A Custom-Built Ambient Scribe Reduces Cognitive Load and Documentation Burden for Telehealth Clinicians

TL;DR

This paper presents a custom ambient scribe system that leverages AI to automatically generate clinical notes during telehealth visits, significantly reducing clinicians' cognitive and documentation burdens.

Contribution

The study introduces a novel ambient scribe application integrated with EHR, utilizing GPT-4o and Whisper, and demonstrates its effectiveness and widespread adoption in a telehealth setting.

Findings

Clinicians report 94% reduced cognitive load.

97% of clinicians experience less documentation burden.

Generated notes surpass expert-written notes in quality.

Abstract

Clinician burnout has motivated the growing adoption of ambient medical scribes in the clinic. In this work, we introduce a custom-built ambient scribe application integrated into the EHR system at Included Health, a personalized all-in-one healthcare company offering telehealth services. The application uses Whisper for transcription and a modular in-context learning pipeline with GPT-4o to automatically generate SOAP notes and patient instructions. Testing on mock visit data shows that the notes generated by the application exceed the quality of expert-written notes as determined by an LLM-as-a-judge. The application has been widely adopted by the clinical practice, with over 540 clinicians at Included Health using the application at least once. 94% (n = 63) of surveyed clinicians report reduced cognitive load during visits and 97% (n = 66) report less documentation burden when using the application. Additionally, we show that post-processing notes with a fine-tuned BART model improves conciseness. These findings highlight the potential for AI systems to ease administrative burdens and support clinicians in delivering efficient, high-quality care.