现有电子病历的自动临床文件重要性估计器。体系结构和实现

Bruno Santos, P. Rodrigues, R. Cruz-Correia
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引用次数: 1

摘要

OPTIM项目的目标是通过预测临床文档的相关性来优化电子健康记录(EHR)的图形用户界面,并在特定时间为给定用户提供相关文档的排序列表。本文描述了关联分配排序原型的体系结构和实现中的一些问题。原型的设计基于两个组件:OPTIM Core,具有逻辑表示、估计服务器的集成和web服务层;OPTIM web,具有显示结果的用户界面。在模拟环境中,原型与电子病历集成进行了测试。结果令人鼓舞,但也暴露出某种程度上缺乏安全性(保密性)。它现在具有每秒对10个文档进行评级的能力。尽管如此,基于数学模型的临床相关性评级等功能的集成可以包含在现有的电子病历中,从而潜在地提高其可用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An automatic clinical document importance estimator for an existing electronic patient record — Architecture and implementation
The goal of the OPTIM project is to optimize the graphical user interface of an electronic health record (EHR) by predicting clinical documents' relevance and provide a ranked list of relevant documents for the given user at a certain time. This paper describes the architecture of the relevance assignment and ranking prototype and some implementation issues. The prototype's design is based on two components: OPTIM Core, with logical representation, estimation server's integration and the webservice layer, and the OPTIM WebUI, with the user interface for presenting the results. The prototype was tested in integration with an EHR using a simulated environment. The results were encouraging but yet they revealed a certain lack of security (confidentiality). It has now the capacity of rating 10 documents per second. Nonetheless, the integration of features such as rating clinical relevance based on mathematical models can be included in existing EHR potentially improving their usability.
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