A real-world stepped wedge cluster randomized trial of practice facilitation to improve cardiovascular care
Bibliographic record
Abstract
BACKGROUND: Practice facilitation has been associated with meaningful improvements in disease prevention and quality of patient care. Using practice facilitation, the Improved Delivery of Cardiovascular Care (IDOCC) project aimed to improve the delivery of evidence-based cardiovascular care in primary care practices across a large health region. Our goal was to evaluate IDOCC's impact on adherence to processes of care delivery. METHODS: A pragmatic stepped wedge cluster randomized trial recruiting primary care providers in practices located in Eastern Ontario, Canada (ClinicalTrials.gov: NCT00574808). Participants were randomly assigned by region to one of three steps. Practice facilitators were intended to visit practices every 3-4 (year 1-intensive) or 6-12 weeks (year 2-sustainability) to support changes in practice behavior. The primary outcome was mean adherence to indicators of evidence-based care measured at the patient level. Adherence was assessed by chart review of a randomly selected cohort of 66 patients per practice in each pre-intervention year, as well as in year 1 and year 2 post-intervention. RESULTS: Eighty-four practices (182 physicians) participated. On average, facilitators had 6.6 (min: 2, max: 11) face-to-face visits with practices in year 1 and 2.5 (min: 0 max: 10) visits in year 2. We collected chart data from 5292 patients. After adjustment for patient and provider characteristics, there was a 1.9 % (95 % confidence interval (CI): -2.9 to -0.9 %) and 4.2 % (95 % CI: -5.7 to -2.6 %) absolute decrease in mean adherence from baseline to intensive and sustainability years, respectively. CONCLUSIONS: IDOCC did not improve adherence to best-practice guidelines. Our results showed a small statistically significant decrease in mean adherence of questionable clinical significance. Potential reasons for this result include implementation challenges, competing priorities in practices, a broad focus on multiple chronic disease indicators, and use of an overall index of adherence. These results contrast with findings from previously reported facilitation trials and highlight the complexities and challenges of translating research findings into clinical practice. TRIAL REGISTRATION: ClinicalTrials.gov NCT00574808.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.011 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".