Real-World Evidence Synthesis of Digital Scribes Using Ambient Listening and Generative Artificial Intelligence for Clinician Documentation Workflows: Rapid Review.

IF 2
JMIR AI Pub Date : 2025-10-10 DOI:10.2196/76743
Naga Sasidhar Kanaparthy, Yenny Villuendas-Rey, Tolulope Bakare, Zihan Diao, Mark Iscoe, Andrew Loza, Donald Wright, Conrad Safranek, Isaac V Faustino, Alexandria Brackett, Edward R Melnick, R Andrew Taylor
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Abstract

Background: As physicians spend up to twice as much time on electronic health record tasks as on direct patient care, digital scribes have emerged as a promising solution to restore patient-clinician communication and reduce documentation burden-making it essential to study their real-world impact on clinical workflows, efficiency, and satisfaction.

Objective: This study aimed to synthesize evidence on clinician efficiency, user satisfaction, quality, and practical barriers associated with the use of digital scribes using ambient listening and generative artificial intelligence (AI) in real-world clinical settings.

Methods: A rapid review was conducted to evaluate the real-world evidence of digital scribes using ambient listening and generative AI in clinical practice from 2014 to 2024. Data were collected from Ovid MEDLINE, Embase, Web of Science-Core Collection, Cochrane CENTRAL and Reviews, and PubMed Central. Predefined eligibility criteria focused on studies addressing clinical implementation, excluding those centered solely on technical development or model validation. The findings of each study were synthesized and analyzed through the QUEST human evaluation framework for quality and safety and the Systems Engineering Initiative for Patient Safety (SEIPS) 3.0 model to assess integration into clinicians' workflows and experience.

Results: Of the 1450 studies identified, 6 met the inclusion criteria. These studies included an observational study, a case report, a peer-matched cohort study, and survey-based assessments conducted across academic health systems, community settings, and outpatient practices. The major themes noted were as follows: (1) they decreased self-reported documentation times, with associated increased length of notes; (2) physician burnout measured using standardized scales was unaffected, but physician engagement improved; (3) physician productivity, assessed via billing metrics, was unchanged; and (4) the studies fell short when compared to standardized frameworks.

Conclusions: Digital scribes show promise in reducing documentation burden and enhancing clinician satisfaction, thereby supporting workflow efficiency. However, the currently available evidence is sparse. Future real-world, multifaceted studies are needed before AI scribes can be recommended unequivocally.

使用环境聆听和生成人工智能的临床医生文档工作流程的数字抄写员的真实世界证据合成:快速回顾。
背景:由于医生在电子健康记录任务上花费的时间是直接患者护理的两倍,数字抄写员已经成为恢复患者-临床沟通和减少文档负担的有前途的解决方案,因此研究它们对临床工作流程、效率和满意度的实际影响至关重要。目的:本研究旨在综合临床医生效率、用户满意度、质量和实际障碍的证据,这些证据与在现实世界的临床环境中使用使用环境听力和生成人工智能(AI)的数字抄写器有关。方法:快速回顾2014年至2024年临床实践中使用环境聆听和生成式人工智能的数字抄写员的真实证据。数据收集自Ovid MEDLINE、Embase、Web of Science-Core Collection、Cochrane CENTRAL and Reviews和PubMed CENTRAL。预定义的资格标准侧重于解决临床实施的研究,排除那些仅以技术开发或模型验证为中心的研究。每项研究的结果通过QUEST质量和安全人类评估框架和患者安全系统工程倡议(SEIPS) 3.0模型进行综合和分析,以评估临床医生工作流程和经验的整合情况。结果:在纳入的1450项研究中,有6项符合纳入标准。这些研究包括一项观察性研究、一份病例报告、一项同行匹配队列研究,以及在学术卫生系统、社区环境和门诊实践中进行的基于调查的评估。注意到的主要主题如下:(1)他们减少了自我报告的文件时间,相应的增加了笔记的长度;(2)采用标准化量表测量的医生职业倦怠不受影响,但医生敬业度有所提高;(3)通过计费指标评估的医生生产力没有变化;(4)与标准化框架相比,这些研究存在不足。结论:数字抄写员有望减轻文件负担,提高临床医生的满意度,从而提高工作效率。然而,目前可获得的证据很少。在明确推荐人工智能抄写员之前,需要对未来的现实世界进行多方面的研究。
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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