CV Wizard: Does a Clinical Decision Support Tool Improve CVD Risk Factor Control in Safety Net Clinics?

Overview

This project aims to reduce disparities in cardiovascular disease (CVD) risk factor control and in rates of heart attacks and strokes among the low-income, racially / ethnically diverse Americans who receive primary care at safety net community health centers (CHCs). To achieve this important objective, the investigators will adapt a successful clinical decision support (CDS) system currently used in CVD care at several large, integrated health care systems, to meet the patient needs and workflow processes of 60 CHCs. The investigators will determine if use of this CDS improves CVD care, reduces disparities in CVD care and outcomes, and increases patient engagement in CVD treatment choices, in CHCs. Results of this randomized trial will help accelerate the translation of major investments in health informatics systems into substantial clinical benefits for large numbers of high-risk, low-income patients. Results will also provide a template for CVD care improvement that can be spread to other CHCs and extended to other clinical conditions.

The investigators seek to learn whether clinical decision support (CDS) systems from well-resourced care settings are effective in safety net community health centers (CHCs), and how to enhance such cross-setting implementation. Thus, the investigators propose a clinic-randomized, pragmatic trial of the uptake and impact of the 'CV Wizard' CDS tool in 60 CHCs that share a linked electronic health record. CV Wizard summarizes each patient's reversible CVD risks, generates prioritized, guideline-based care recommendations based on those risks, and shows these in a 'provider view' and a 'patient view,' enabling patient engagement. Use rates and satisfaction with this CDS were high in the large healthcare delivery system where it was developed and tested. The investigators will: study its impact in the CHC setting, assess uptake of the CDS system, assess strategies for integrating it into CHC workflows, and its impact on patients' CVD risk and risk factor management. The investigators hypothesize that this cutting-edge CDS will improve rates of guideline-based CVD preventive care in CHC patients, who experience disparities in CVD risk factors, care and outcomes. The 60 study clinics will be members of OCHIN, Inc., a non-profit health center-controlled network and national leader in health information technology for CHCs. OCHIN's leadership enthusiastically supports the proposed work and will help ensure that recruitment goals are met. The investigators will partner with stakeholders / medical leadership from OCHIN's member clinics at every step, via existing structures. This study addresses gaps in guideline-based CVD care in high-risk populations, using targeted, multi-level strategies; considers setting-specific needs; tests how CDS affects guideline implementation in community clinics; and uses technology to support patient engagement. Results will yield knowledge about providing CHCs with cutting-edge CDS, and associated impacts on CVD disparities. The innovative study is the second trial to implement CDS tools from private care settings in CHCs, and the first to do so with complex CDS tools that address a range of CVD risk management guidelines, make prioritized care recommendations, and facilitate point-of-care patient engagement. Results could lead to substantial improvements in CVD prevention, care, and outcomes in CHCs nationwide. Our overarching aims are to: Aim 1. Conduct a clinic-randomized trial of the impact of an evidence-based point-of-care CDS system on (i) overall CVD risk scores, and (ii) control of individual CVD risks (blood pressure; HbA1c, lipid levels; aspirin use; smoking; body mass index), among high CVD risk CHC adult patients. H1: High CVD risk patients in Arm 1 CHCs will have significantly lower overall CVD risk scores over a 12-month post-index visit period, compared to those in Arm 2 CHCs. H2: High CVD risk patients in Arm 1 CHCs who have poor control of specific CVD risk factors at an index visit will have significantly better control of those factors over a 12 month post-index visit period, compared to those in Arm 2 CHCs. H3: Disparities in specific CVD risk factor control between CHC patients' versus national CVD risk factor control rates will be significantly reduced by 18 months post-implementation in each Arm (secondary analysis). Aim 2. Develop and hone need-based implementation support protocols to help Arm 1 CHCs implement the CV Wizard CDS system into their standard workflows; assess whether use of the protocols developed for Arm 1 CHCs accelerates implementation and adoption of the CDS system in the Arm 2 CHCs. H4: CDS uptake into CHC workflows will be significantly faster in Arm 2 CHCs than in Arm 1 CHCs. Aim 3. Conduct a mixed methods process evaluation, guided by the Technology Acceptance Model, to identify and address patient, provider, and delivery system barriers to uptake / impact of this CDS in CHCs.