Bridging the Health Data Divide

被引:18
|
作者
Celi, Leo Anthony [1 ]
Davidzon, Guido [1 ]
Johnson, Alistair E. W. [1 ]
Komorowski, Matthieu [1 ]
Marshall, Dominic C. [1 ]
Nair, Sunil S. [1 ]
Phillips, Colin T. [1 ]
Pollard, Tom J. [1 ]
Raffa, Jesse D. [1 ]
Salciccioli, Justin D. [1 ]
Salgueiro, Francisco Muge [1 ]
Stone, David J. [1 ]
机构
[1] MIT Crit Data, 77 Massachusetts Ave, Cambridge, MA 02139 USA
基金
美国国家卫生研究院;
关键词
electronic health records; machine learning; health care policy; medical education; collaboration;
D O I
10.2196/jmir.6400
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
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.
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页数:6
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