Krumholz Harlan M
Harlan M. Krumholz (
Health Aff (Millwood). 2014 Jul;33(7):1163-70. doi: 10.1377/hlthaff.2014.0053.
Big data in medicine--massive quantities of health care data accumulating from patients and populations and the advanced analytics that can give those data 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 article 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 utilized, these reservoirs of data can be a practically inexhaustible source of knowledge to fuel a learning health care system.
医学中的大数据——从患者和人群中积累的海量医疗保健数据，以及能赋予这些数据意义的先进分析方法——有望成为知识生成的引擎，以满足患者、临床医生、管理人员、研究人员和卫生政策制定者广泛存在的未满足的信息需求。本文探讨了如何利用大数据来推进预测、绩效、发现和比较效果研究，以应对患者、人群和组织的复杂性。将大数据和下一代分析方法纳入临床和人群健康研究与实践，不仅需要新的数据来源，还需要新的思维、培训和工具。如果得到充分利用，这些数据宝库可以成为推动学习型医疗保健系统的几乎取之不尽的知识来源。
