A working definition — versioned, hash-anchored, free to adopt
Regulators now require a licensed clinician behind AI-generated clinical decisions. Certifying bodies audit organizations. But the requirement lives at the level of the single determination — and no one has defined what counts there. This is a working definition: five tests a review must pass to be called real, written so that anyone — a vendor, a regulator, a reporter — can check each one.
Version 1.0 · July 19, 2026 · canonical text · SHA-256 d731ce0a…8bf4d38 — the definition is anchored in the same registry it prescribes.
The reviewer holds an active license appropriate to the decision, verified against the primary source at review time, and matched to the case's jurisdiction and specialty.
Check it: NPI lookup against CMS NPPES → TEST 2The reviewer is organizationally independent of the developer of the AI system under review, and compensation does not depend on the direction of the verdict.
Why it matters: a vendor grading its own homework is governance, not review → TEST 3A defined sample is independently double-reviewed and inter-reviewer agreement statistics are disclosed. A process that cannot show its disagreement rate cannot show its engagement.
The evidence for this test: unmeasured sign-off is the documented failure mode → TEST 4Every determination produces a tamper-evident receipt at signing — content hash, verdict, credential class, timestamp — verifiable by any third party without trusting the reviewing organization.
Try one: verify any receipt in the public registry → TEST 5Receipts are anchored so they outlive the operator — committed to a public, independently verifiable timestamp and retained for the full audit period. Proof that dies with the vendor is not proof.
The mechanism: registry root countersigned into Bitcoin daily →Each of these is real and useful — and each stops one level above the determination. This definition is the missing bottom layer, not a competitor to any of them.
Voluntary Responsible Use of AI certification (2026) for its 22,000+ accredited organizations — governance playbooks: policy, oversight committees, lifecycle, vendor oversight. Organization-level.
URACHealth Care AI accreditation with AI/ML transparency and bias-testing standards in v8.0+. Accredits the program, not the determination.
NCQAAI provisions entering Health Plan Accreditation and utilization-management standards for 2026. Plan-level.
CMS WISeRRequires licensed clinicians behind every non-payment recommendation and human review of every denial — the requirement IS per-determination, but no test of what counts, and no verifiability mechanism. The gap this page fills.
CMS SaMS / "O1" (proposed)The CY2027 OPPS rule creates the first Medicare payment category for clinical AI — paid per use, to facilities — and flags per-click billing as a program-integrity concern with no verification mechanism proposed. Tests 4 and 5 are the answer; see our O1 page.