在EHR工作流程中探索任务模式,使用动作序列嵌入和基于图形的分析
Seunghwan Kim1,2, Thomas Kannampallil2,3,4, Brett D Wick5
1Roy and Diana Vagelos Division of Biology and Biomedical Sciences, Washington University St. Louis, Saint Louis, USA.
Studies in health technology and informatics
|August 8, 2025
概括
这项研究引入了新的方法来分析电子健康记录 (EHR) 中的临床医生工作流程. 该研究成功地确定了不同的临床任务组,为自动化工作流模式表征铺平了道路.
科学领域:
- 医疗信息学 医疗信息学
- 临床工作流分析分析
- 在医疗保健中的数据挖掘.
背景情况:
- 电子健康记录 (EHR) 产生了大量的审计日志数据.
- 了解EHR系统中的临床医生工作流程对于优化医疗保健提供和系统设计至关重要.
- 目前分析EHR审计日志的方法通常是手动的,耗时的.
研究的目的:
- 开发和应用新的计算技术来分析EHR系统中的临床医生工作流程.
- 在EHR审计日志数据中描述临床医生活动的不同模式.
- 探索无监督机器学习在识别工作流程模式方面的潜力.
主要方法:
- 利用基于上下文的嵌入和基于图形的维度减少的新组合.
- 应用这些技术来分析基于EHR的审计日志数据的序列.
- 雇员无监督学习方法来识别工作流程模式,没有预定义的标签.
主要成果:
- 根据EHR审计日志序列,成功确定了不同的临床任务组.
- 证明了结合嵌入和缩小维度技术的有效性.
- 揭示了临床医生使用电子记忆录的基本结构.
结论:
- 开发的方法提供了一种强大的,半自动化的方法来描述EHR临床医生的工作流程.
- 这些发现表明,无监督方法在了解和优化医疗保健IT使用方面有很大的潜力.
- 进一步的研究可以在这些技术的基础上进行,以提高EHR系统设计和临床效率.
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