Key result
Implementation research methods are essential to evaluate the clinical impact of predictive analytics in precision medicine.
Why the study?
Realizing the opportunities of predictive analytics in heart, lung, blood, and sleep disorders requires implementation research methods to define benefits, harms, reach, sustainability, and resource utilization implications.
This NHLBI workshop review highlights that realizing the clinical and public health potential of predictive analytics requires pairing data science tools with implementation science to evaluate real-world benefits, harms, reach, and sustainability.
Answers are grounded in this paper and cite their sources.
Predictive analytics warrant caution before clinical or public health adoption; leaves open optimal implementation frameworks for precision cardiovascular care.
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.
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Pearson et al. (2020) conducted a review in Heart, lung, blood, and sleep disorders. Predictive analytics and implementation research was evaluated. Predictive analytics require implementation research methods to define benefits, harms, reach, sustainability, and resource utilization in precision medicine and public health.
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