How AI Algorithms Control Your Health Insurance Coverage

Health insurance companies have increasingly embraced artificial intelligence (AI) algorithms over the past decade. Unlike doctors and hospitals, which use AI for patient diagnosis and treatment, insurers deploy these algorithms to determine whether to pay for recommended health care services and treatments.

One of the most common applications is prior authorization, where a doctor needs payment approval from the insurance company before providing care. Insurers use an algorithm to decide if the requested care is medically necessary and should be covered. These AI systems also help insurers determine the extent of care a patient can receive, such as the number of days of hospital care after surgery.

If an insurer declines to pay for a treatment, patients typically have three options: appeal the decision, agree to a different treatment, or pay for the recommended treatment themselves. However, only about 1 in 500 claim denials are appealed due to the time, money, and expert help required.

As a legal scholar specializing in health law and policy, I am concerned about the impact of insurance algorithms on people's health. While insurers claim AI helps make quick, safe decisions and avoids wasteful treatments, there is strong evidence suggesting the opposite. These systems are often used to delay or deny care, all in the name of cost savings.

Insurers refuse to disclose how these algorithms work, making it impossible to understand their decision-making process. Using AI to review coverage saves insurers time and resources, as fewer medical professionals are needed to review each case. However, the financial benefit to insurers extends beyond cost savings. If an AI system quickly denies a valid claim and the patient appeals, the appeal process can take years. If the patient is seriously ill and expected to die soon, the insurance company might save money by dragging out the process in the hope that the patient dies before the case is resolved.

This creates the disturbing possibility that insurers might use algorithms to withhold care for expensive, long-term, or terminal health problems, such as chronic disabilities. Research supports this concern, showing that patients with chronic illnesses are more likely to be denied coverage and suffer as a result. Additionally, Black and Hispanic people, as well as those who identify as LGBTQ+, are more likely to experience claims denials.

Insurers argue that patients can always pay for any treatment themselves, but this argument ignores reality. These decisions have serious health consequences, especially when people can’t afford the care they need.

Unlike medical algorithms, insurance AI tools are largely unregulated. They do not have to go through Food and Drug Administration (FDA) review, and insurance companies often claim their algorithms are trade secrets. This means there is no public information about how these tools make decisions, and no outside testing to ensure they are safe, fair, or effective.

Some states, including Colorado, Georgia, Florida, Maine, and Texas, have proposed laws to rein in insurance AI. A few have passed new laws, including a 2024 California statute that requires a licensed physician to supervise the use of insurance coverage algorithms. However, most state laws suffer from the same weaknesses, leaving too much control in the hands of insurers to define “medical necessity” and in what contexts to use algorithms for coverage decisions.

Health law experts argue that regulating health care coverage algorithms is now imperative. The FDA, which already reviews many medical AI tools for safety and effectiveness, is well positioned to do so. FDA oversight would provide a uniform, national regulatory scheme instead of a patchwork of rules across the country.

In summary, while AI has the potential to improve health care, the current use of AI in insurance coverage decisions raises significant concerns about patient health and equity. Stronger regulation and transparency are essential to ensure these tools are used responsibly and ethically.