A Custom-Built Ambient Scribe Reduces Cognitive Load and Documentation Burden for Telehealth Clinicians
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arXiv
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| Format: | Preprint |
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2025
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| author | Morse, Justin Gilbert, Kurt Shin, Kyle Cooke, Rick Rose, Peyton Sullivan, Jack Sisante, Angelo |
| author_facet | Morse, Justin Gilbert, Kurt Shin, Kyle Cooke, Rick Rose, Peyton Sullivan, Jack Sisante, Angelo |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_17754 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | A Custom-Built Ambient Scribe Reduces Cognitive Load and Documentation Burden for Telehealth Clinicians Morse, Justin Gilbert, Kurt Shin, Kyle Cooke, Rick Rose, Peyton Sullivan, Jack Sisante, Angelo Human-Computer Interaction Artificial Intelligence Computation and Language Computers and Society 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. |
| title | A Custom-Built Ambient Scribe Reduces Cognitive Load and Documentation Burden for Telehealth Clinicians |
| topic | Human-Computer Interaction Artificial Intelligence Computation and Language Computers and Society |
| url | https://arxiv.org/abs/2507.17754 |