03647nas a2200553   4500000000100000008004100001653001100042653001100053653000900064653000900073653002200082653001600104653001700120653001700137653001400154653004200168653002400210653003300234653002800267653002400295653003200319653002400351653002300375653005900398653005200457653006300509653004600572653003500618653003500653653004700688653003800735653003800773653003400811653001700845653001800862100001700880700001400897700001200911700001700923700001000940700001600950700001400966700001300980245016400993250001501157490000601172520190101178020001403079       2017                            d10aFemale10aHumans10aAged10aMale10aTreatment Outcome10aMiddle Aged10aRisk Factors10aTime Factors10aAustralia10aRandomized Controlled Trials as Topic10aGuideline Adherence10aPractice Guidelines as Topic10aRisk Reduction Behavior10aQuality Improvement10aDecision Support Techniques10aPrimary Health Care10aDrug Prescriptions10aCardiovascular Agents/adverse effects/*therapeutic use10aCardiovascular Diseases/diagnosis/*drug therapy10a*Drug Therapy, Computer-Assisted/adverse effects/standards10a*Practice Patterns, Physicians'/standards10a*Primary Health Care/standards10a*Quality Improvement/standards10a*Quality Indicators, Health Care/standards10acardiovascular disease prevention10acomputer decision support systems10ahealth information technology10aintervention10along-term use1 aPanaretto K.1 aHarris M.1 aZwar N.1 aUsherwood T.1 aLi Q.1 aPatel Bindu1 aPeiris D.1 aPatel A.00aImpact of Sustained Use of a Multifaceted Computerized Quality Improvement Intervention for Cardiovascular Disease Management in Australian Primary Health Care  a2017/10/270 v63 aBACKGROUND: 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.  a2047-9980