Initial uptake of the Ontario Pharmacy Smoking Cessation Program
Bibliographic record
Abstract
BACKGROUND: Smoking is a significant public health concern. The Ontario Pharmacy Smoking Cessation Program was launched in September 2011 to leverage community pharmacists and expand access to smoking cessation services for public drug plan beneficiaries. METHODS: We examined health care utilization data in Ontario to describe public drug plan beneficiaries receiving, and pharmacies providing, smoking cessation services between September 2011 and September 2013. Patient characteristics were summarized, stratified by drug plan group: seniors (age ≥65 years) or social assistance. Trends over time were examined by plotting the number of services, unique patients and unique pharmacies by month. We then examined use of follow-up services and prescription smoking cessation medications. RESULTS: We identified 7767 residents receiving pharmacy smoking cessation services: 28% seniors (mean age = 69.9, SD = 4.8; 53% male) and 72% social assistance (mean age = 44.4 years, SD = 11.8; 48% male). Cumulative patient enrollment increased over time with an average of 311 (SD = 61) new patients per month, and one-third (n = 1253) of pharmacies participated by the end of September 2013. Regions with the highest number of patients were Erie St. Clair (n = 1328) and Hamilton Niagara Haldimand Brant (n = 1312). Sixteen percent of all patients received another pharmacy service (e.g., MedsCheck) on the same day as smoking cessation program enrollment. Among patients with follow-up data, 56% received follow-up smoking cessation services (60% seniors, 55% social assistance) and 74% received a prescription smoking cessation medication. One-year quit status was reported for 12%, with a 29% success rate. CONCLUSIONS: Program enrollment has increased steadily since its launch, yet only a third of pharmacies participated and 56% of patients received follow-up services.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".