학술논문
Precision Health Analytics With Predictive Analytics and Implementation Research: JACC State-of-the-Art Review.
Document Type
Journal Article
Author
Pearson, Thomas A; Califf, Robert M; Roper, Rebecca; Engelgau, Michael M; Khoury, Muin J; Alcantara, Carmela; Blakely, Craig; Boyce, Cheryl Anne; Brown, Marishka; Croxton, Thomas L; Fenton, Kathleen; Green Parker, Melissa C; Hamilton, Andrew; Helmchen, Lorens; Hsu, Lucy L; Kent, David M; Kind, Amy; Kravitz, John; Papanicolaou, George John; Prosperi, Mattia
Source
Subject
*CARDIOLOGY
*PUBLIC health
*MEDICAL care
*PROGNOSIS
*NEWSLETTERS
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Language
ISSN
0735-1097
Abstract
Emerging data science techniques of predictive analytics expand the quality and quantity of complex data relevant to human health and provide opportunities for understanding and control of conditions such as heart, lung, blood, and sleep disorders. To realize these opportunities, the information sources, the data science tools that use the information, and the application of resulting analytics to health and health care issues will require implementation research methods to define benefits, harms, reach, and sustainability; and to understand related resource utilization implications to inform policymakers. This JACC State-of-the-Art Review is based on a workshop convened by the National Heart, Lung, and Blood Institute to explore predictive analytics in the context of implementation science. It highlights precision medicine and precision public health as complementary and compelling applications of predictive analytics, and addresses future research and training endeavors that might further foster the application of predictive analytics in clinical medicine and public health. [ABSTRACT FROM AUTHOR]