环境人工智能的实用性随机控制试验,以改善卫生从业人员的福祉
Majid Afshar1,2,3, Mary Ryan Baumann1,4,5, Felice Resnik1
1Institute for Clinical and Translational Research, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA.
NEJM AI
|February 2, 2026
概括
在实用试验中,环境人工智能显著减少了临床医生的倦怠和文档时间. 虽然专业成就没有显著增加,但人工智能改进了计费代码,而不会影响笔记质量.
科学领域:
- 医疗信息学 医疗信息学
- 临床操作 临床操作
- 医疗保健中的人工智能
背景情况:
- 电子健康记录 (EHR) 文档对从业人员的疲劳和倦怠有重大贡献.
- 生成型人工智能 (AI) 书记者通过自动化笔记起草提供了一个潜在的解决方案.
- 支持人工智能书记在临床环境中的有效性的证据仍然有限.
研究的目的:
- 评估环境人工智能对临床医生的倦怠和专业成就的影响.
- 评估记录时间的变化,工作之外的工作 (WoW) 和记录质量.
- 为了确定人工智能对诊断计费代码准确性的影响.
主要方法:
- 这是一项为期24周的逐步形,个别随机的实用性试验,涉及66名医疗保健从业者.
- 实践者被分配到6周的环境AI实施序列.
- 主要结果包括职业成就和工作疲劳/人际疏远;次要结果评估了文档时间,WoW,质量和计费代码.
主要成果:
- 环境人工智能使用导致工作疲劳/人际疏远的显著减少 (P<0.001).
- 用于笔记的时间每天减少0.36小时 (P<0.001),诊断计费代码得到了改进.
- 文档质量仍然很高,没有检测到软件性能偏移.
结论:
- 环境人工智能有效地减少了医疗保健从业人员在现实环境中的工作疲劳和人际疏远.
- 文件处理时间缩短,但不会影响诊断,账单合规性或笔记质量.
- 虽然专业成就没有显著增加,但环境人工智能显示出减轻EHR相关负担的希望.
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