TY - JOUR KW - Female KW - Humans KW - Aged KW - Male KW - Treatment Outcome KW - Middle Aged KW - Risk Factors KW - Time Factors KW - Australia KW - Randomized Controlled Trials as Topic KW - Guideline Adherence KW - Practice Guidelines as Topic KW - Risk Reduction Behavior KW - Quality Improvement KW - Decision Support Techniques KW - Primary Health Care KW - Drug Prescriptions KW - Cardiovascular Agents/adverse effects/*therapeutic use KW - Cardiovascular Diseases/diagnosis/*drug therapy KW - *Drug Therapy, Computer-Assisted/adverse effects/standards KW - *Practice Patterns, Physicians'/standards KW - *Primary Health Care/standards KW - *Quality Improvement/standards KW - *Quality Indicators, Health Care/standards KW - cardiovascular disease prevention KW - computer decision support systems KW - health information technology KW - intervention KW - long-term use AU - Panaretto K. AU - Harris M. AU - Zwar N. AU - Usherwood T. AU - Li Q. AU - Patel Bindu AU - Peiris D. AU - Patel A. AB - BACKGROUND: We evaluated a multifaceted, computerized quality improvement intervention for management of cardiovascular disease (CVD) risk in Australian primary health care. After completion of a cluster randomized controlled trial, the intervention was made available to both trial arms. Our objective was to assess intervention outcomes in the post-trial period and any heterogeneity based on original intervention allocation. METHODS AND RESULTS: Data from 41 health services were analyzed. Outcomes were (1) proportion of eligible population with guideline-recommended CVD risk factor measurements; and (2) the proportion at high CVD risk with current prescriptions for guideline-recommended medications. Patient-level analyses were conducted using generalized estimating equations to account for clustering and time effects and tests for heterogeneity were conducted to assess impact of original treatment allocation. Median follow-up for 22 809 patients (mean age, 64.2 years; 42.5% men, 26.5% high CVD risk) was 17.9 months post-trial and 35 months since trial inception. At the end of the post-trial period there was no change in CVD risk factor screening overall when compared with the end of the trial period (64.7% versus 63.5%, P=0.17). For patients at high CVD risk, there were significant improvements in recommended prescriptions at end of the post-trial period when compared with the end of the trial period (65.2% versus 56.0%, P<0.001). There was no heterogeneity of treatment effects on the outcomes based on original randomization allocation. CONCLUSIONS: CVD risk screening improvements were not observed in the post-trial period. Conversely, improvements in prescribing continued, suggesting that changes in provider and patient actions may take time when initiating medications. CLINICAL TRIAL REGISTRATION: URL: http://www.anzctr.org.au. Unique identifier: 12611000478910. AD - The George Institute for Global Health, University of Sydney, Camperdown, Australia bpatel@georgeinstitute.org.au.
The George Institute for Global Health, University of Sydney, Camperdown, Australia.
University of New South Wales, Sydney, Australia.
University of Queensland, Teneriffe, Australia.
University of Wollongong, Australia. AN - 29066447 BT - J Am Heart AssocJ Am Heart AssocJ Am Heart Assoc C2 - PMC5721891 DP - NLM ET - 2017/10/27 J2 - Journal of the American Heart Association LA - eng M1 - 10 N1 - 2047-9980
Patel, Bindu
Peiris, David
Usherwood, Tim
Li, Qiang
Harris, Mark
Panaretto, Kathryn
Zwar, Nicholas
Patel, Anushka
Journal Article
Multicenter Study
Observational Study
England
J Am Heart Assoc. 2017 Oct 24;6(10). pii: JAHA.117.007093. doi: 10.1161/JAHA.117.007093. N2 - BACKGROUND: We evaluated a multifaceted, computerized quality improvement intervention for management of cardiovascular disease (CVD) risk in Australian primary health care. After completion of a cluster randomized controlled trial, the intervention was made available to both trial arms. Our objective was to assess intervention outcomes in the post-trial period and any heterogeneity based on original intervention allocation. METHODS AND RESULTS: Data from 41 health services were analyzed. Outcomes were (1) proportion of eligible population with guideline-recommended CVD risk factor measurements; and (2) the proportion at high CVD risk with current prescriptions for guideline-recommended medications. Patient-level analyses were conducted using generalized estimating equations to account for clustering and time effects and tests for heterogeneity were conducted to assess impact of original treatment allocation. Median follow-up for 22 809 patients (mean age, 64.2 years; 42.5% men, 26.5% high CVD risk) was 17.9 months post-trial and 35 months since trial inception. At the end of the post-trial period there was no change in CVD risk factor screening overall when compared with the end of the trial period (64.7% versus 63.5%, P=0.17). For patients at high CVD risk, there were significant improvements in recommended prescriptions at end of the post-trial period when compared with the end of the trial period (65.2% versus 56.0%, P<0.001). There was no heterogeneity of treatment effects on the outcomes based on original randomization allocation. CONCLUSIONS: CVD risk screening improvements were not observed in the post-trial period. Conversely, improvements in prescribing continued, suggesting that changes in provider and patient actions may take time when initiating medications. CLINICAL TRIAL REGISTRATION: URL: http://www.anzctr.org.au. Unique identifier: 12611000478910. PY - 2017 SN - 2047-9980 ST - Journal of the American Heart AssociationJournal of the American Heart Association T2 - J Am Heart AssocJ Am Heart AssocJ Am Heart Assoc TI - Impact of Sustained Use of a Multifaceted Computerized Quality Improvement Intervention for Cardiovascular Disease Management in Australian Primary Health Care VL - 6 ER -