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Whenever an AI tool gives a result about a patient, the hospital system would permanently record what it saw, which version it was, what it said and what the doctor did with it.
Most AI outputs are transient and not stored, making retrospective audit, harm investigation and performance measurement impossible. The proposal is a standard for AI audit trails in the EHR (FHIR resources capturing model identifier and version, input references and hashes, output, confidence, timestamp, and the clinician's acceptance or override), required for all deployed cancer AI and feeding post-market performance reporting.
Shares Mandatory post-market performance reporting for cancer AI, How medical AI devices are evaluated: limitations and recommendations from an analysis of FDA approvals, AI that is built but not validated or deployed.
Shares How medical AI devices are evaluated: limitations and recommendations from an analysis of FDA approvals, AI that is built but not validated or deployed.
Shares How medical AI devices are evaluated: limitations and recommendations from an analysis of FDA approvals, AI that is built but not validated or deployed.
Shares How medical AI devices are evaluated: limitations and recommendations from an analysis of FDA approvals, AI that is built but not validated or deployed.
Shares How medical AI devices are evaluated: limitations and recommendations from an analysis of FDA approvals, AI that is built but not validated or deployed.
Shares How medical AI devices are evaluated: limitations and recommendations from an analysis of FDA approvals, AI that is built but not validated or deployed.
Shares How medical AI devices are evaluated: limitations and recommendations from an analysis of FDA approvals, AI that is built but not validated or deployed.
Shares How medical AI devices are evaluated: limitations and recommendations from an analysis of FDA approvals, AI that is built but not validated or deployed.