Insurers, Medicare Use AI to Deny Claims, Sparking Lawsuits and Patient Harm

Artificial intelligence programs are increasingly being used by private health insurers and government programs to make decisions about medical claims, a practice that has led to numerous lawsuits and reports of patients being denied necessary care.

Major insurers like UnitedHealth Group, Humana, and Cigna are facing class-action lawsuits accusing them of using AI to automatically deny payments for treatments and care, even when doctors deem them medically necessary. These legal challenges allege that the AI systems, such as UnitedHealth's nH Predict, are followed so rigidly that human reviewers have little discretion, leading to claim denials after short periods of rehabilitation or treatment.

One complaint details the case of Gene Lokken, an elderly man who allegedly had his nursing home care denied by UnitedHealth's AI after just two weeks, despite his doctor's assessment that he still required extensive rehabilitation. His family was forced to pay thousands of dollars out-of-pocket monthly for his care until his death. Similar allegations are leveled against Humana regarding the same AI program and against Cigna for using a different algorithm that allegedly allowed for mass denials of claims without individual review.

"From their perspective, you might as well have been speaking Esperanto. They just had no idea what it was that was being said to them when they were being told. They usually heard about it for the first time when they were being told that they needed to leave," said Glenn Danas, an attorney representing plaintiffs in these cases. "They just had no idea what was going on or why this was being done to them."

These private insurer practices have drawn parallels to a new program launched by the Trump administration for traditional Medicare. The WISeR (Wasteful and Inappropriate Service Reduction) model, which began in January, uses AI and machine learning to adjudicate prior authorization decisions for certain procedures in six states. While intended to ensure appropriate Medicare payment, the program has also faced criticism from patient advocates and physicians.

Reports indicate that the WISeR model has led to delayed care and denials for medically necessary services. Documents obtained by the Electronic Frontier Foundation through a Freedom of Information Act request revealed aggressive denials, with one company using the AI model denying more requests than it approved. Delays were also common, with one review taking 83 days when the model was supposed to decide within 72 hours.

"We have patients calling our offices crying in pain because their procedures are being delayed while awaiting approvals or guidance tied to this model," one doctor wrote in federal documents. "A 3-4 day delay for necessary pain procedures is already difficult for vulnerable patients, but when providers cannot obtain answers for weeks, the situation becomes unacceptable."

Experts note that while AI has the potential to streamline healthcare administration, its rapid deployment in critical decision-making processes outpaces regulatory oversight. Defining what constitutes meaningful human review in AI-driven insurance decisions remains an unsolved problem for policymakers.

"I think everyone agrees at a high level of generality, ‘Yes, AI should be used to enhance human review and not to replace it,’ but no one actually knows how to write rules to enforce it," said Daniel Schwarcz, a law professor at the University of Minnesota. "It is incredibly hard to specify in rules or regulations a standard that is verifiable and enforceable."

In the absence of comprehensive regulation, legal experts and patient advocates advise individuals to appeal any denied claims, as many are overturned on appeal. Some states and lawmakers in Congress are beginning to propose measures for transparency and human involvement in AI-driven insurance claims, but the widespread adoption and flexibility of these technologies present significant challenges for effective regulation. In the meantime, the profit incentive for companies to utilize these AI tools remains a strong driving force.