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J Am Coll Cardiol. 2018 Dec 25;72(25):3301-3309. doi: 10.1016/j.jacc.2018.09.079.

Future of Personalized Cardiovascular Medicine: JACC State-of-the-Art Review.

Author information

1
Duke Forge, Duke University School of Medicine, Durham, North Carolina; Verily Life Sciences (Alphabet), South San Francisco, California; Stanford University Department of Medicine, Stanford, California. Electronic address: robert.califf@duke.edu.

Abstract

Previous decades have seen significant progress in the biological understanding of cardiovascular disease, as well as major advances in computational and information technologies. However, anticipated improvements in outcomes, quality, and cost of cardiovascular medicine at the individual and population levels from these advances have lagged expectations. Further, trends showing widening gaps in the pace of technological development and its successful uptake and application in practice suggests that substantial systemic changes are needed. Recent declines in key U.S. health outcomes have added further urgency to seek scalable approaches that deliver the right treatment to the right patient and to develop information-driven policies that improve health. The clinical care and research enterprises are currently in the midst of assimilating changes entrained by a "fourth industrial revolution" marked by the convergence of biology, physical sciences, and information science. These changes, if managed appropriately, can simultaneously enable cost-effective personalized medical care as well as more effective and targeted population health interventions. In this paper derived from a lecture in honor of cardiologist Paul Dudley White, the author explores how White's prescient insights into prevention and treatment continue to resonate today as we seek to assimilate ubiquitous computing, sophisticated sensor technologies, and bidirectional digital communication into the practice of cardiology. How the ongoing acceleration in basic science and information technologies can be wedded to the principles articulated by White as we pursue scalable approaches to personalized medicine is also examined.

KEYWORDS:

data science; electronic health record; precision medicine; registry

PMID:
30573033
DOI:
10.1016/j.jacc.2018.09.079

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