Substantial progress in reducing cardiovascular disease (CVD) morbidity and mortality would be achieved if evidence-based guidelines for CVD risk factor control were implemented consistently in primary care settings. Electronic health record (EHR)-based clinical decision support (CDS) systems that identify uncontrolled CVD risk factors and provide individualized care recommendations improved rates of guideline-concordant CVD care in large, integrated healthcare settings, but little is known about how effective such CDS may be in safety net community health centers (CHCs). CHCs' socioeconomically vulnerable patients have far worse CVD risk factor control and higher rates of major CVD events than the general population. Implementing CDS that leads to improved CVD risk factor control in CHCs could reduce national disparities in CVD outcomes, but CHCs rarely have the resources to develop sophisticated CDS, and very few currently have such systems for CVD care. The proposed study is designed to address this. We will randomize 60 CHCs with a shared EHR to immediate vs. delayed implementation of a sophisticated CDS system that provides point-of-care CVD care recommendations to the primary care provider and the patient, and has been proven highly successful in large, integrated care settings. Before implementing the CDS, we will ask CHC patients and providers about the particular patient needs and perspectives and clinic workflows likely to influence adoption and impact of the CDS in CHCs. This input will inform development of CHC care team training strategies, and adaptation of the patient-facing aspects of the CDS system. We will measure adoption of the CDS, and impact of its use over time on CVD risk scores and risk factor control (blood pressure, HbA1c, lipid levels; aspirin use; smoking; body mass index) in high-CVD risk CHC patients. We will also conduct a mixed methods process evaluation, to identify facilitators and barriers to use of the CDS, and to iteratively develop and test strategies for supporting its adoption and ongoing use in CHC workflows. We anticipate that this intervention could (a) improve CVD care among low-income CHC patients, (b) reduce CVD care disparities between CHC populations and national rates, and (c) facilitate greater CHC patient engagement in CVD treatment decision-making and prioritization. The proposed work directly responds to PAR 15-279 goals: it addresses gaps in guideline- based care in high-risk populations with targeted, innovative, multi-level strategies; considers setting-specific needs; and supports patient engagement. Our team's research experience and established partnerships with key healthcare system stakeholders increase the likelihood of project success. Results will yield EHR- agnostic CDS tools for use by any CHC with an implementation guide, build knowledge about how to minimize disparities in CVD care and outcomes using scalable CDS strategies, and help translate investments in informatics into clinical benefit for millions of high-risk, low-income Americans.

Public Health Relevance

Our parent study is testing whether ?CV Wizard,? an EHR-based clinical decision support tool, improves cardiovascular disease risk management when used at in-person encounters in community health centers. Because the COVID-19 pandemic forced many community health centers (and other primary care providers) to shift from in-person to virtual care (telephone, video) encounters, we propose to add analyses to the parent study to determine how cardiovascular disease risk is managed in virtual encounters, and CV Wizard?s use and impact in that context.

National Institute of Health (NIH)
National Heart, Lung, and Blood Institute (NHLBI)
Research Project (R01)
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Fine, Larry
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Kaiser Foundation Research Institute
United States
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