One such instance that highlights the growing challenges occurred when Yolanda Troublefield, MD, JD, an attending surgeon and otolaryngologist at Southcoast Physicians Group in Massachusetts and a member of the American Academy of Otolaryngology–Head and Neck Surgery’s Physician Payment and Policy Workgroup, sought prior authorization for an eight-year-old child requiring an adenoidectomy with ear tube placement. The child had a history of recurrent otitis media, with documented infections from both primary care and otolaryngology, further supported by audiogram results. Even with the patient’s parents being medical professionals familiar with the standard of care, the insurance company denied the request. Dr. Troublefield suspects the denial stemmed from the AI system’s interpretation of the medical documentation. Specifically, while the diagnosis was "recurrent otitis media," a portion of the assessment-and-plan section of the note inadvertently read "acute otitis media." This seemingly minor discrepancy, potentially overlooked by an AI that may not fully grasp the nuances of clinical documentation, led to the denial, necessitating a potentially time-consuming peer-to-peer conversation and delaying necessary treatment for the child.
Denials at Machine Speed: The AI Effect on Prior Authorization
The advent of AI in prior authorization and clawback processes for services already rendered is leading to a dramatic increase in claim denials. Physicians report these denials are occurring at an unprecedented speed and often in perplexing ways. This forces healthcare professionals to dedicate more time and resources to secure coverage for medically necessary treatments, leading to widespread exasperation. Practices are increasingly relying on AI to both submit documentation to insurers and to formulate responses to denials, creating an automated exchange with uncertain long-term consequences for the healthcare system.
"What we’re seeing is faster denial of claims because of the use of AI," stated Dr. Troublefield. "You can set the dial in different ways. You can set it high, medium, or low. And they’re set high for denials." This sentiment is echoed by a significant portion of the medical community. A survey conducted by the American Medical Association (AMA) last year revealed that 60% of physicians are concerned that AI is already increasing or will increase prior authorization denial rates. Furthermore, 55% of physicians reported that prior authorization delays access to necessary care either always or often, and a staggering 79% indicated that prior authorization sometimes leads to patients abandoning treatment altogether. Perhaps most alarmingly, 26% of physicians reported that prior authorization has resulted in a serious adverse event for a patient under their care.
Bruce Scott, MD, a former president of the AMA and an otolaryngologist at ENT Care Centers in Louisville, Kentucky, expressed a sentiment shared by many of his colleagues: "I think physicians were very hopeful that AI was going to be a boost, a solution if you will, to reduce the administrative burdens that we all face." Unfortunately, this optimism has largely failed to materialize. Dr. Scott elaborated on the escalating technological arms race, stating, "Eventually, their bot is going to talk to my bot. Because my bot is going to tell me how to document so I get authorization, and then their AI is going to get even smarter and deny that, so I get a denial letter back. And in the meantime, the physicians and patients are stuck in the middle, and that’s the problem."
Regulatory Intervention: States Step In Amidst AI’s Growing Influence
In response to the growing concerns surrounding AI’s role in claim denials, a wave of new state laws has emerged, or are slated to take effect, aiming to regulate the use of artificial intelligence in this critical aspect of healthcare administration. For example, an Alabama law mandates that insurers base their determinations on a patient’s unique circumstances rather than relying solely on aggregated group datasets. Similarly, an Indiana law prohibits insurers from using AI as the exclusive basis for downcoding a claim. A Washington state law now requires that such determinations must be made by licensed and qualified health professionals. These legislative efforts represent a growing recognition of the need for human oversight and patient-centric decision-making in the face of increasingly automated processes.
The federal government is also beginning to leverage AI in its own health insurance programs. The Centers for Medicare and Medicaid Services (CMS) has launched the WISeR (Wasteful and Inappropriate Service Reduction) program, which utilizes AI in conjunction with human review. According to CMS, this initiative aims to "reduce clinically unsupported care by working with companies experienced in using enhanced technologies to expedite and improve the review process for a pre-selected set of services that are vulnerable to fraud, waste, and abuse." The program commenced in January in six states: New Jersey, Ohio, Oklahoma, Texas, Arizona, and Washington, signaling a broader federal interest in employing AI for cost containment and fraud detection within Medicare.
Fighting Automation with Automation: Physicians Develop AI Solutions
Faced with the pervasive use of AI by insurers, many physicians feel compelled to adopt similar technologies to navigate the system. Bradford Bichey, MD, a rhinologist at Indiana Sinus Centers, has developed an AI product designed to streamline physicians’ office operations, including the generation of documentation for prior authorization submissions. Dr. Bichey observed a significant surge in clawback attempts a few years ago, with insurers requesting documentation for cases they suggested should not have been covered. The number of such requests jumped from an average of five at a time to as many as 50. He noted that the language used in these requests suggested an "early experimentation" with AI, with "verbiage was slightly off" and, in one instance, a letter that was "almost hateful." Over time, the tone of these communications has become more professional, but the underlying challenge remains.
In response, Dr. Bichey developed "Blue," an AI product under his company, Nemedic. Blue generates not only clinical notes based on patient encounters but also prior authorization documents specifically tailored to the requirements of individual insurers for particular indications. For example, if "United" is mentioned during a clinical visit, the software automatically cues the generation of a document compliant with United Healthcare’s specifications, as gleaned from their publicly available documents. These prior authorization submissions demand comprehensive justifications, often requiring more detail than standard clinical notes. For a nasal endoscopy, the AI can generate documentation stating, "routine anterior examination was insufficient to visualize the deeper nasal passage and assess for ongoing mucosal disease. Diagnostic rigid nasal endoscopy was medically necessary to direct visualization of the sinonasal mucosa," while also carefully noting exclusions, such as "this procedure was not performed for routine screening, but to inform management."
"You have to know [the insurer’s] inclusion and exclusion," Dr. Bichey explained. "And it’s almost impossible for someone who does billing to constantly keep up with all these plans because we see hundreds of different types of insurance." He finds that appealing denials is often straightforward, as it typically involves pointing to information already submitted but overlooked. "When we do this, we just resubmit the same note and say, ‘You’re wrong—look at paragraph three,’" he stated. Dr. Bichey claims that his improved upfront documentation has eliminated the need for peer-to-peer calls for the past two years.
Not an AI Problem, but a Governance Problem: The Underlying Dynamics
Matthew Crowson, MD, assistant professor of otolaryngology–head and neck surgery at Harvard Medical School and director of clinical informatics and artificial intelligence at Massachusetts Eye and Ear, posits that the issue is not inherently with AI itself, but rather with the governance surrounding its implementation. "It’s not so much that AI is the problem," he asserted. "It’s more the governance around this stuff, or lack thereof."
Dr. Crowson contends that AI has not resolved the fundamental provider-versus-payer dynamic. "It’s turning into a battle of the bots," he observed. "The application of AI by providers and payers is cutting both ways. It doesn’t resolve the fundamental tension between approving and denying based on medical necessity. It’s scaling up existing decision-making workflows faster."
However, he acknowledges that AI has, in certain respects, improved administrative efficiency in ways that can benefit patients. For instance, if a recommended ear drop is not on a health insurance plan’s formulary, a nurse or medical assistant would traditionally need to gather supporting information and complete a form for an appeal. AI can now draft a contextualized appeal very quickly, potentially expediting medication delivery to patients. "What would take a human process maybe seven business days to do, now you can do it in one," Dr. Crowson noted. "I think administratively, it’s massively speeding up our ability to respond quickly."
Efficiency Gains or Just More Activity? The Unclear Impact of AI
A report released by the Peterson Health Technology Institute earlier this year, based on workshops involving senior leaders from healthcare systems, health plans, technology developers, investment firms, and federal agencies, presented a nuanced and somewhat ambiguous picture of AI’s effects on the U.S. medical landscape. The report suggests that while AI may reduce the cost of obtaining prior authorizations for individual organizations, it has not necessarily lowered overall system costs. Furthermore, the deployment of AI by providers is reportedly increasing "billing intensity," leading to the identification of more severe diagnoses and advanced treatments, which in turn drives up costs.
Workshop participants expressed concerns that the optimized use of AI by both insurers and providers risks making the entire process "more activity-intensive" rather than truly more efficient. One healthcare provider, quoted in the report, lamented, "Bots don’t get tired of asking questions, so my review queue keeps growing." This suggests that while AI can automate repetitive tasks, it may also lead to an unending stream of automated inquiries and reviews, further burdening healthcare professionals.
Patients Caught in the Middle: The Human Cost of the Bot Wars
Meanwhile, the increasingly complex prior authorization process continues to strain the physician-patient relationship, according to otolaryngologists. Dr. Troublefield highlighted that extensive conversations with patients about insurance coverage requirements and hurdles are a daily reality. "It takes more time—I don’t think any of us runs on schedule at all. I would say five years ago, we probably could run on schedule. Not anymore. It never, ever, ever happens," she stated. "We’re finding that we’re constantly having to apologize, apologize, apologize. And that’s not the way people want to be treated."
Dr. Scott recounted a distressing experience where a patient with a growing maxillary sinus tumor, who had finally accepted the necessity of surgery, received a denial letter from the insurer stating the procedure was denied because she hadn’t yet been on an antibiotic. This assessment, Dr. Scott described as "preposterous." The patient subsequently called, suggesting, "The insurance company said I might get better on an antibiotic, so shouldn’t we try an antibiotic?" Dr. Scott reflected, "Now I’ve got to go explain to this patient, and I’m thinking about the trust relationship that I had with this patient and having to re-establish that trust." He advocates for physicians to appeal more often, noting that his practice appeals every denial. However, he acknowledges the prevalence of physician burnout, which can make it challenging for clinicians to "go to battle every time." He and the AMA are actively pushing for physician involvement in the development of regulations and processes surrounding AI.
A Fork in the Road for Prior Authorization: Navigating the Future
Dr. Crowson views the current situation as the healthcare field approaching a critical juncture. One path forward involves both providers and payers utilizing AI to efficiently process routine paperwork and basic tasks, freeing up human resources to focus on complex cases. The alternative path, he warns, is an "escalating compliance and gaming war." He expresses hope for a "pragmatic, middle-of-the-road approach—use it for what AI is good for: automating administrative monotony and other simple tasks that can be safely and efficiently scaled."
Dr. Troublefield harbors concerns that AI might simply add "another hoop" for physicians to jump through, requiring the use of specific terminology. However, she finds the prospect of software that automatically generates templates based on insurer requirements appealing, provided it is practical for daily use. She maintains some optimism that technology, coupled with "smart legislation" that regulates AI’s involvement in insurance decisions, could offer solutions. Furthermore, she believes that amplifying patient voices, and even celebrity endorsements, could significantly bolster legislative efforts. Ultimately, Dr. Troublefield concludes, physicians must adapt to the evolving landscape. "The system is changing, and either you have to be part of the change, or you’re going to get left behind," she stated. "It’s the same thing as when the automobile happened, right? You’re not stopping it, so you have to figure out ways within the system to make sure that what you want, and what your goals are, are actually achieved." The integration of AI into prior authorization represents a profound shift, demanding thoughtful adaptation and strategic foresight from all stakeholders in the healthcare ecosystem.
Thomas R. Collins is a freelance medical writer based in Florida.
