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 -