AI助手自动生成医患记录，显著减轻医生负担。
A Custom-Built Ambient Scribe Reduces Cognitive Load and Documentation Burden for Telehealth Clinicians
- 用Whisper语音转录+GPT-4o生成病历和患者指导
- 生成病历质量优于专家手写，94%医生感觉更轻松
- 适合希望减负的医疗从业者，尤其远程诊疗场景
临床医生倦怠推动了智能辅助记录系统的应用。本文介绍了一个为Included Health公司定制的嵌入电子病历系统的环境式医疗助手，利用Whisper进行语音转录，并通过GPT-4o的上下文学习模块自动生成SOAP病历与患者指导。在模拟就诊数据测试中，该系统生成的病历质量超过专家手写版本（以LLM作为评判标准）。该应用已在临床广泛使用，超过540名医生至少使用过一次。调查显示，94%（n=63）的医生认为使用后就诊时认知负荷降低，97%（n=66）表示文书工作负担减少。此外，经过微调的BART模型后处理可进一步提升病历简洁性。结果表明，此类AI系统有潜力缓解行政压力，支持高效高质量医疗服务。
原文摘要 · Abstract (English)
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.
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