Delivering evidence-based smoking cessation treatment in primary care practice: experience of Ontario family health teams.
Bibliographic record
Abstract
OBJECTIVE: To report on the delivery of evidence-based smoking cessation treatments (EBSCTs) within a sample of 40 Ontario family health teams (FHTs). DESIGN: In each FHT, consecutive patients were screened for smoking status and eligible patients completed a questionnaire immediately following their clinic visits (index visits). Multilevel analysis was used to examine FHT-level, provider-level, and patient-level predictors of EBSCT delivery. SETTING: Forty FHTs in Ontario. PARTICIPANTS: Across the 40 participating FHTs, 24,033 patients were screened and 2501 eligible patients contributed data. MAIN OUTCOME MEASURES: Provider performance in the delivery of EBSCTs during the preceding 12 months and during the index visits was assessed. RESULTS: The rate of provider delivery of EBSCT for the previous 12 months was 74.0% for the advise strategy. At the index visit, rates of EBSCT strategy delivery were 56.8% for ask; 46.9% for advise; 38.7% for assist; 11.6% for prescribing pharmacotherapy; and 11.3% for arrange follow-up. Significant intra-FHT and intraprovider variability in the rates of EBSCT delivery was identified. Family health teams with a physician champion (odds ratio [OR] 2.0; 95% CI 1.1 to 3.6; P < .01) and providers who highly ranked the importance of smoking cessation (OR 1.7; 95% CI 1.1 to 2.7; P < .01) were more likely to deliver EBSCTs. Patient readiness to quit (OR 1.6; 95% CI 1.3 to 1.9; P < .001), presence of smoking-related illness (OR 1.6; 95% CI 1.2 to 2.1; P < .01), and presenting for an annual health examination (OR 2.0; 95% CI 1.6 to 2.5; P < .001) were associated with the delivery of EBSCTs. CONCLUSION: Rates of smoking cessation advice were higher than previously reported for Canadian physicians; however, rates of assistance with quitting were lower. Future quality improvement initiatives should specifically target increasing the rates of screening and advising among low-performing FHTs and providers within FHTs, with a particular emphasis on doing so at all clinic appointments; and improving the rate at which assistance with quitting is delivered.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".