Simpao Allan F, Ahumada Luis M, Gálvez Jorge A, Rehman Mohamed A
Department of Anesthesiology and Critical Care Medicine, Perelman School of Medicine at the University of Pennsylvania and the Children's Hospital of Philadelphia, 34th Street and Civic Center Blvd., Suite 9329, Philadelphia, PA, 19104-4399, USA,
J Med Syst. 2014 Apr;38(4):45. doi: 10.1007/s10916-014-0045-x. Epub 2014 Apr 3.
Federal investment in health information technology has incentivized the adoption of electronic health record systems by physicians and health care organizations; the result has been a massive rise in the collection of patient data in electronic form (i.e. "Big Data"). Health care systems have leveraged Big Data for quality and performance improvements using analytics-the systematic use of data combined with quantitative as well as qualitative analysis to make decisions. Analytics have been utilized in various aspects of health care including predictive risk assessment, clinical decision support, home health monitoring, finance, and resource allocation. Visual analytics is one example of an analytics technique with an array of health care and research applications that are well described in the literature. The proliferation of Big Data and analytics in health care has spawned a growing demand for clinical informatics professionals who can bridge the gap between the medical and information sciences.
联邦政府对健康信息技术的投资促使医生和医疗保健机构采用电子健康记录系统；结果是以电子形式（即“大数据”）收集的患者数据大幅增加。医疗保健系统利用大数据，通过分析——将数据与定量和定性分析相结合以进行决策的系统方法——来提高质量和绩效。分析已应用于医疗保健的各个方面，包括预测风险评估、临床决策支持、家庭健康监测、财务和资源分配。可视化分析是一种分析技术的示例，其在医疗保健和研究中的一系列应用在文献中有详细描述。医疗保健领域大数据和分析的激增，引发了对能够弥合医学与信息科学之间差距的临床信息学专业人员的需求不断增长。
