The Enduring Burden of Prior Authorization
Prior authorization, a protocol requiring healthcare providers to obtain approval from insurers before rendering certain services, medications, or procedures, has long been a contentious issue within the American healthcare system. Its original intent was to serve as a vital check on overuse, prevent unnecessary spending, and guide patients toward more cost-effective yet equally efficacious treatments. However, its implementation has frequently devolved into a labyrinthine bureaucratic hurdle, imposing significant distress on patients and substantial administrative overhead on medical practices.
Personal accounts vividly illustrate the human toll of this process. Stories abound of patients enduring prolonged periods of uncertainty, navigating complex paperwork, and battling insurers to gain approval for physician-recommended care. These tribulations often involve crucial prescription medications, diagnostic tests, or life-saving surgical procedures. A substantial majority of physicians, as highlighted by various surveys, voice significant concerns that prior authorization processes lead to dangerous care delays, which can compel patients to abandon vital treatments while awaiting an insurer’s verification of eligibility and medical necessity. When care is denied, patients are left with the option to appeal, a process that demands further time and effort, often with no guarantee of success.
Efforts Towards Reform and Streamlining
Recognizing the widespread dissatisfaction and documented negative impacts, both governmental bodies and private insurers have undertaken initiatives to ameliorate the prior authorization system. In 2024, former President Joe Biden’s administration issued a significant rule aimed at reforming prior authorization for government-run health plans. This regulation mandated specific timelines for insurers to issue prior authorization decisions: 72 hours for urgent requests and seven calendar days for non-urgent requests. These critical timeline requirements officially came into effect on January 1 of this year for most public sector health plans, including Medicare Advantage, Medicaid, and plans on the Affordable Care Act (ACA) marketplace. The goal was to inject much-needed efficiency and predictability into a system notorious for its delays.
Concurrently, in 2025, the Trump administration, alongside major insurers, pledged to further streamline and accelerate prior authorization processes across the board. Key commitments from private insurance companies included a vow to standardize electronic requests by 2027 and, more immediately, to "reduce the volume of medical services subject to prior authorization" by 2026. This reduction targeted common procedures such as colonoscopies and cataract surgeries, signaling an acknowledgment from the industry that too many services were being subjected to the authorization burden. Early industry-based surveys suggest some movement, with reports indicating an 11 percent decline in prior authorization requests between June 2025 and April 2026. However, the critical question of whether the denial rate has decreased remains largely unanswered, casting a shadow of uncertainty over the true impact of these changes.
The Advent of AI: The WISeR Model
Despite these efforts, the Trump administration has embarked on a more radical approach: integrating artificial intelligence into the prior authorization framework, particularly within Original Medicare. This year, the Centers for Medicare and Medicaid Services (CMS) launched a demonstration project called WISeR, an acronym for Wasteful and Inappropriate Service Reduction Model. The WISeR model, which is slated to run through December 2031 across six states (the specific states include Florida, Georgia, Illinois, Michigan, North Carolina, and Ohio, chosen for their high volume of specific service utilization and claims data), leverages AI to identify and reduce waste and fraud in Original Medicare, ultimately aiming to decrease unnecessary procedures.
Historically, prior authorization has been extensively utilized in Medicare Advantage (MA) plans—the privately run alternative to original Medicare that now covers approximately 55 percent of Medicare-eligible seniors and disabled individuals. However, its deployment in Original Medicare has been rare, making the WISeR model a significant paradigm shift. The model combines advanced technologies like machine learning with human clinical review to evaluate services deemed vulnerable to overuse, fraud, and abuse. Initial targets include complex areas such as skin and tissue substitutes, electrical nerve stimulator implants, and knee arthroscopy for knee osteoarthritis. CMS asserts that by integrating AI, the WISeR model will "ensure timely and appropriate Medicare payment for select items and services."
Rising Concerns and Criticisms
The introduction of AI into prior authorization, particularly with the WISeR model, has been met with substantial apprehension and outright opposition from various stakeholders. The American Medical Association (AMA) has been a vocal critic, advocating for greater transparency regarding AI algorithms and demanding that insurers provide detailed clinical reasoning to justify any denials of coverage. An AMA survey of physicians in 2025 revealed widespread concern, with 61 percent of doctors worrying that AI would exacerbate denials of what they consider medically necessary treatments.
Health policy analyst Camm Epstein encapsulated a prevalent sentiment in an email to Undark, stating that "AI should be used to make appropriate care easier to approve, not necessary care easier to deny." This sentiment underscores a fundamental fear: that AI, rather than serving as an efficiency tool, could become a more potent gatekeeper, further restricting access to care.
Early observations from the WISeR pilot states have reinforced these anxieties. Wendell Potter, a prominent advocate for health insurance reform and former Cigna executive, covered the political pushback against the model on his Substack publication "HEALTH CARE un-covered." In the same publication, Zena Wolf, a researcher with the Center for Health & Democracy, cited investigations by leading news outlets such as The Washington Post, KFF Health News, and The Seattle Times, which suggested that in its initial months, the WISeR model has already led to care delays and denials in some instances across the six pilot states. This contradicts the stated goal of timely payments and suggests that even with automated processes, the administrative burden on healthcare providers may remain high, or even increase, as they grapple with appeals and denials.
A particularly contentious aspect of the WISeR model is the financial incentive structure for participating vendors. These vendors, hired to execute the AI-driven prior authorization, earn a share of what CMS refers to as "averted expenditures." This arrangement creates a direct financial motivation for vendors to reject care requests, sparking long-standing concerns about profit-making being linked to discouraging patients from receiving medically necessary care. This conflict of interest has prompted several lawmakers to introduce resolutions and amendments aimed at blocking funding for the WISeR model, citing grave threats to patient access and the potential for financially driven denial strategies.
A Dichotomy in Policy: The Trump Administration’s Dual Stance
The Trump administration’s approach to prior authorization appears to operate with a degree of internal contradiction. On one hand, it is expanding the use of AI and prior authorization in Original Medicare through the WISeR model, a move that critics argue could increase denials. On the other hand, the administration has publicly pressured private insurers, including Medicare Advantage plans, to reduce and streamline their prior authorization processes. CMS Administrator Mehmet Oz notably issued a stern warning to insurance company executives: "If you don’t do it yourselves, then we’re going to do it for you," signaling a readiness to impose federal regulation if industry-led reforms are insufficient.
In response to this governmental pressure, health plans have released data suggesting compliance. The aforementioned industry survey indicated an 11 percent reduction in prior authorization requests. Furthermore, insurers have pledged greater transparency around the clinical reasoning underlying prior authorization decisions and affirmed that "AI or algorithms without clinician or practitioner review are not used to deny prior authorization requests that involve medical necessity or clinical considerations." This commitment aims to alleviate concerns about decisions being made solely by algorithms, without human oversight.
However, skepticism persists. As KFF has noted, public prior authorization data often falls short on insight, particularly regarding actual denial rates. Without this crucial information, it remains challenging to ascertain whether the system is truly improving for patients or simply shifting the burden. Physician Jared Dashevsky, founder of Healthcare Huddle, articulates this frustration succinctly: "AI could eliminate barriers, reduce administrative waste, give us more time with patients. But that’s not what’s being built." Instead, he warns of an "arms race to deny faster and appeal faster. More automation of a broken system that shouldn’t exist in its current form."
Broader Implications and the Path Forward
The integration of AI into prior authorization represents a pivotal moment for healthcare. It highlights the fundamental tension between the imperative to control spiraling healthcare costs and the ethical obligation to ensure timely and equitable patient access to medically necessary care. While AI holds undeniable potential for efficiency and accuracy in processing unambiguous claims, its deployment within a system characterized by complex medical necessity determinations, financial incentives, and significant power imbalances raises serious questions.
The experiences within Medicare Advantage offer a cautionary tale. Federal government reports, including those from the HHS Office of Inspector General (OIG), have repeatedly pointed to instances where MA plans denied beneficiaries access to services despite apparent compliance with coverage rules. Although MA plans reportedly overturned 81 percent of denials upon appeal in 2024, the initial denial itself creates significant stress, delays, and potential harm for patients. Erecting obstacles to medically appropriate care, especially when linked to profit motives, remains a profound area of concern. A newly released Commonwealth Fund survey in June 2026 found that approximately one in five American working-age adults with private insurance reported experiencing a denial of coverage for physician-recommended medical care in 2025. Of those denied, 41 percent reported delayed care, and over a quarter stated their health problem worsened as a result.
As AI systems become more sophisticated, the need for robust regulatory frameworks, transparent algorithms, and strong ethical guidelines becomes paramount. Oversight must ensure that AI tools genuinely serve to facilitate appropriate care rather than becoming tools for cost containment that inadvertently jeopardize patient well-being. The current debate surrounding AI in prior authorization underscores the urgent need for a holistic approach that prioritizes patient outcomes, clinician autonomy, and system integrity over purely financial metrics. Without careful calibration and stringent accountability, the promise of AI in healthcare risks being overshadowed by the unintended consequences of an overly automated, profit-driven system.
