Bridging the Health Data Divide

J Med Internet Res. 2016 Dec 20;18(12):e325. doi: 10.2196/jmir.6400.

Abstract

Fundamental quality, safety, and cost problems have not been resolved by the increasing digitization of health care. This digitization has progressed alongside the presence of a persistent divide between clinicians, the domain experts, and the technical experts, such as data scientists. The disconnect between clinicians and data scientists translates into a waste of research and health care resources, slow uptake of innovations, and poorer outcomes than are desirable and achievable. The divide can be narrowed by creating a culture of collaboration between these two disciplines, exemplified by events such as datathons. However, in order to more fully and meaningfully bridge the divide, the infrastructure of medical education, publication, and funding processes must evolve to support and enhance a learning health care system.

Keywords: collaboration; electronic health records; health care policy; machine learning; medical education.

MeSH terms

  • Delivery of Health Care / methods*
  • Education, Medical
  • Electronic Health Records*
  • Humans
  • Machine Learning