BankingSR 26-2 · FFIEC HealthcareRUAIH · HTI-1 PrivacyADMT · ART. 22

AI trust infrastructure for clinical AI

Get through the hospital AI committee before the review becomes the reason the deal died.

Committees no longer ask whether the model is accurate. They ask whether clinicians rubber-stamp it, and whether your numbers can be trusted. Coriqo keeps a record your team can’t edit, and the committee checks it themselves.

See what the committee checks See the review number they will believe

Coriqo holds records of how your AI was approved and reviewed. It needs no patient records.

Maps to Joint Commission RUAIHONC HTI-1 DSINIST AI RMF 1.0EU AI Act

Where clinical AI deals stall

The model passed. The committee still has to decide whether its clinicians and patients can rely on it.

Three objections come up in nearly every review. None of them is about accuracy.

Repeated work

Every health system asks differently

One wants your bias approach, the next your training-data demographics, the third your retirement policy. Same evidence, rebuilt by hand for every deal.

Self-reported numbers

Your override rate is your own number

You say clinicians override 12% of the time. Their counsel asks who computed it, and whether anyone could have edited it.

The new objection

The question changed

They now ask whether your tool turns clinicians into rubber stamps. A slide doesn’t answer that.

A healthcare data breach cost $7.42M on average in 2025, the highest of any industry (IBM Cost of a Data Breach 2025). And a tribunal has already held a company liable for what its own AI told someone (Moffatt v. Air Canada, Feb 2024).

Illustrative example · a sample vendor and a sample hospital, not a customer

The committee asked whether clinicians rubber-stamp the tool. The vendor showed them the review record.

01 · The question

"Does anyone actually look?"

At a sample hospital, the chief nursing officer asks: when the sepsis tool flags a patient, does a clinician read it, or click accept?

02 · The record

Every review, timed as it happened

The vendor opens the review record: time spent per decision, and how often clinicians disagreed with the model.

03 · The awkward part

The numbers were not flattering

A median of 1.4 seconds and no disagreement in six months. A finding was already open, owned by the medical director. The vendor couldn’t leave it out.

04 · The committee checks

They verify it themselves

The committee gets time-limited, read-only access and checks it on its own. Coriqo reports the numbers and never grades a clinician.

Any vendor can publish a log. The committee trusted a number the vendor couldn’t edit, including the part it would rather not have shown.

One record, every framing

Every committee asks in its own words. Answer each one from the same record.

Pick the domain the committee is asking about. Each Joint Commission RUAIH requirement, cross-referenced to ONC HTI-1, is answered from records you already hold.

RUAIH domain

RUAIH certifies the health system's AI governance program, not your product. These are the checks your documentation has to satisfy for their certification to hold.

Governance2 checks

R-01Blocks sign-off if absent

Documentation must name the accountable owner and governance body responsible for the AI system’s oversight, and state how AI-related decisions are escalated and reviewed within that structure.

RUAIH · Governance

Answered by 4 sealed records · last change event #2,208

R-02Weakens the record if absent

Documentation must state the policies covering the AI system’s full lifecycle — intake and approval, deployment, change management, and retirement — not only its initial validation.

RUAIH · Governance

Answered by 6 sealed records · last change event #2,377

Requirement text is the shipped rulepack (Joint Commission RUAIH domains, ONC HTI-1 source attributes). Evidence counts are sample data.

Oversight Proof

Did a clinician really review it? A number you cannot edit, on record before a regulator or a plaintiff works it out.

Clinicians are told to review every recommendation. Coriqo records how long each review took and how often the reviewer agreed with the model, in a record you can’t edit.

Why it holds up

The referee is not the player

The measurement goes into an add-only record your team can’t rewrite, and the committee checks it with a public key.

Why it grows in value

Better models widen the gap

As accuracy rises, review gets more ceremonial. You can’t infer scrutiny from model quality. You have to measure it at the human.

Where it's heading

How much one approval covers, once agents act

Once agents act, one approval can authorize thousands of actions. Coriqo records how much a single signature covered.

coriqo.io / vendor_clinical_ai / oversight / sepsis-triage@v4Sealed

Human review record

Tier-1 diagnostic recommendation · 2026-02-01 → 2026-07-31 · sample data

Median time on decision

1.4s

Across 3,000 reviewed decisions

Concordance with model

100%

No reviewer departure recorded

Decisions in scope

3,000

4 reviewers · 6-month window

Threshold you set · finding opened

Concordance stayed above 95% for 90 days on Tier-1 decisions. Coriqo opened a tracked finding against the threshold your medical director configured. It reports the number; the judgment stays with your clinical governance body.

Owner · dr. c. mensah, medical director · due 2026-09-15

Recorded as event #2,411 in an append-only chain
Merkle root 7a3f…c901 · Ed25519, coriqo-key-2026-01
Anyone can verify it with the public key alone, without a Coriqo server

	What Coriqo does (a monitor)	What Coriqo will not do (a detector)
Output	"Dr. Park: 1.4s median, 100% concordance, 3,000 decisions."	"This approval was not a genuine review."
The claim	A fact about what happened.	A verdict about a named clinician.
Who judges	Your medical director, the committee, a regulator.	Us. That is not our place.
If it's wrong	It cannot be. It reports the record.	Every false positive becomes your employment-law problem.

Also for payers

Every 2026 state statute says a licensed human, not the model, makes the denial. Most plans cannot show it happened.

The figure that defined this problem, about a second per claim, came from journalism, not from any plan’s own systems. Find it on your own record first, while it is still a finding and not a liability.

ArtifactThe same sealed package vendors use.

RecordsWho reviewed the determination, for how long, and whether they departed from the model.

AudienceState regulators, external review organizations and your appeals team.

BoundaryCoriqo never decides a claim or scores a reviewer.

Shared foundation

The proof underneath: one shared verification core, with healthcare checks on top.

The chain, the seal and the public-key check are the same code in every Coriqo deployment. Healthcare is a set of checks on top, not a separate product with separate guarantees.

How verification works · How it's built

Shared

Append-only event log. Every approval, change, and finding sealed with SHA-256. Alter a record after the fact and verification fails.

Shared

Merkle proofs. They let a committee verify one event without holding the whole chain.

Shared

Time-boxed external portal. Read-only access for a reviewer outside your company, with every view logged.

Healthcare-specific

RUAIH and HTI-1 rulepack. Ten deterministic requirement checks, plus NIST AI RMF 1.0 as the underlying framework.

Healthcare-specific

Clinical decision classes. Diagnostic recommendation, treatment plan, and risk stratification, each governed on its own track.

Coriqo Shield · early access

Keep patient identifiers out of the AI apps your staff use.

Shield replaces emails, phone numbers and SSNs before a message leaves each Mac. It doesn’t catch names or clinical free text yet, so it supports a PHI policy rather than replacing one.

See Shield

We're looking for clinical AI vendors to shape this vertical.

Two healthcare rulepacks ship today, and no vendor has run the full motion end to end yet. Tell us which committee question keeps stalling your deals.

Talk to us