开发和评估基于人工智能的工作流程,以优先考虑患者门户消息
Jie Yang1, Jonathan So1, Hao Zhang1
1Department of Health Informatics, NYU Langone Health, New York, NY 10016, United States.
JAMIA open
|August 19, 2024
概括
一个人工智能 (AI) 系统优先考虑紧急的患者门户消息,减少临床医生的审查时间. 这种人工智能集成到电子健康记录 (EHR) 中,可以通过更快地响应关键的健康问题来增强患者的护理.
科学领域:
- 医疗信息学 医疗信息学
- 医疗保健中的人工智能
- 临床工作流的优化 临床工作流优化
背景情况:
- 患者门户网站信息量增加对医疗保健提供者构成了挑战.
- 紧急消息需要快速关注,但不适合异步通信.
- 现有的工作流程可能会延迟关键消息审查.
研究的目的:
- 开发和实施一个人工智能系统来优先考虑患者门户消息.
- 为了减少审查高急性患者信息的时间.
- 将AI整合到电子健康记录 (EHR) 中,以改善临床工作流程.
主要方法:
- 开发了一个基于变压器 (BERT) 的双向编码器表示的大型语言模型.
- 在超过4万个患者发送的消息中训练模型,以识别紧急主题.
- 将AI模型集成到EHR系统中,用于实时消息优先级.
主要成果:
- 人工智能模型在验证中显示出高性能 (C-统计=97%).
- 集成的人工智能将高分数消息的未读消息时间减少了21分钟.
- 前后分析显示,消息审查周转时间有显著改善.
结论:
- 人工智能驱动的患者门户消息优先级改进了护理服务.
- 将人工智能与人类工作流程结合起来,对于成功实施至关重要.
- 未来的工作包括扩大AI能力,用于建议行动和响应起草.
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