Abstract MP70: Impact of Systematic Approaches to Tobacco Treatment: The Ottawa Model for Smoking Cessation
Bibliographic record
Abstract
Introduction: Tobacco use is the largest preventable cause of death. It is a major risk factor for each of the leading chronic diseases, including cancer, heart disease, stroke, and respiratory illness. Smoking cessation is the single most powerful preventive intervention available. The Ottawa Model for Smoking Cessation (OMSC) is a systematic, comprehensive approach to clinical tobacco dependence treatment. It is designed to assist health professionals to transform clinical practice through knowledge translation, implementation support, and quality evaluation. Hypothesis: We assessed the hypothesis that with the addition of a systematic approach to addressing tobacco use, an increase in provider-level support would be realized. Methods: Using a detailed Workplan, OMSC Outreach Facilitators work with sites to adapt their clinical practices and to implement an evidence-based smoking cessation program. This process is comprised of six phases of step-by-step instructions for planning, implementing, evaluating and sustaining an evidence-based clinical cessation system. Metrics are collected on smoking status, brief yet strategic advice to stop smoking, rates of delivery of evidence-based cessation support, and patient quit rates. Data from Electronic Medical Records and from the OMSC patient database are used to measure program outcomes. Results: Over 440 organizations have implemented the OMSC resulting in thousands of healthcare providers across Canada being trained on the latest clinical approaches to smoking cessation. Collectively, the OMSC network has intervened with more than 400,000 patients, providing them with evidence-based interventions. An analysis of almost 4,000 patients within the OMSC primary care network has shown significant increases of rates of Ask, Advise and Act among providers after implementing the program. For patients referred to the OMSC follow-up program, smoking status was assessed for the primary care and hospital programs, respectively. In 2017-18, 60 day outcomes for primary care patients indicated that 22%-57% (125 of 561; 125 of 218) were smoke-free at this time point. For hospitalized patients who reached the 180 day time point, the range was found to be 18%-48% (1156 of 6473; 1156 of 2399). The lower range represents all patients, assuming those not reached have returned to smoking, while the upper range represents only those patients who were reached by the OMSC follow-up program. Conclusions: With the application of a systematic, evidence-based program, there was an increase in the rates of delivery of smoking cessation best practices by healthcare providers. As a result, more patients made further assisted quit attempts resulting in long-lasting quit rates. The OMSC program has shown to be effective in changing provider behaviour with respect to smoking cessation, and in turn, has helped to increase quit rates among patients who smoke.
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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 | 0.074 | 0.198 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.009 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.015 | 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".