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 (17.9% versus 2.7%; P<0.001), lipid-lowering (19.2% versus 4.8%; P<0.001), and blood pressure-lowering medications (23.3% versus 12.1%; P=0.02). 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.
AD - 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.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 (17.9% versus 2.7%; P<0.001), lipid-lowering (19.2% versus 4.8%; P<0.001), and blood pressure-lowering medications (23.3% versus 12.1%; P=0.02). 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.
PY - 2015 SN - 1941-7705 (Electronic)