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首页> 美国卫生研究院文献>AMIA Annual Symposium Proceedings >Why aren’t they happy? An analysis of end-user satisfaction with Electronic health records
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Why aren’t they happy? An analysis of end-user satisfaction with Electronic health records

机译：他们为什么不开心？最终用户对电子健康记录的满意度分析

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>Introduction. Implementations of electronic health records (EHR) have been met with mixed outcome reviews. Complaints about these systems have led to many attempts to have useful measures of end-user satisfaction. However, most user satisfaction assessments do not focus on high-level reasoning, despite the complaints of many physicians. Our study attempts to identify some of these determinants.>Method. We developed a user satisfaction survey instrument, based on pre-identified and important clinical and non-clinical clinician tasks. We surveyed a sample of in-patient physicians and focused on using exploratory factor analyses to identify underlying high-level cognitive tasks. We used the results to create unique, orthogonal variables representative of latent structure predictive of user satisfaction.>Results. Our findings identified 3 latent high-level tasks that were associated with end-user satisfaction: a) High- level clinical reasoning b) Communicate/coordinate care and c) Follow the rules/compliance.>Conclusion: We were able to successfully identify latent variables associated with satisfaction. Identification of communicability and high-level clinical reasoning as important factors determining user satisfaction can lead to development and design of more usable electronic health records with higher user satisfaction.
机译：>简介。电子健康记录（EHR）的实施已通过混合结果评估得到了满足。关于这些系统的投诉导致了许多尝试来获得有用的最终用户满意度度量。但是，尽管许多医生抱怨，但大多数用户满意度评估并未将重点放在高级推理上。我们的研究试图找出其中的一些决定因素。>方法。我们根据预先确定的重要临床和非临床临床医生任务开发了用户满意度调查工具。我们调查了住院医生的样本，并专注于使用探索性因素分析来识别潜在的高级认知任务。我们使用结果创建了代表用户满意度的潜在结构的唯一正交变量。>结果。我们的发现确定了3个与最终用户满意度相关的潜在高级任务：级别的临床推理b）沟通/协调护理，以及c）遵守规则/合规性。>结论：我们能够成功识别出与满意度相关的潜在变量。将可通信性和高级临床推理识别为确定用户满意度的重要因素，可以导致开发和设计具有更高用户满意度的更多可用电子健康记录。

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