Abstract MP70: Impact of Systematic Approaches to Tobacco Treatment: The Ottawa Model for Smoking Cessation
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,074 | 0,198 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,001 |
| Méta-épidémiologie (sens large) | 0,003 | 0,009 |
| Bibliométrie | 0,004 | 0,006 |
| Études des sciences et des technologies | 0,003 | 0,003 |
| Communication savante | 0,006 | 0,003 |
| Science ouverte | 0,004 | 0,005 |
| Intégrité de la recherche | 0,004 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,015 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».