Overview
Physicians were spending 30-40% of their working day on documentation - manually writing SOAP notes after each visit, looking up ICD-10 codes, and flagging follow-ups. Documentation burden was limiting patient throughput and contributing to burnout.
Build a production healthcare AI system that converts spoken patient visits into structured clinical records - automatically, from a single voice recording.
We built a browser-based recording UI in Next.js that sends visit audio to a FastAPI backend (Python 3.9+, SQLAlchemy 2.0, Docker). OpenAI Whisper handles multi-language transcription. GPT-4 then generates a structured SOAP note - Subjective, Objective, Assessment, Plan - and extracts ICD-10 and CPT codes, flags medication interaction warnings, and surfaces clinical risk alerts. Each visit is linked to a patient record with full visit history and status tracking. JWT authentication with bcrypt and HTTP-only cookies. Frontend deployed on Vercel, backend on Cloud Run via Docker Compose.
Physicians capture a complete structured medical record - transcript, SOAP note, diagnosis codes, medication warnings, and follow-up plan - from one voice recording, with zero manual typing. The full note is available before the patient leaves the room.
Deliverables
- Browser-based audio recording
- Whisper multi-language transcription
- GPT-4 SOAP note generation
- ICD-10 / CPT code extraction
- Medication warning and risk alert detection
- Patient and visit management
- JWT auth with bcrypt
- Vercel + Cloud Run Docker deployment
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