AI quietly denying insurance claims
- UnitedHealth, Cigna, and other insurers are facing deeper scrutiny as automated tools shape claim denials, especially in Medicare Advantage and prior authorization. - One of the clearest examples is Cigna’s PXDX system — tied to 300,000 denials in two months — while Senate investigators found major MA insurers denied about one-quarter of post-acute requests. - This matters because denial rates are already high, appeals are rare, and new CMS rules now force faster, more explainable prior-authorization decisions.
Insurance denials are becoming a software story. That is the real shift here. Insurers have always said no to claims and prior-authorization requests, but now more of that process is being routed through prediction models, rules engines, and algorithmic triage tools that can scale denials faster than patients can challenge them. The backlash is no longer hypothetical — it is showing up in lawsuits, Senate investigations, and new federal rules. ### What is the actual problem? The problem is not some sci-fi system fully replacing doctors overnight. It is more mundane — and more powerful. Insurers use software to flag claims, compare diagnosis codes to procedures, predict how long a patient “should” need rehab or nursing care, and route cases toward approval or denial. A human may still sign the final decision, but if the machine does the sorting and recommendation at scale, the machine is shaping the outcome. (statnews.com) ### Where has this shown up most clearly? The clearest public example is Medicare Advantage post-acute care. Reporting on UnitedHealth’s use of NaviHealth described algorithms being used to predict how long older patients should stay in rehab or skilled nursing, with coverage sometimes cut off when the model’s estimate ran out even if clinicians wanted more care. UnitedHealth retired the NaviHealth brand in 2024, but the broader use of these tools did not disappear. (statnews.com) ### Why are people calling this “AI denials”? Because the practical effect looks like automation deciding who gets paid or treated. In one lawsuit against Cigna, plaintiffs said the insurer used a system called PXDX to reject claims in bulk, then had physicians sign off without meaningful individual review. The underlying reporting tied PXDX to more than 300,000 denials over two months in 2022, with doctors spending an average of 1.2 seconds on each case. That is not careful medical judgment — that is industrialized filtering. (statnews.com) ### Is this just a few bad anecdotes? No — the scale is the point. A Senate Permanent Subcommittee on Investigations report released on October 17, 2024 said UnitedHealthcare, Humana, and CVS used automated systems to review post-acute care and, by 2022, were denying roughly 1 in 4 such requests for Medicare Advantage members. That does not prove every denial was wrong, but it shows these tools are embedded in core coverage decisions, not sitting in a lab demo. (statnews.com) ### Why don’t patients just appeal? Basically because the system is built for drop-off. KFF’s latest look at HealthCare.gov plans found insurers denied 19% of in-network claims in 2024, and consumers appealed fewer than 1% of denied in-network claims. When denials are common and appeals are rare, even a modestly overaggressive algorithm can save money simply because most people never fight back. ### What are regulators doing about it? (hsgac.senate.gov) CMS has started forcing more process discipline. Its January 17, 2024 prior-authorization rule requires impacted payers to send specific denial reasons, build electronic prior-auth workflows, and meet faster decision timelines. That rule does not ban algorithms. But it does make opaque, shrug-emoji denials harder to defend. If a model helps say no, the insurer now has more pressure to explain why in a way patients and providers can contest. (kff.org) ### So what is the real risk for insurers? The risk is not just bad press. It is that automation turns a compliance problem into a pattern. Once denials become faster, cheaper, and less visible, companies can drift into a system where nobody can clearly explain a decision, nobody wants to own it, and courts or regulators start treating the whole workflow as suspect. That is exactly why these cases keep attracting attention. (cms.gov) ### Bottom line? AI is not quietly taking over insurance by itself. People are still building the rules, buying the software, and approving the workflows. But automation is making denials easier to scale and harder to challenge — and that is why this has become a real political and legal fight now. (statnews.com 1) (statnews.com 2)
