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A Sequential Data Analysis Approach to Electronic Health Record Workflow

机译:电子健康记录工作流程的顺序数据分析方法

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Failure to understand clinical workflow across electronic health record (EHR) tasks is a significant contributor to usability problems. In this paper, we employed sequential data analysis methods with the aim of characterizing patterns of 5 clinicians' information-gathering across 66 patients. Two analyses were conducted. The first one characterized the most common sequential patterns as reflected in the screen transitions. The second analysis was designed to mine and quantify the frequency of sequence occurrence. We observed 27 screen-transition patterns that were employed from 2 to 7 times. Documents/Images and Intake/ Output screens were viewed for nearly all patients indicating the importance of these information sources. In some cases, they were viewed more than once which may show that users are following inefficient patterns in the information gathering process. New quantitative methods of analysis as applied to interaction data can yield critical insights in robust designs that better support clinical workflow.
机译:未能了解电子健康记录(EHR)任务的临床工作流程是可用性问题的重要贡献者。在本文中,我们采用了顺序数据分析方法,目的是在66名患者中表征5名临床医生的信息收集的模式。进行了两次分析。第一个表征最常见的连续模式,如屏幕转换中反映的。第二个分析设计用于挖掘并量化序列发生的频率。我们观察了27种筛选过渡模式,从2〜7次使用。为几乎所有患者观看了文档/图像和进气/输出屏幕,表明这些信息来源重要性。在某些情况下,他们被视为多次,这可能表明用户在信息收集过程中遵循低效模式。适用于交互数据的新定量分析方法可以产生更强支持临床工作流程的强大设计的关键洞察。

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