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Nat Rev Cardiol. 2016 Jun;13(6):350-9. doi: 10.1038/nrcardio.2016.42. Epub 2016 Mar 24.

Big data analytics to improve cardiovascular care: promise and challenges.

Author information

1
University of Colorado School of Medicine, 13001 East 17th Place, Aurora, Colorado 80045, USA.
2
VA Eastern Colorado Health System, Cardiology (111B), 1055 Clermont Street, Denver, Colorado 80220, USA.
3
Brigham and Women's Hospital, 75 Francis Street, Boston, Massachusetts 02115, USA.
4
Harvard T.H. Chan School of Public Health, 677 Huntington Avenue, Boston, Massachusetts 02115, USA.

Abstract

The potential for big data analytics to improve cardiovascular quality of care and patient outcomes is tremendous. However, the application of big data in health care is at a nascent stage, and the evidence to date demonstrating that big data analytics will improve care and outcomes is scant. This Review provides an overview of the data sources and methods that comprise big data analytics, and describes eight areas of application of big data analytics to improve cardiovascular care, including predictive modelling for risk and resource use, population management, drug and medical device safety surveillance, disease and treatment heterogeneity, precision medicine and clinical decision support, quality of care and performance measurement, and public health and research applications. We also delineate the important challenges for big data applications in cardiovascular care, including the need for evidence of effectiveness and safety, the methodological issues such as data quality and validation, and the critical importance of clinical integration and proof of clinical utility. If big data analytics are shown to improve quality of care and patient outcomes, and can be successfully implemented in cardiovascular practice, big data will fulfil its potential as an important component of a learning health-care system.

PMID:
27009423
DOI:
10.1038/nrcardio.2016.42
[Indexed for MEDLINE]

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