Ambient artificial intelligence scribes: utilization and impact on documentation time.

IF 4.7 2区医学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS

Journal of the American Medical Informatics Association Pub Date : 2024-12-17 DOI:10.1093/jamia/ocae304

Stephen P Ma, April S Liang, Shreya J Shah, Margaret Smith, Yejin Jeong, Anna Devon-Sand, Trevor Crowell, Clarissa Delahaie, Caroline Hsia, Steven Lin, Tait Shanafelt, Michael A Pfeffer, Christopher Sharp, Patricia Garcia

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引用次数: 0

Abstract

Objectives: To quantify utilization and impact on documentation time of a large language model-powered ambient artificial intelligence (AI) scribe.

Materials and methods: This prospective quality improvement study was conducted at a large academic medical center with 45 physicians from 8 ambulatory disciplines over 3 months. Utilization and documentation times were derived from electronic health record (EHR) use measures.

Results: The ambient AI scribe was utilized in 9629 of 17 428 encounters (55.25%) with significant interuser heterogeneity. Compared to baseline, median time per note reduced significantly by 0.57 minutes. Median daily documentation, afterhours, and total EHR time also decreased significantly by 6.89, 5.17, and 19.95 minutes/day, respectively.

Discussion: An early pilot of an ambient AI scribe demonstrated robust utilization and reduced time spent on documentation and in the EHR. There was notable individual-level heterogeneity.

Conclusion: Large language model-powered ambient AI scribes may reduce documentation burden. Further studies are needed to identify which users benefit most from current technology and how future iterations can support a broader audience.

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目的量化大型语言模型驱动的环境人工智能（AI）代笔的使用情况及其对记录时间的影响：这项前瞻性质量改进研究是在一家大型学术医疗中心进行的，共有来自 8 个非住院学科的 45 名医生参加，历时 3 个月。使用和记录时间来自电子健康记录（EHR）的使用情况：在 17 428 次会诊中，有 9629 次（55.25%）使用了环境人工智能抄写员，用户之间存在显著的异质性。与基线相比，每份记录的中位时间显著减少了 0.57 分钟。每天记录、下班后和总电子病历时间的中位数也分别大幅减少了 6.89 分钟、5.17 分钟和 19.95 分钟：环境人工智能抄写员的早期试点表明，其使用率很高，减少了文档记录和电子病历所花费的时间。结论：大型语言模型驱动的环境人工智能抄写员的使用率很高，减少了记录和在电子病历上花费的时间：结论：由大型语言模型驱动的环境人工智能抄写员可以减轻文档记录的负担。还需要进一步研究，以确定哪些用户从当前技术中获益最多，以及未来的迭代如何支持更广泛的受众。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of the American Medical Informatics Association 医学-计算机：跨学科应用

CiteScore

14.50

自引率

7.80%

发文量

230

审稿时长

3-8 weeks

期刊介绍： JAMIA is AMIA''s premier peer-reviewed journal for biomedical and health informatics. Covering the full spectrum of activities in the field, JAMIA includes informatics articles in the areas of clinical care, clinical research, translational science, implementation science, imaging, education, consumer health, public health, and policy. JAMIA''s articles describe innovative informatics research and systems that help to advance biomedical science and to promote health. Case reports, perspectives and reviews also help readers stay connected with the most important informatics developments in implementation, policy and education.