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The American Journal of Managed Care May 2016
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Potential of Risk-Based Population Guidelines to Reduce Cardiovascular Risk in a Large Integrated Health System
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Potential of Risk-Based Population Guidelines to Reduce Cardiovascular Risk in a Large Integrated Health System

Galina Inzhakova, MPH; Hui Zhou, PhD, MS; Macdonald Morris, PhD; Megan I. Early, MD, MPH; Anny H. Xiang, PhD; Steven J. Jacobsen, MD, PhD; and Stephen F. Derose, MD, MSHS
The authors evaluated the clinical applicability, accuracy, and implications of using an automated risk calculator and risk-based decision tool in an integrated health system.
We found that the automated risk calculator can be applied to a large proportion of a population with 1 or more years of EHR data with fairly good discrimination and predictiveness. This finding indicates a useful application to risk stratify large populations. We also found that a risk-based decision tool identified for possible treatment a group of patients at higher risk of CVD events than traditional guidelines, even without any increase in the number of patients treated. There thus exists the potential to further reduce population risk using such a tool. Automated risk calculators combined with decision support can individualize therapy for patients in a way that focuses on overall risk reduction rather than just biological targets. Further exploration of risk-based decision tools—with and without data imputation—compared with usual practice will help determine the value of such an approach. Ultimately, the use of such tools may depend on implementations that save effort in clinical practice.

Acknowledgments

The authors would like to thank David M. Eddy, PhD, founder and chief medical officer of Emeritus Archimedes, Inc, for his review of the manuscript; and Portia Summers, BS, Kaiser Permanente Southern California, for her help with preparation of the manuscript for submission.

Author Affiliations: Department of Research and Evaluation, Kaiser Permanente Southern California (GI, HZ, AHX, SJJ, SFD, MIE), Pasadena, CA; Archimedes, Inc (MM), San Francisco, CA.

Source of Funding: This study was funded by the Kaiser Permanente Health Plan.

Author Disclosures: At the time of the study IndiGO was a product of Archimedes, Inc, which was a wholly owned subsidiary of Kaiser Permanente. During the study and preparation of this manuscript, Dr Morris had stock options in Archimedes, Inc, was employed by Archimedes, and was inventor on risk stratification patents assigned to Archimedes; he is now affiliated with Symphony Health Performance Analytics, Alpharetta, GA. During the study and preparation of this manuscript, all other study personnel (including all those who obtained and analyzed the data) were employed by the Southern California Permanente Medical Group, which partners with the Kaiser Permanente Health Plan to deliver healthcare to health plan members. Dr Early is now affiliated with the Department of Obstetrics and Gynecology and Women’s Health, Montefiore Medical Center the University Hospital for Albert Einstein College of Medicine, Bronx, New York. The remaining authors report no other potential financial or conflicts of interest related to the subject in this article.

Authorship Information: Concept and design (MM, AHX, SJJ, SFD); acquisition of data (MM, MIE, SJJ, SFD); analysis and interpretation of data (GI, HZ, MIE, AHX, SJJ, SFD); drafting of the manuscript (GI, SFD); critical revision of the manuscript for important intellectual content (GI, HZ, MM, AHX, SJJ, SFD); statistical analysis (HZ, MM, SFD); obtaining funding (SJJ, SFD); administrative, technical, or logistic support (GI, MIE, SJJ, SFD); and supervision (SFD).

Address correspondence to: Stephen F. Derose, MD, MSHS, Department of Research and Evaluation, Kaiser Permanente Southern California, 100 S Los Robles, Pasadena, CA 91101. E-mail address: Stephen.F.Derose@kp.org.
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