Ambient Clinical Documentation

Use AI to automate clinical note-taking and reduce clinician documentation burden

Business impact

• Physician productivity — Increases by reducing time spent on paperwork, enabling more patient visits
• Physician burnout rates — Decreases as documentation burden is alleviated, improving clinician well-being
• Patient care time — Increases due to less clinician distraction from administrative tasks
• Clinician documentation time — Decreases by automating note generation and transcription during consultations
• EHR usage time — Reduces as AI scribes streamline electronic health record interactions
• Revenue per clinician — Slightly increases from improved productivity and more patient visits

Data requirements

• Audio recordings of patient-clinician interactions (Audio) — Used to transcribe conversations and generate clinical notes
• Electronic Health Records (EHR) data (Structured) — Provides patient history and context to enrich documentation
• Clinical guidelines and medical terminologies (Text) — Supports accurate and standardized note generation

AI methods and techniques

• Generative AI — Generates draft clinical notes from transcribed audio in real time
• Predictive AI — Anticipates relevant clinical information to complete notes efficiently

AI models and model families

GPT-4o, Claude, Llama

Industries

Real-world evidence

2 documented case studies on record.

Companies using this: Mass General Brigham, UChicago Medicine.