AI Audit Trail (Clinical)
A clinical AI audit trail is a time-stamped record of the AI-assisted document steps covered by an implementation: what the AI proposed, what an authorized person changed or approved, and when. Its exact scope, retention and source are defined for each institution.
Put the evidence in context
Review the intended task, source information, human checkpoints and observed results together. A benchmark or sandbox result has a defined scope; it does not establish suitability, approval or performance for every institution.
Read the full explanationCare Workspace connects healthcare work such as appointments, reviewed reporting and follow-up. Micromeet Cowork supports team work with digital employees and reusable Skills, including meeting summaries, decisions and task handoffs.
Read the full explanationWithout an audit trail, an AI-generated note is just text — you cannot tell which parts came from the model, what a clinician corrected, or whether anyone reviewed it at all. With one, every clinical document carries its own provenance, which is what regulators, payers and quality teams need when a record is questioned after the fact.
This is core to clinician-reviewed AI documentation: the audit trail is the mechanism that makes clinician sign-off actually enforceable, by recording the human review and approval that turn an AI draft into a clinician-owned record.