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Record W2922415494 · doi:10.1161/circ.139.suppl_1.mp70

Abstract MP70: Impact of Systematic Approaches to Tobacco Treatment: The Ottawa Model for Smoking Cessation

2019· article· en· W2922415494 on OpenAlexaffabout
Mustafa Coja, Kerri‐Anne Mullen, Robert D. Reid, Andrew Pipe

Bibliographic record

VenueCirculation · 2019
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Health and Risk Factors
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsMedicineSmoking cessationPsychological interventionOutreachIntervention (counseling)Family medicineKnowledge translationNursing

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.074
metaresearch head score (Gemma)0.198
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.469
Threshold uncertainty score0.932

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0740.198
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0030.009
Bibliometrics0.0040.006
Science and technology studies0.0030.003
Scholarly communication0.0060.003
Open science0.0040.005
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0150.001

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.

Opus teacher head0.130
GPT teacher head0.318
Teacher spread0.189 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

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Citations0
Published2019
Admission routes2
Has abstractyes

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