David Peiris1, Tim Usherwood2, Kathryn Panaretto2, Mark Harris2, Jennifer Hunt2, Julie Redfern2, Nicholas Zwar2, Stephen Colagiuri2, Noel Hayman2, Serigne Lo2, Bindu Patel2, Marilyn Lyford2, Stephen MacMahon2, Bruce Neal2, David Sullivan2, Alan Cass2, Rod Jackson2, Anushka Patel2. 1. From The George Institute for Global Health, University of Sydney, Sydney, New South Wales, Australia (D.P., J.R., S.L., B.P., M.L., S.M., B.N., A.P.); Westmead Clinical School (T.U.), The Boden Institute (S.C.), and Sydney Medical School (D.S.) University of Sydney, New South Wales, Sydney, Australia; Queensland Aboriginal and Islander Health Council, Brisbane, Queensland, Australia (K.P.); Centre for Primary Health Care and Equity (M.H.) and School of Public Health and Community Medicine (N.Z.) University of New South Wales, Sydney, New South Wales, Australia; Aboriginal Health and Medical Research Council, Sydney, New South Wales, Australia (J.H.); Inala Indigenous Health Service, Queensland Health, Brisbane, Queensland, Australia (N.H.); Menzies School of Health Research, Darwin, Northern Territory, Australia (A.C.); and School of Population Health, University of Auckland, Auckland, New Zealand (R.J.). dpeiris@georgeinstitute.org. 2. From The George Institute for Global Health, University of Sydney, Sydney, New South Wales, Australia (D.P., J.R., S.L., B.P., M.L., S.M., B.N., A.P.); Westmead Clinical School (T.U.), The Boden Institute (S.C.), and Sydney Medical School (D.S.) University of Sydney, New South Wales, Sydney, Australia; Queensland Aboriginal and Islander Health Council, Brisbane, Queensland, Australia (K.P.); Centre for Primary Health Care and Equity (M.H.) and School of Public Health and Community Medicine (N.Z.) University of New South Wales, Sydney, New South Wales, Australia; Aboriginal Health and Medical Research Council, Sydney, New South Wales, Australia (J.H.); Inala Indigenous Health Service, Queensland Health, Brisbane, Queensland, Australia (N.H.); Menzies School of Health Research, Darwin, Northern Territory, Australia (A.C.); and School of Population Health, University of Auckland, Auckland, New Zealand (R.J.).
Abstract
BACKGROUND: Despite effective treatments to reduce cardiovascular disease risk, their translation into practice is limited. METHODS AND RESULTS: 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 andothers 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; P=0.02), but there was no significant differences in recommended prescriptions for the high-risk cohort (n=10,308; 56.8% versus 51.2%; P=0.12). There were significant treatment escalations (new prescriptions or increased numbers of medicines) for antiplatelet (4.3% versus 2.7%; P=0.01), and BP lowering (18.2% versus 11.0%; P=0.02) but not lipid-lowering medications. CONCLUSIONS: 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. CLINICAL TRIAL REGISTRATION URL: https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=336630. Australian New Zealand Clinical Trials Registry No. 12611000478910.
RCT Entities:
BACKGROUND: Despite effective treatments to reduce cardiovascular disease risk, their translation into practice is limited. METHODS AND RESULTS: 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; P=0.02), but there was no significant differences in recommended prescriptions for the high-risk cohort (n=10,308; 56.8% versus 51.2%; P=0.12). There were significant treatment escalations (new prescriptions or increased numbers of medicines) for antiplatelet (4.3% versus 2.7%; P=0.01), and BP lowering (18.2% versus 11.0%; P=0.02) but not lipid-lowering medications. CONCLUSIONS: 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. CLINICAL TRIAL REGISTRATION URL: https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=336630. Australian New Zealand Clinical Trials Registry No. 12611000478910.
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