Big data and new knowledge in medicine: the thinking, training, and tools needed for a learning health system.
Big data and new knowledge in medicine: the thinking, training, and tools needed for a learning health system.
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DOI：
10.1377/hlthaff.2014.0053
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发表时间：
2014-07
期刊：
影响因子：
--
通讯作者：
Krumholz HM
中科院分区：
文献类型：
--
作者：
Krumholz HM
医学中的大数据--从患者和人群中积累的大量医疗保健数据以及可以赋予其意义的高级分析--具有成为知识生成引擎的前景，这对于解决患者、临床医生、管理人员、研究人员和卫生政策制定者广泛的未满足的信息需求是必要的。本文探讨了利用大数据推进预测、性能、发现和比较有效性研究的方法，以解决患者、人群和组织的复杂性。将大数据和下一代分析应用于临床和人口健康研究和实践不仅需要新的数据源，还需要新的思维、培训和工具。如果使用得当，这些数据库实际上可以成为取之不尽的知识来源，为学习型医疗保健系统提供动力。
Big data in medicine--massive quantities of health care data accumulating from patients and populations and the advanced analytics that can give it meaning--hold the prospect of becoming an engine for the knowledge generation that is necessary to address the extensive unmet information needs of patients, clinicians, administrators, researchers, and health policy makers. This paper explores the ways in which big data can be harnessed to advance prediction, performance, discovery, and comparative effectiveness research to address the complexity of patients, populations, and organizations. Incorporating big data and next-generation analytics into clinical and population health research and practice will require not only new data sources but also new thinking, training, and tools. Adequately used, these reservoirs of data can be a practically inexhaustible source of knowledge to fuel a learning health care system.