CAIHL read · Jun 11, 2026

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STAT+: Private Medicare plans erect barriers to rehab care in pursuit of profit, federal investigators find

What CAIHL does

Critical AI Health Literacy (CAIHL) is an analytical lens — Hugo Campos and Liz Salmi's 2025 National Academy of Medicine commentary, "Critical AI Health Literacy as Liberation Technology." It applies Paulo Freire's theory of critical literacy to health AI.

The central question CAIHL asks is whose interests does this AI actually serve? Four dimensions answer it: who is the primary user, where is it hosted, whose interests does it advance, and does it expand or constrain patient agency.

This deep-read separates the four dimensions on a single item from the day's scan, so you can see the specific structural shape of the AI in question — not just the bucket it landed in.

How this item reads through CAIHL

Primary user

patient

Patients, families, and care partners are the primary users of this AI.

Hosting

government

Hosted or controlled by a government agency or program.

Interests

patient-aligned

Interest structure prioritizes patients. Operates on a philanthropic, public-service, or advocacy footing.

Agency

expanding

Expands patient capabilities, supports their questions, increases their ability to act on their own values across and beyond health systems.

One-sentence synthesis

Federal OIG findings on payer denial patterns; expanding agency through formally documented evidence.

How this item appeared in the daily scan

Editor's note: When the OIG finds the pattern and the AMA adopts the policy in the same week, the regulatory weather has shifted. The patient who was denied appeals-reversal rehab care is the named claimant in both documents.

Summary: STAT: Federal OIG investigation finds Medicare Advantage plans erecting structural barriers to rehab care — the operational framework that the AMA's AI-in-prior-authorization policy is responding to.

Read the original source →

methodology

Limitations

CAIHL is a lens, not a verdict. The four dimensions are conditions of use — reassess them when a tool's business model, deployment context, or patient behavior changes. See the NAM commentary for the full framework.