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CorporateMeasures: A clinical analytics framework leading to clinical intelligence

机译:CorporateMeasures:临床分析框架,导致临床情报

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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:医疗组织中的患者信息分布在几个系统和数据孤岛上。临床医生根据患者健康记录中的数据做出决定。提高决策支持的效率需要集体知识所有患者信息。将患者数据与许多数据库中链接到一个数据仓库中的古典方法在建立临床分析时造成各种问题。在工程和业务中使用的性能测量和管理方法的实施适应了医疗情况,并开发了一个新的系统,允许不是技术专业人员开发,测试和将定制分析到患者健康数据的临床医生。本文的第I部分是介绍医疗保健数据分析中的问题和当前情况。第二部分规定了瞄准和目标。第三部分解释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种性能指标的结果,并通过技术和临床可用性方法评估系统。第五部分结束并讨论了未来的工作。

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