July 9, 2014

Can the Learning Health Care System Be Educated With Observational Data?

Author Affiliations
  • 1Center for Evidence-Based Medicine, School of Public Health, Brown University, Providence, Rhode Island
  • 2Department of Health Services, Policy, and Practice, School of Public Health, Brown University, Providence, Rhode Island
  • 3Predictive Analytics and Comparative Effectiveness (PACE) Center, Institute for Clinical Research and Health Policy Studies, Tufts Medical Center, Boston, Massachusetts

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JAMA. 2014;312(2):129-130. doi:10.1001/jama.2014.4364

Given the complexity of medical decision making and the myriad questions that arise during the care of individuals, an expectation that every causal question be addressed with a randomized clinical trial (RCT) is not realistic. Nevertheless, large administrative databases linked with electronic health records, coupled with new statistical methods for extracting causal information from raw data, can complement clinical trial evidence, enabling a “learning health care system.” Yet despite continued advances in epidemiological and statistical methods and the advent of “big data,”1 there is concern that inferences from observational data can lead to poor health care decisions by misrepresenting association for causation.

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