aceThe missing layer: decision integrity as a verifiable assurance layer in interpretive clinical artificial intelligence
Objective: Interpretive clinical artificial intelligence (AI), in which a clinician interprets an image or signal and an AI system offers a competing or confirming read, is increasingly routine in radiology, pathology, dermatology, and endoscopy. Oversight of these systems assumes that independent human judgment occurred before AI influence entered the decision. The informatics infrastructure, meaning the electronic health record, its audit logs, and the reporting systems built on them, does not verify this. Dis…
A proposed six-event tamper-evident record under sequential disclosure could make pre-AI judgment, post-AI revision, and rationale auditable.
Electronic health records, audit logs, and reporting systems do not verify that independent clinician judgment preceded AI influence in image and signal interpretation.
The authors state the architecture is only a candidate for evaluation and not a validated standard, so its real-world effectiveness is untested.
Evidence
- Peer-reviewedJournal of the American Medical Informatics Association2026-10-16
How should this claim be treated?
Truvace Impact Record TRV-2026-1646, v1: “The missing layer: decision integrity as a verifiable assurance layer in interpretive clinical artificial intelligence.” Truvace, 2026-10-17. /record/TRV-2026-1646 (accessed at citation time). sha256 689257d214c6b294…
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