title: Big data and new knowledge in medicine: the thinking, training, and tools needed for a learning health system.
abstract: 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.
authors.affiliation: Harlan M. Krumholz (Harlan.Krumholz@yale.edu) is the Harold H. Hines Jr. Professor of Medicine and Epidemiology and Public Health at the Yale University School of Medicine, in New Haven, Connecticut.
authors.forename: Harlan M
authors.initials: HM
authors.lastname: Krumholz
mesh_terms: D003627:Data Interpretation, Statistical; D057225:Data Mining / Q000379:methods*; D066264:Datasets as Topic; D020000:Decision Support Systems, Clinical; D003695:Delivery of Health Care / Q000458:organization & administration*; D006801:Humans; D007858:Learning; D008490:Medical Informatics; D013850:Thinking
keywords: Information Technology; Medicine/Clinical Issues; Research And Technology