CV Wizard: Does a Prioritized, Point-of-Care Clinical Decision Support Tool Improve Guideline-Based CVD Risk Factor Control in Safety Net Clinics?

PROJECT SUMMARY / ABSTRACT: Substantial progress in reducing cardiovascular disease (CVD)morbidity and mortality would be achieved if evidence-based guidelines for CVD risk factor control wereimplemented consistently in primary care settings. Electronic health record (EHR)-based clinical decisionsupport (CDS) systems that identify uncontrolled CVD risk factors and provide individualized carerecommendations 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 ofmajor CVD events than the general population. Implementing CDS that leads to improved CVD risk factorcontrol in CHCs could reduce national disparities in CVD outcomes, but CHCs rarely have the resources todevelop sophisticated CDS, and very few currently have such systems for CVD care. The proposed study isdesigned to address this. We will randomize 60 CHCs with a shared EHR to immediate vs. delayedimplementation of a sophisticated CDS system that provides point-of-care CVD care recommendations tothe primary care provider and the patient, and has been proven highly successful in large, integrated caresettings. Before implementing the CDS, we will ask CHC patients and providers about the particular patientneeds 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-facingaspects of the CDS system. We will measure adoption of the CDS, and impact of its use over time on CVDrisk scores and risk factor control (blood pressure, HbA1c, lipid levels; aspirin use; smoking; body massindex) in high-CVD risk CHC patients. We will also conduct a mixed methods process evaluation, to identifyfacilitators and barriers to use of the CDS, and to iteratively develop and test strategies for supporting itsadoption and ongoing use in CHC workflows. We anticipate that this intervention could (a) improve CVD careamong low-income CHC patients, (b) reduce CVD care disparities between CHC populations and nationalrates, and (c) facilitate greater CHC patient engagement in CVD treatment decision-making andprioritization. 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-specificneeds; and supports patient engagement. Our team's research experience and established partnerships withkey 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 tominimize disparities in CVD care and outcomes using scalable CDS strategies, and help translateinvestments in informatics into clinical benefit for millions of high-risk, low-income Americans.