Effect of a Computer-Guided, Quality Improvement Program for Cardiovascular Disease Risk Management in Primary Health Care. (January 2015)

• Record Type: Journal Article
• Authors: Peiris, David; Usherwood, Tim; Panaretto, Kathryn; Harris, Mark; Hunt, Jennifer; Redfern, Julie; Zwar, Nicholas; Colagiuri, Stephen; Hayman, Noel; Lo, Serigne; Patel, Bindu; Lyford, Marilyn; MacMahon, Stephen; Neal, Bruce; Sullivan, David; Cass, Alan; Jackson, Rod; Patel, Anushka
• Is Part Of: Circulation. Volume 8:Number 1(2015)
• Publication Date: 2015-01
• Subjects: Cardiovascular system -- Diseases -- Treatment -- Periodicals; Cardiovascular system -- Diseases -- Research -- Periodicals; Outcome assessment (Medical care) -- Periodicals; Evidence-based medicine -- Periodicals; 616.1007
• DOI: 10.1161/CIRCOUTCOMES.114.001235
• Languages: English
• ISSNs: 1941-7713

Abstract

<abstract> <title> <x xml:space="preserve">Abstract</x> </title> <sec> <title>Background—</title> <p>Despite effective treatments to reduce cardiovascular disease risk, their translation into practice is limited.</p> </sec> <sec> <title>Methods and Results—</title> <p>Using a parallel arm cluster-randomized controlled trial in 60 Australian primary healthcare centers, we tested whether a multifaceted quality improvement intervention comprising computerized decision support, audit/feedback tools, and staff training improved (1) guideline-indicated risk factor measurements and (2) guideline-indicated medications for those at high cardiovascular disease risk. Centers had to use a compatible software system, and eligible patients were regular attendees (Aboriginal and Torres Strait Islander people aged ≥35 years and others aged ≥45 years). Patient-level analyses were conducted using generalized estimating equations to account for clustering. Median follow-up for 38 725 patients (mean age, 61.0 years; 42% men) was 17.5 months. Mean monthly staff support was <1 hour/site. For the coprimary outcomes, the intervention was associated with improved overall risk factor measurements (62.8% versus 53.4% risk ratio; 1.25; 95% confidence interval, 1.04–1.50; <italic>P</italic>=0.02), but there was no significant differences in recommended prescriptions for the high-risk cohort (n=10 308; 56.8% versus 51.2%; <italic>P</italic>=0.12). There were significant treatment escalations (new prescriptions or increased numbers of medicines) for antiplatelet (17.9% versus 2.7%; <italic>P</italic><0.001), lipid-lowering (19.2% versus 4.8%; <italic>P</italic><0.001), and blood pressure–lowering medications (23.3% versus 12.1%; <italic>P</italic>=0.02).</p> </sec> <sec> <title>Conclusions—</title> <p>In Australian primary healthcare settings, a computer-guided quality improvement intervention, requiring minimal support, improved cardiovascular disease risk measurement but did not increase prescription rates in the high-risk group. Computerized quality improvement tools offer an important, albeit partial, solution to improving primary healthcare system capacity for cardiovascular disease risk management.</p> </sec> <sec> <title>Clinical Trial Registration—</title> <p>URL: <ext-link ext-link-type="uri" xlink:href="https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=336630" xlink:type="simple" xmlns:xlink="http://www.w3.org/1999/xlink">https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=336630</ext-link>. Australian New Zealand Clinical Trials Registry No. 12611000478910.</p> </sec> </abstract>