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July 3, 2018

Big Data and Predictive Analytics: Recalibrating Expectations

Author Affiliations
  • 1Department of Health Sciences Research, Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, Minnesota
  • 2Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands
  • 3Predictive Analytics and Comparative Effectiveness Center, Institute for Clinical Research and Health Policy Studies, Tufts Medical Center, Boston, Massachusetts
JAMA. 2018;320(1):27-28. doi:10.1001/jama.2018.5602

With the routine use of electronic health records (EHRs) in hospitals, health systems, and physician practices, there has been rapid growth in the availability of health care data over the last decade. In addition to the structured data in EHRs, new methods such as natural language processing can derive meaning from unstructured data, permitting the capture of substantial clinical information embedded in clinical notes. Furthermore, the growth in the availability of registries and claims data and the linkages between all these data sources have created a big data platform in health care, vast in both size and scope.

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