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Improvement in Cardiovascular Risk Prediction with Electronic Health Records

Journal of Cardiovascular Translational Research volume 9, pages 214–222 (2016)Cite this article

Abstract

The aim of this study was to compare the QRISKII, an electronic health data-based risk score, to the Framingham Risk Score (FRS) and atherosclerotic cardiovascular disease (ASCVD) score. Risk estimates were calculated for a cohort of 8783 patients, and the patients were followed up from November 29, 2012, through June 1, 2015, for a cardiovascular disease (CVD) event. During follow-up, 246 men and 247 women had a CVD event. Cohen’s kappa statistic for the comparison of the QRISKII and FRS was 0.22 for men and 0.23 for women, with the QRISKII classifying more patients in the higher-risk groups. The QRISKII and ASCVD were more similar with kappa statistics of 0.49 for men and 0.51 for women. The QRISKII shows increased discrimination with area under the curve (AUC) statistics of 0.65 and 0.71, respectively, compared to the FRS (0.59 and 0.66) and ASCVD (0.63 and 0.69). These results demonstrate that incorporating additional data from the electronic health record (EHR) may improve CVD risk stratification.

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Abbreviations

AF:

Atrial fibrillation

ASCVD:

Atherosclerotic cardiovascular disease

BMI:

Body mass index

CVD:

Cardiovascular disease

CHD:

Coronary heart disease

CKD:

Chronic kidney disease

EHR:

Electronic health record

HITECH:

Health Information Technology for Economic and Clinical Health

HOUSES:

Housing data

FRS:

Framingham Risk Score

HDL:

High-density lipoprotein

MI:

Myocardial infarction

RA:

Rheumatoid arthritis

REP:

Rochester Epidemiology Project

UK:

United Kingdom

USA:

United States of America

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Acknowledgments

This study was made possible by using the resources of the Rochester Epidemiology Project, which is supported by the National Institute on Aging of the National Institutes of Health under award number R01AG034676. The Mayo Clinic Biobank is supported by the Mayo Clinic Center for Individualized Medicine.

Author information

Authors and Affiliations

  1. Department of Health Sciences Research, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA

    Mindy M. Pike, Paul A. Decker, Nicholas B. Larson, Jennifer L. St. Sauver, Véronique L. Roger, Walter A. Rocca, Janet E. Olson & Suzette J. Bielinski

  2. Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN, USA

    Jennifer L. St. Sauver

  3. Department of Medicine, Mayo Clinic, Rochester, MN, USA

    Paul Y. Takahashi

  4. Division of Cardiovascular Diseases in the Department of Internal Medicine, Mayo Clinic, Rochester, MN, USA

    Véronique L. Roger

  5. Department of Neurology, Mayo Clinic, Rochester, MN, USA

    Walter A. Rocca

  6. Department of Surgery, Mayo Clinic, Rochester, MN, USA

    Virginia M. Miller

  7. Department of Physiology and Biomedical Engineering, Mayo Clinic, Rochester, MN, USA

    Virginia M. Miller

  8. Department of Healthcare Policy and Research, Weill Cornell Medical College, New York, NY, USA

    Jyotishman Pathak

Authors
  1. Mindy M. Pike
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  2. Paul A. Decker
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  3. Nicholas B. Larson
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  4. Jennifer L. St. Sauver
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  5. Paul Y. Takahashi
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  6. Véronique L. Roger
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  7. Walter A. Rocca
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  8. Virginia M. Miller
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  9. Janet E. Olson
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  10. Jyotishman Pathak
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  11. Suzette J. Bielinski
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Corresponding author

Correspondence to Suzette J. Bielinski.

Ethics declarations

All procedures followed were in accordance with the ethical standards of the responsible committee on human experimentation (institutional and national) and with the Helsinki Declaration of 1975, as revised in 2000. All research procedures were approved by the Institutional Review Committee of the Mayo Clinic.

Conflict of Interest

The authors declare that they have no competing interests.

Human and Animal Rights and Informed Consent

No animal studies were carried out by the authors for this article. The participants provided written and informed consent for the general research.

Additional information

Editor-in-Chief Jennifer L. Hall oversaw the review of this article

The content of this study is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

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Pike, M.M., Decker, P.A., Larson, N.B. et al. Improvement in Cardiovascular Risk Prediction with Electronic Health Records. J. of Cardiovasc. Trans. Res. 9, 214–222 (2016). https://doi.org/10.1007/s12265-016-9687-z

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