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连续性医疗记录(CCR)的性能评估:移动健康管理系统中的解析模型

Performance evaluation of continuity of care records (CCRs): parsing models in a mobile health management system.

作者信息

Chen Hung-Ming, Liou Yong-Zan

机构信息

Department of Computer Science and Information Engineering, National Taichung University of Science and Technology, Taichung, Taiwan, Republic of China,

出版信息

J Med Syst. 2014 Oct;38(10):117. doi: 10.1007/s10916-014-0117-y. Epub 2014 Aug 3.

Abstract

In a mobile health management system, mobile devices act as the application hosting devices for personal health records (PHRs) and the healthcare servers construct to exchange and analyze PHRs. One of the most popular PHR standards is continuity of care record (CCR). The CCR is expressed in XML formats. However, parsing is an expensive operation that can degrade XML processing performance. Hence, the objective of this study was to identify different operational and performance characteristics for those CCR parsing models including the XML DOM parser, the SAX parser, the PULL parser, and the JSON parser with regard to JSON data converted from XML-based CCR. Thus, developers can make sensible choices for their target PHR applications to parse CCRs when using mobile devices or servers with different system resources. Furthermore, the simulation experiments of four case studies are conducted to compare the parsing performance on Android mobile devices and the server with large quantities of CCR data.

摘要

在移动健康管理系统中,移动设备充当个人健康记录(PHR)的应用托管设备,而医疗服务器则用于交换和分析PHR。最流行的PHR标准之一是连续护理记录(CCR)。CCR以XML格式表示。然而,解析是一项代价高昂的操作,会降低XML处理性能。因此,本研究的目的是针对那些CCR解析模型,包括XML DOM解析器、SAX解析器、PULL解析器以及针对从基于XML的CCR转换而来的JSON数据的JSON解析器,确定不同的操作和性能特征。这样,开发人员在使用具有不同系统资源的移动设备或服务器来解析CCR时,就可以为其目标PHR应用做出明智的选择。此外,还进行了四个案例研究的模拟实验,以比较在安卓移动设备和服务器上处理大量CCR数据时的解析性能。

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