Appl Clin Inform 2019; 10(03): 421-445
DOI: 10.1055/s-0039-1692186
Research Article
Georg Thieme Verlag KG Stuttgart · New York

Physicians Voluntarily Using an EHR-Based CDS Tool Improved Patients' Guideline-Related Statin Prescription Rates: A Retrospective Cohort Study

Timothy S. Chang
1  Department of Neurology, University of California, Los Angeles, Los Angeles, California, United States
,
Ashwin Buchipudi
2  Information Services and Solutions, University of California, Los Angeles, Los Angeles, California, United States
,
Gregg C. Fonarow
3  Division of Cardiology, Department of Medicine, University of California, Los Angeles, Los Angeles, California, United States
,
Michael A. Pfeffer
4  Division of General Internal Medicine, Department of Medicine, University of California, Los Angeles, Los Angeles, California, United States
,
Jennifer S. Singer
5  Department of Urology, University of California, Los Angeles, Los Angeles, California, United States
,
Eric M. Cheng
1  Department of Neurology, University of California, Los Angeles, Los Angeles, California, United States
› Author Affiliations
Funding This research was supported by NIH National Center for Advancing Translational Science (NCATS) UCLA CTSI Grant Number UL1TR001881.
Further Information

Publication History

02 January 2019

26 April 2019

Publication Date:
19 June 2019 (online)

Abstract

Background In 2013, the American College of Cardiology (ACC) and the American Heart Association (AHA) released a revised guideline on statin therapy initiation. The guideline included a 10-year risk calculation based on regression modeling, which made hand calculation infeasible. Compliance to the guideline has been suboptimal, as many patients were recommended but not prescribed statin therapy. Clinical decision support (CDS) tools may improve statin guideline compliance. Few statin guideline CDS tools evaluated clinical outcome.

Objectives We determined if use of a CDS tool, the statin macro, was associated with increased 2013 ACC/AHA statin guideline compliance at the level of statin prescription versus no statin prescription. We did not determine if each patient's statin prescription met ACC/AHA 2013 therapy intensity recommendations (high vs. moderate vs. low).

Methods The authors developed a clinician-initiated, EHR-embedded statin macro command (“statin macro”) that displayed the 2013 ACC/AHA statin guideline recommendation in the electronic health record documentation. We included patients who had a primary care visit during the study period (January 1–June 30, 2016), were eligible for statin therapy based on the ACC/AHA guideline prior to the study period, and were not prescribed statin therapy prior to the study period. We tested the association of macro usage and statin therapy prescription during the study period using relative risk and mixed effect logistic regression.

Results Subjects included 11,877 patients seen in primary care, who were retrospectively recommended statin therapy at study initiation based on the ACC/AHA guideline, but who had not received statin therapy. During the study period, 125 clinicians used the statin macro command for 389 of the 11,877 patients (3.2%). Of the 389 patients for whom that statin macro was used, 108 patients (28%) had a statin prescribed during the study period. Of the 11,488 for whom the statin macro was not used, 1,360 (13%) patients received a clinician-prescribed statin (relative risk 2.3, p < 0.001). Controlling for patient covariates and clinicians, statin macro usage was significantly associated with statin therapy prescription (odds ratio 2.86, p < 0.001).

Conclusion Although the statin macro had low uptake, its use was associated with a greater rate of statin prescriptions (dosage not determined) for patients whom 2013 ACC/AHA guidelines required statin therapy.

Protection of Human and Animal Subjects

The University of California, Los Angeles Institutional Review Board approved a waiver of authorization for this study (IRB#: 16–001676).


Supplementary Material