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CorporateMeasures: A clinical analytics framework leading to clinical intelligence

机译:CorporateMeasures:产生临床智能的临床分析框架

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Patient information in healthcare organizations is distributed across several systems and data silos. Clinicians make decisions based on data in patient health records. Improving the efficiency of decision-support requires collective knowledge of all patient information. The classical approach of linking patient data from many databases into one data warehouse poses various problems when it comes to building clinical analytics. An implementation of the Performance Measurement and Management approach used in Engineering and Business is adapted to healthcare scenarios, and a new system is developed that allows clinicians that are not technical professionals to develop, test and apply custom analytics to patient health data. Part I of this paper is an introduction to the problems and current situation in healthcare data analytics. Part II states the aim and objectives. Part III explains the system design and its modular components. Part IV presents the results of three performance indicators evaluated through the system, and evaluates the system through technical and clinical usability methods. Part V concludes and discusses future work.
机译:医疗保健组织中的患者信息分布在多个系统和数据孤岛中。临床医生根据患者健康记录中的数据做出决定。要提高决策支持的效率,需要对所有患者信息有共同的了解。将来自多个数据库的患者数据链接到一个数据仓库中的经典方法在构建临床分析时会遇到各种问题。工程和业务中使用的绩效评估和管理方法的实现方式适用于医疗保健场景,并且开发了一个新系统,该系统允许非技术专业人员的临床医生开发,测试并将定制分析应用于患者健康数据。本文的第一部分是对医疗保健数据分析中的问题和现状的介绍。第二部分阐述了目的和目标。第三部分介绍了系统设计及其模块化组件。第四部分介绍了通过系统评估的三个性能指标的结果,并通过技术和临床可用性方法对系统进行了评估。第五部分总结并讨论了未来的工作。

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