arthroscopy for osteoarthritis. Using AI and machine learning, CMS will review whether requests for these services meet Medicare’s existing coverage standards. While the agency emphasizes WISeR does not alter coverage or payment policies, it will introduce prior authorization requirements and post-service reviews intended to flag fraud, waste, and abuse.

CMS cites wasteful or inappropriate care as accounting for up to 25% of US health spending, with Medicare paying $5.8 billion for such services in 2022. Yet industry experts quoted in the article expressed concern that AI-driven review could disrupt care delivery. Wes Battiste of Avanza Healthcare Strategies said the model risks undermining physicians’ ability to provide timely care, since AI—not clinicians—will decide if procedures are appropriate. Although denied cases can be appealed to human reviewers, Battiste questioned whether those reviewers will have relevant specialty expertise.

Michael McClain of LeftCoast Healthcare Advisors cautioned the program may function more as a cost-control mechanism than a true fraud prevention effort. He noted several high-fraud states, including New York and California, are excluded from the pilot. McClain also raised concerns about the lack of governance over AI tools used in clinical decision-making, describing the technology as “unproven” and lacking transparency around performance and oversight.

For ASCs, the model could reshape daily operations. Additional documentation, delayed reimbursements, and prolonged authorizations could reduce efficiency and potentially affect staffing levels. As Battiste noted, delays tied to prior authorization could lower case volumes below cost-efficient thresholds.

If implemented as planned, the WISeR model will test not only AI’s ability to identify inappropriate care but also how much automation the nation’s outpatient surgery sector can absorb without compromising patient access and operational stability.