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Your doctor recommends pain treatment, but Medicare’s AI may have a different opinion.

Your doctor recommends pain treatment, but Medicare's AI may have a different opinion.

Changes to Medicare Approval Process Could Lengthen Wait Times for Treatment in Ohio

CLEVELAND, Ohio — Ohioans on Medicare who depend on steroid injections for pain management might face longer waits for treatment next year. This change comes as new pilot programs will require prior approval for certain healthcare claims submitted to traditional Medicare, a shift from current practices aimed at curbing waste and fraud.

Ohio is one of six states participating in a model designed to reduce inappropriate healthcare services. A six-year pilot program is set to begin in January. Concerns have been raised in Congress regarding its funding.

Organizations representing physicians and patients have criticized the initiative, predicting that it will restrict and delay healthcare access for older individuals. There is significant worry about the decisions made regarding care, especially with the involvement of AI.

“We’re saving costs at the expense of our patients,” said Charlotte Rudolph from the Ohio Universal Healthcare Action Network. Her advocacy group highlights that Medicare enrollees are among the most vulnerable populations in Ohio, and even the thought of these procedural changes adds unnecessary stress to patients.

Judith Stein, who leads the Centers for Medicare Advocacy, echoed similar sentiments. She pointed out that the new approval process could create barriers between healthcare providers’ recommendations and what patients actually receive based on algorithmic decisions.

The pilot will focus on specific procedures like skin and tissue replacements, knee arthroscopy, and pain management injections, among others. Notably, services like hospital stays and emergency care are not part of this initiative.

According to federal statistics, these targeted services accounted for up to $5.8 billion in spending in 2022. Medicare, the federal health insurance program for those over 65 and certain younger individuals with disabilities, has over 2.5 million enrollees in Ohio.

While there are potential benefits to prior approval, such as reducing unnecessary treatments, critics argue it causes delays in care and increases out-of-pocket costs for patients. Reports indicate that one in five insured individuals experienced claim denials over a year, with private insurance having higher rejection rates than Medicare or Medicaid.

The public’s dissatisfaction with denied claims was highlighted in a social media post featuring UnitedHealthcare CEO Brian Thompson. The company is currently facing lawsuits claiming that it improperly used AI to deny care to elderly patients.

Medicare’s suggested changes are blurring the lines between traditional Medicare and Medicare Advantage plans, which typically require prior authorization for services. Currently, original Medicare does not mandate this process, while more than half of Ohio enrollees are in Medicare Advantage.

Some advocates see these changes as a backdoor method to funnel patients into Medicare Advantage plans, potentially restricting the freedoms offered by traditional Medicare, as Carrie Graham points out. Last year, about 12% of denied pre-approvals in Medicare Advantage plans were appealed, with a vast majority being overturned. However, many patients do not contest denials due to the complexities involved.

Reports suggest that health insurers are increasingly using AI to make decisions regarding service approvals. While officials claim that denials within the Medicare pilot will be evaluated by licensed clinicians, some studies indicate that AI may increase denial rates and worsen existing health disparities.

Critics also note the financial incentives for companies involved in the pilot, as they profit from the savings generated by rejected claims. “Using AI feels like a way to introduce electronic oversight that could limit coverage,” Stein commented.

She added that she often sees clinicians reinforcing AI decisions about care coverage, but her experience suggests this doesn’t seem to happen consistently in practice.

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