用药核对任务的过程挖掘与民族志研究
Process Mining and Ethnography Study of Medication Reconciliation Tasks.
作者信息
Vellore Vaishak Ramesh, Grando M Adela, Duncan Benjamin, Kaufman David R, Furniss Stephanie K, Doebbeling Bradley N, Poterack Karl A, Miksch Timothy, Helmers Richard A
机构信息
Fulton Schools of Engineering, Arizona State University, AZ, US.
Biomedical Informatics, College of Health Solutions, Arizona State University, AZ, US.
出版信息
AMIA Annu Symp Proc. 2020 Mar 4;2019:1167-1176. eCollection 2019.
We studied the medication reconciliation (MedRec) task through analysis of computer logs and ethnographic data. Time spent by healthcare providers performing MedRec was compared between two different EHR systems used at four different regional perioperative settings. Only one of the EHRs used at two settings generated computer logs that supported automatic discovery of the MedRec task. At those two settings, 53 providers generated 383 MedRec instances. Findings from the computer logs were validated with ethnographic data, leading to the identification and removal of 47 outliers. Without outliers, one of the settings had slightly smaller mean (SD) time in seconds 67.3 (40.2) compared with the other, 92.1 (25). The difference in time metrics was statistically significant (p<.001). Reusability of an existing task-based analytic method allowed for rapid study of EHR-based workflow and task.
我们通过分析计算机日志和人种志数据研究了用药核对（MedRec）任务。在四个不同的区域围手术期环境中使用的两种不同电子健康记录（EHR）系统之间，比较了医疗服务提供者执行MedRec所花费的时间。在两个环境中使用的EHR中，只有一个生成了支持自动发现MedRec任务的计算机日志。在这两个环境中，53名提供者生成了383个MedRec实例。计算机日志的结果用人种志数据进行了验证，从而识别并去除了47个异常值。去除异常值后，其中一个环境的平均（标准差）时间（以秒为单位）略短，为67.3（40.2），而另一个环境为92.1（25）。时间指标的差异具有统计学意义（p<0.001）。现有基于任务的分析方法的可重用性使得能够快速研究基于EHR的工作流程和任务。
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