What an AI Scribe Actually Does
An AI medical scribe listens to the patient-physician conversation in real time, extracts clinical intent, and generates structured SOAP notes, HPI sections, and assessment plans — ready for physician review and EHR insertion. It's not transcription. It's comprehension.
The Azure OpenAI Architecture
We use Azure OpenAI (GPT-4 Turbo) with Azure Speech Services for real-time audio streaming. The pipeline: audio → Azure Speech SDK → chunked transcript → GPT-4 prompt → structured clinical output → EHR API. All data stays within Azure's HIPAA-eligible services — no data leaves the tenant boundary.
Prompt Engineering for Clinical Accuracy
Generic prompts produce generic notes. We invest significant effort in specialty-specific prompt templates — a cardiology note looks nothing like a psychiatry note. We also inject patient context (age, chief complaint, existing conditions) to improve extraction accuracy.
EHR Integration Realities
FHIR R4 is the standard, but real-world EHR APIs are inconsistent. We've integrated with Epic, Athenahealth, and several smaller systems. Each requires custom mapping. Plan for this — it's where most of the integration time goes.
Accuracy and Physician Trust
Physicians don't trust black boxes. We built a review-and-edit UI that shows confidence scores per section, highlights uncertain extractions, and tracks edit rates over time. As the model learns from corrections, accuracy improves. Most clinicians reach 90%+ accuracy within 2 weeks of use.
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