Evidence to action: a tailored multifaceted approach to changing family physician practice patterns and improving preventive care.
Bibliographic record
Abstract
BACKGROUND: Although there is much room for improvement in the performance of recommended preventive manoeuvres, many inappropriate preventive interventions are being done. We evaluated a multifaceted intervention, delivered by nurses trained in prevention facilitation, to improve prevention in primary care. METHODS: Forty-six health service organizations (HSOs) were recruited from 100 sites in Ontario. After baseline data were collected, we randomly assigned the practices to either an 18-month (July 1997 to December 1998) multifaceted intervention delivered by 1 of 3 nurse facilitators (23 practices) or no intervention (23 practices). The unit of intervention and analysis was the medical practice. The outcome measure was an overall index of preventive performance, which was calculated as the proportion of eligible patients who received 8 recommended preventive manoeuvres less the proportion of eligible patients who received 5 inappropriate preventive manoeuvres. RESULTS: One HSO, in the intervention group, was lost to follow-up. Before the intervention, the index of preventive performance was similar for the intervention and control groups (31.9% [95% confidence interval (CI) 27.3%-36.5%] and 32.1% [95% CI 27.2%-37.0%] respectively). At follow-up the corresponding values were 43.2% (95% CI 38.4%-48.0%) and 31.9% (95% CI 26.8%-37.0%), for an absolute improvement in the intervention group of 11.5% (p < 0.001). The mean proportion of eligible patients who received the recommended manoeuvres was 62.3% (95% CI 58.2%-66.4%) in the intervention group, as compared with 57.4% (95% CI 54.1%-60.7%) in the control group, for an absolute improvement of 7.2% (p = 0.008). The corresponding values for the inappropriate manoeuvres were 19.1% (95% CI 15.6%-22.6%) and 25.5% (95% CI 20.0%-31.0%), for an absolute improvement of 4.4% (p = 0.019). INTERPRETATION: The tailored multifaceted intervention delivered by nurse facilitators was effective in modifying physician practice patterns and significantly improved preventive care performance.
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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 | 0.086 | 0.158 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.008 | 0.003 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.006 | 0.009 |
| Research integrity | 0.012 | 0.009 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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".