Voice-to-EMR
Voice-to-EMR (also called V2N) is the workflow that turns a spoken clinical encounter into structured documentation written back into the electronic medical record (EMR). It pairs medical automatic speech recognition with structuring into a SOAP note and coding-ready context, with a clinician reviewing before anything is filed.
From consultation audio to a reviewable draft
AI Scribe turns supported consultation audio into structured note, visit-summary or referral-letter drafts. Clinicians review the draft and any coding suggestions before the approved context is used in an enabled Care Workspace workflow.
Read the full explanationAfter clinician approval, AI Scribe can use an institution-verified export or integration path. Language performance, permissions and any EMR writeback are checked for your intended workflow; the EMR remains the source of record.
Read the full explanationThe workflow runs in five steps: the consultation is captured in the languages actually spoken in the room; medical automatic speech recognition (ASR) transcribes it; the transcript is structured into a draft SOAP note (Subjective, Objective, Assessment, Plan) with coding-ready context; the clinician reviews, edits, and approves the draft; and only the approved content is written back into the EMR. The clinician's review is not an add-on — it is the step that makes the workflow safe to run, which is why Voice-to-EMR is a working example of AI documentation with clinician sign-off.
Voice-to-EMR is Micromeet's clinical-documentation product line, delivered as AI Scribe (Voice-to-EMR). The practical integration path is to work on top of the EMR or hospital information system already in place — writing back only clinician-approved content — so it replaces a step in the workflow instead of adding one. Clinical judgment stays with clinicians; the AI does not diagnose or sign.