For the past two years, 83-year-old Keith Magnuson has been grappling with severe pain due to lumbar spinal stenosis, a debilitating back condition that makes even simple tasks unbearable. Previously an avid rock climber and hiker, he now struggles to unload his dishwasher without discomfort.
"I’m in pain every time I’m on my feet," Magnuson, a resident of Seattle, lamented. Thankfully, his doctor proposed a minimally invasive procedure called lumbar decompression (MILD), which poses a lower risk than traditional surgery and is covered by Medicare for patients over 65. However, Magnuson faced a hurdle: an epidural steroid injection, part of his treatment plan, was denied by Medicare.
Despite his doctors submitting additional requests with further documentation, the denial persisted. It was only during the third rejection that he learned the decision was made not by a medical professional, but by artificial intelligence. “I was outraged,” Magnuson remarked. “It’s AI making these decisions?”
Magnuson's situation isn't an isolated incident. Across six states in the U.S.—Washington, Arizona, New Jersey, Ohio, Oklahoma, and Texas—Medicare enrollees are discovering that AI programs are determining their eligibility for specific treatments. This pilot program, initiated by the U.S. Department of Health and Human Services (HHS), aims to assess whether AI can curb excessive spending within Medicare by denying “unnecessary” medical procedures.
Medicare, a public health insurance program mainly for seniors and some individuals with disabilities, is a significant component of federal spending, accounting for about 14 percent. The program has initiated this AI endeavor as part of a broader initiative to minimize costs and prevent inappropriate treatment recommendations, especially after a report suggested that up to $5.8 billion in Medicare spending in 2022 was deemed wasteful.
This pilot program, known as the Wasteful and Inappropriate Service Reduction (WISeR) Model, requires healthcare providers to submit justifications online for particular treatments. A third-party AI assesses these submissions to decide whether they meet Medicare criteria.
Magnuson represents just one case among many, as the implementation of the WISeR initiative has led to significant complications. Medical providers are experiencing technical difficulties, prolonged wait times, and unexpected treatment denials. Hospitals often find themselves inundated with additional paperwork and the need to bring patients in for more appointments. Approval for procedures has transitioned from a matter of days to potentially weeks, leaving patients like Magnuson in severe discomfort.
"This was presented to us as something that would revolutionize the process, ensuring swift approvals," explained Jeb Shepard, director of policy at the Washington State Medical Association. In reality, however, patients are frequently waiting weeks, a situation especially detrimental for the elderly, whose health can deteriorate rapidly without prompt care.
Despite some tech companies offering timely assistance regarding care denials, others have proven to be unresponsive, leaving physicians frustrated. Dr. Jeff Marr, a health economist, described the AI decision-making process as a "complete black box," highlighting the lack of transparency around how these systems operate.
The WISeR program scrutinizes 15 types of treatments, including epidural steroid injections, and necessitates prior authorization from the AI each time a doctor prescribes one. While the Centers for Medicare and Medicaid Services (CMS) claims doctors should receive results within 72 hours, the reality has been far more tangled. Health professionals complain that this added layer of AI oversight complicates an already simplified approval process, turning it cumbersome.
Critics argue that AI should not dictate treatment approvals, with Dr. Steve Aydin, a pain specialist in New Jersey, asserting that medical decisions require a clinician’s nuanced understanding of a patient’s individual experience. Many physicians express concerns that the deployment of AI lacked adequate consultation, leading to administrative obstacles and patient delays.
Michelle Mello, a professor of health policy, notes that this program was rolled out without Congressional approval, allowing the administration to bypass a formal procedure due to its voluntary nature for tech companies. Nevertheless, the program is mandatory for doctors, who risk losing Medicare funding without participation.
As the effects of the WISeR program become apparent, many have expressed their worries that the payment structures for AI services could inadvertently encourage unnecessary care denials. Frustrations mount as patients consistently face delays in receiving much-needed medical attention.
In this context, individuals like Magnuson have taken measures into their own hands, sometimes opting to pay for treatments out of pocket, even when it leads to uncertainty about reimbursement. Magnuson’s plea highlights the systemic issues within the rollout of AI in Medicare, urging for a reconsideration of how such technology is implemented in healthcare.
While many within the medical community acknowledge the potential benefits of AI—such as improving diagnostic accuracy—there is a pervasive concern about entrusting crucial decision-making solely to machines, devoid of human judgment. The challenge ahead will be ensuring AI serves as a complement to human expertise rather than a replacement, particularly when patient lives are at stake.
