From Health 201AI Med Risk

documented ai-in-healthcare failures — what went wrong, why, and what might have helped, synthesised from public sources


EFF records: Medicare's WISeR AI prior-authorization pilot missed deadlines by up to 83 days and drew reports of patients left in pain

What happenedCMS's Wasteful and Inappropriate Service Reduction (WISeR) model launched in January 2026 and is set to run until 2031. In six states (New Jersey, Ohio, Oklahoma, Texas, Arizona and Washington), traditional Medicare providers must get prior approval for 13 services, including skin substitutes, epidural injections and kyphoplasty. Private vendors use AI systems to evaluate those requests. More than 1,000 pages of records that the Electronic Frontier Foundation obtained through a FOIA lawsuit against CMS were published on 8 September 2026. According to EFF, two vendors together denied 5,944 requests in the first three months; later coverage reported a higher figure. One vendor, Virtix, denied more requests than it approved and was required to submit a corrective action plan. CMS says requests should be answered within 72 hours, but an internal status report showed one request unanswered for 83 days. Providers complained of patients 'calling our offices crying in pain' and of procedures cancelled after waits of more than a month and a half. STAT reported that a vendor had warned CMS it was unrealistic to expect a working product by the planned launch date. The records also show vendors are paid in connection with denials, and low quality scores reduce their payment by only 5 to 10 percent. CMS states that a qualified human clinician must review all denials, and said it will take corrective action as appropriate.

Failure modeAn AI-driven coverage review was launched quickly at scale with weak vendor readiness and payment incentives tied to denials. The result was high denial rates and processing delays far beyond the stated 72-hour standard, which delayed time-sensitive procedures, while the AI's role and methods stayed largely undisclosed.

What might have helpedEFF and other commentators point out that the clinician-review requirement may mean little if AI recommendations shape human decisions; tracking how often reviewers overturn AI recommendations could show whether that review is a real check. Independent, published monitoring of denial rates, overturn-on-appeal rates and turnaround times from launch could have exposed the delays and one vendor's outlier denial rate sooner. Separating vendor pay from denials, and confirming that a system works before go-live (a vendor reportedly warned it would not), could also have reduced the risk.

Mitigation: no published fix or mitigation found so far. Checked monthly; see what was tried elsewhere.

Sources: eff.org · statnews.com · medicaldaily.com · newsweek.com · sources re-checked 2026-10-11
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