How patients are using AI to fight back against denied insurance claims

Key Concepts

Artificial Intelligence (AI) in Health Insurance: The use of AI algorithms by health insurers for claims processing, utilization management, and decision-making.
Claim Denials: Instances where health insurance claims are rejected, leading to patients being responsible for medical costs.
Affordable Care Act (ACA) Plans: Health insurance plans offered under the ACA, which have seen a significant rate of claim denials.
Appeals Process: The formal procedure patients can follow to challenge a denied insurance claim.
Utilization Management: The process insurers use to manage healthcare costs by reviewing the necessity and appropriateness of medical services.
Prior and Concurrent Authorization: Processes requiring insurer approval before certain medical services are rendered or continued.
AI Arms Race: The escalating use of AI by both insurers and patients/providers to gain an advantage in the claims process.
Medical Necessity: The requirement that medical services be appropriate and required for the diagnosis or treatment of a condition.
Regulatory Landscape: The existing and needed regulations governing the use of AI in health insurance.

AI-Driven Claim Denials and Patient Appeals

Rising Claim Denials and Low Appeal Rates

Health insurers are increasingly employing artificial intelligence (AI) in their claims processing systems, which has coincided with a rise in claim denials. In recent years, approximately 20% of claims filed by Americans on Affordable Care Act (ACA) plans have been denied. In 2023 alone, this amounted to about 73 million people who had claims for in-network services denied. A significant barrier to patients receiving payment for these denied claims is the low appeal rate. Less than 1% of individuals whose claims were denied attempted to appeal. This is attributed to the process being perceived as too lengthy or too confusing.

Insurers' Use of AI in Claims Processing

The extent to which health insurance companies utilize AI and other automated predictive algorithms in their claim approval or denial systems is not fully transparent. However, a survey conducted in 2025 indicated that 71% of health insurers admitted to using AI for utilization management. This includes processes such as prior and concurrent authorization. Furthermore, several lawsuits have been filed alleging the use of AI in these decisions, with some denial letters explicitly stating that the claim was reviewed by an AI program.

The Complexity of the Appeals Process

Jennifer Oliva, a professor at Indiana University's Maurer School of Law, highlights the complexity of the appeals process as a major deterrent for patients. When individuals are facing acute care situations, often in emergent settings like the ICU, they may lack the prior knowledge, resources, or ability to navigate such a complex system. Despite the low appeal rates, Oliva notes that a majority of those who do appeal are very successful, underscoring the potential effectiveness of the appeals process if pursued.

AI as a Tool for Patients to Fight Denials

In response to the challenges faced by patients, software companies are now leveraging AI to assist individuals in appealing denied claims. These AI systems work by:

Collecting Documentation: The system prompts users to provide all relevant documentation that would support their appeal.
Fee-Based Service: Users typically pay a fee, around $40 or $50, for the service.
Generating Appeal Letters: The AI then generates a detailed claims appeal letter that the patient can submit to their insurer.

Early reports suggest that these AI-powered tools have been beneficial for users. Oliva encourages patients to explore these options, but also expresses concern about an "AI arms race" where insurers may escalate their AI capabilities in response to consumer empowerment.

Concerns About Insurer AI Tactics

Oliva voices significant concerns about the potential misuse of AI by insurers. She notes that insurers have a high rate of claim denials, and very few people appeal. AI can be used to detect individuals who are unlikely to appeal based on historical claims data or the anticipated duration of the appeals process. Her primary concern is that insurers might use "robust AI" to selectively target expensive cases where patients are less likely to survive or endure the appeals process. While acknowledging the value of AI tools for patients and providers, she fears an escalating imbalance of resources, with insurers becoming increasingly sophisticated while patients and providers lag behind.

The Regulatory Vacuum

The regulatory landscape governing the use of AI in health insurance is described as "very lightly regulated" with "almost nothing existing." Current regulations often stipulate that a human must be involved in the final determination of a claim. However, investigative reporting and pending lawsuits suggest that this is not always the case, with humans potentially rubber-stamping AI-driven decisions. Oliva advocates for robust front-end regulation to ensure that AI tools used by insurers make good, accurate, transparent, and valid decisions based on the patient's medical necessity, as required by law and plan contracts.

Conclusion and Key Takeaways

The increasing reliance on AI by health insurers has led to a surge in claim denials, disproportionately affecting patients who often face complex and emergent healthcare situations. The appeals process, though effective for those who pursue it, is a significant barrier due to its complexity and time commitment. AI is now emerging as a tool for patients to combat these denials, offering a more accessible and efficient way to file appeals. However, this has sparked concerns about an "AI arms race," with potential for insurers to exploit AI for strategic denial of claims, particularly for costly cases. The current regulatory framework is inadequate, highlighting the urgent need for robust regulations to ensure transparency, accuracy, and fairness in AI-driven health insurance decision-making, with a focus on medical necessity.