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Specifying Design Criteria for Electronic Medical Record Interface Using Cognitive Framework

机译:使用认知框架为电子病历接口指定设计标准

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摘要

As the healthcare industry transitions from paper to electronic medical records (EMRs), medical informatics researchers face the task of ensuring that the electronic presentation of the information remains usable and effective while capitalizing on the ability of EMRs to tailor information to different users. In our research, we focus on utilizing formal cognitive science methodology to guide the conversion of paper-based narrative discharge summaries to a more dynamic, structured electronic version. In this paper, we present the results of a cognitive analytic study () that determines a ‘core’ component in medical narratives and () that compares the use of structured and narrative texts by physicians with varying expertise. Specifically, we studied six psychiatrists at three levels of expertise— experts, intermediates, and novices. The subjects were given two clinical case scenarios with discharge summaries and asked to verbalize their thoughts as they read through the summaries. The interview transcripts were analyzed for recalls and inferences generated in the verbalization. Based on experts’ verbalizations, the discharge summaries were organized into a more structured form and used in the interview of other subjects. Novice-level subjects had more recall with the structured than with the narrative format. More errors were also made in recall with the narrative than with the structured text. We discuss how these results are valuable in designing an EMR interface to reduce errors and to support users of different expertise.
机译:随着医疗保健行业从纸质过渡到电子病历(EMR),医学信息学研究人员面临的任务是确保信息的电子呈现方式保持可用和有效,同时利用EMR为不同用户量身定制信息的能力。在我们的研究中,我们专注于利用正式的认知科学方法论来指导将基于纸张的叙述性摘要转换为更具动态性,结构化的电子版本。在本文中,我们介绍了一项认知分析研究的结果(),该研究确定医学叙事中的“核心”组成部分,并且()比较具有不同专业知识的医生对结构化和叙事文本的使用。具体来说,我们研究了三个专家级别的六位精神科医生-专家,中级和新手。给受试者两个出院摘要的临床案例,并要求他们在阅读摘要时表达自己的想法。分析了访谈笔录,以了解口头表达中产生的回忆和推论。基于专家的口头表达,出院总结被组织成更具结构化的形式,并被用于其他主题的访谈中。新手级别的对象对结构化的回忆比对叙事格式的回忆要多。与结构化文本相比,叙述中的回忆还产生了更多错误。我们讨论了这些结果在设计EMR界面以减少错误并为不同专业知识的用户提供支持方面的价值。

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