Health Data and Data Governance
Health Data and Data Governance
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DOI：
10.3233/978-1-61499-291-2-67
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发表时间：
2013-01-01
期刊：
影响因子：
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通讯作者：
Grain, Heather
中科院分区：
文献类型：
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作者：
Hovenga, Evelyn J. S.;Grain, Heather
健康是一个知识产业，其基础是为支持护理、服务规划、融资和知识进步而收集的数据。越来越需要收集、检索和使用电子格式的健康记录信息，以提供更大的灵活性，因为这使得能够以多种位置和格式检索和显示数据，而不管数据是在哪里收集的。要做到这一点，电子保存的记录需要更好的结构和一致性。使用临床系统实时生成的记录中保存的数据也有可能减少获取知识所需的时间，因为收集研究特定信息的需要较少，只有在应用数据治理原则的情况下才有可能做到这一点。互联设备和信息系统现在正在产生前所未有的海量数据。分析和挖掘大量数据的能力，即“大数据”，为政策制定者和决策者提供了对工作和信息流的各个方面以及业务业务模式和趋势的新见解，并推动了更高的效率以及更安全和更有效的保健。这使决策者能够通过识别基于这些知识的触发因素来应用基于来自许多个体患者记录的知识而开发的规则和指导。在临床决策支持系统中，将关于个人的信息与基于从许多积累的信息中获得的知识的规则进行比较，以在临床过程中的适当时间提供指导。要做到这一点，必须以兼容和一致的方式表示单个系统中的数据和知识规则。本章描述数据属性；解释数据和信息之间的区别；概述对高质量数据的要求；显示健康数据标准的相关性；以及描述数据治理如何影响系统中内容的表示和信息的使用
Health is a knowledge industry, based on data collected to support care, service planning, financing and knowledge advancement. Increasingly there is a need to collect, retrieve and use health record information in an electronic format to provide greater flexibility, as this enables retrieval and display of data in multiple locations and formats irrespective of where the data were collected. Electronically maintained records require greater structure and consistency to achieve this. The use of data held in records generated in real time in clinical systems also has the potential to reduce the time it takes to gain knowledge, as there is less need to collect research specific information, this is only possible if data governance principles are applied. Connected devices and information systems are now generating huge amounts of data, as never before seen. An ability to analyse and mine very large amounts of data, "Big Data", provides policy and decision makers with new insights into varied aspects of work and information flow and operational business patterns and trends, and drives greater efficiencies, and safer and more effective health care. This enables decision makers to apply rules and guidance that have been developed based upon knowledge from many individual patient records through recognition of triggers based upon that knowledge. In clinical decision support systems information about the individual is compared to rules based upon knowledge gained from accumulated information of many to provide guidance at appropriate times in the clinical process. To achieve this the data in the individual system, and the knowledge rules must be represented in a compatible and consistent manner. This chapter describes data attributes; explains the difference between data and information; outlines the requirements for quality data; shows the relevance of health data standards; and describes how data governance impacts representation of content in systems and the use of that information