AI Medical Scribe Accuracy: What Clinicians Should Measure

A vendor accuracy number, such as 99%, tells you little unless you know how it was measured. Which audio, which speakers, which specialties, how many encounters, and who counted an error?

Transcription errors and note errors are different. Word error rate measures the transcript. What matters clinically is whether the note contains a wrong medication, wrong dose, wrong side, a missing negation, or an invented detail.

Measure what hurts: count omissions (things said but missing), commissions (things in the note that were never said) and attribution errors (a statement assigned to the wrong speaker).

Test on your own visits. Take ten to twenty of your typical encounters, generate notes, and mark every error by severity. Repeat with a difficult case: noisy room, accented speech, dense specialty terminology.

Track your edit time, not just error counts. If review and correction takes as long as writing the note, the tool is not helping you.

For that reason MD Record AI does not publish a single accuracy figure. Every generated note is a draft, and evaluating it on your own encounters is the only number that counts for your practice.