Improving prevention in primary care: evaluating the effectiveness of outreach facilitation
Bibliographic record
Abstract
BACKGROUND: Out reach facilitation is designed to promote uptake of evidence-based guidelines. There is evidence indicating that outreach facilitation can be effective in improving implementation of preventive care in GPs' offices. In this trial, we test a modified version of an outreach facilitation intervention. OBJECTIVE: To evaluate whether a comprehensive preventive intervention program using outreach facilitators improves preventive care delivery. DESIGN: Match-paired, cluster-randomized controlled trial. SETTING: Fee-for-service primary care practices in Eastern Ontario, Canada, at a time of physician shortage. PARTICIPANTS: Volunteer sample of 54 primary care practices. MAIN OUTCOME MEASURES: Mean difference between trial arms in practices' delivery of preventive manoeuvres, measured by preventive performance indices estimated from chart reviews and patient survey data. RESULTS: No difference was detected between the trial's arms for the primary outcome's overall prevention index [2.0%; 95% confidence interval (CI) -3.2 to 7.3; P = 0.44]. A small significant difference between the arms was detected for the secondary outcome's overall prevention index (2.8%; 95% CI 0.7-4.8; P = 0.01). CONCLUSION: In contrast to similar facilitation trials, this outreach facilitation program did not produce improvements in the delivery of preventive care. This lack of effect may be due to differences in the intervention and context, or the practice's limited capacity to change. Our intervention simultaneously facilitated a high number of manoeuvres, blinded facilitators and physicians to the targeted tests and had a relatively short intervention period and large number of practices assigned per facilitator. Changes in the primary care service model in Ontario at the time of the trial could have also washed out the intervention effect.
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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 | 0.027 | 0.044 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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".