Influence of physician networks on the implementation of pharmaceutical alternatives to a toxic drug supply in British Columbia
Notice bibliographique
Résumé
BACKGROUND: Characterizing the diffusion of adopted changes in policy and clinical practice can inform enhanced implementation strategies to ensure prompt uptake in public health emergencies and other rapidly evolving disease areas. A novel guidance document was introduced at the onset of the COVID-19 pandemic in British Columbia (BC), Canada, which supported clinicians to prescribe opioids, stimulants, and benzodiazepines. We aimed to determine the extent to which uptake and discontinuation of an initial attempt at a prescribed safer supply (PSS) program were influenced through networks of prescribers. METHODS: We executed a retrospective population-based study using linked health administrative data that captured all clinicians who prescribed to at least one client with a substance use disorder from March 27, 2020, to August 31, 2021. Our main exposure was the prescribing patterns of an individuals' peers, defined as the proportion of a prescribers' professional network (based on shared clients), which had previously prescribed PSS, updated monthly. The primary outcome measured whether a clinician had prescribed their initial PSS prescription during a given calendar month. The secondary outcome was the discontinuation of PSS prescribing, defined as an absence for PSS prescriptions for at least 3 months. We estimated logistic regression models using generalized estimated equations on monthly repeated measurements to determine and characterize the extent to which peer networks influenced the initiation and discontinuation of PSS prescribing, controlling for network, clinician, and caseload characteristics. Innovators were defined as individuals initiating PSS prior to May 2020, and early adopters were individuals initiating PSS after. RESULTS: Among 14,137 prescribers treating clients with substance use disorder, there were 228 innovators of prescribed safer supply and 1062 early adopters through the end of study follow-up, but 653 (50.6%) were no longer prescribing by August 2021. Prescribers with over 20% of peers whom had adopted PSS had a nearly fourfold higher adjusted odds of PSS prescribing themselves (aOR: 3.79, 95% CI: (3.15, 4.56)), compared to those with no connected safer supply prescribers. CONCLUSIONS: The uptake of PSS in BC was highly dependent on the behavior of prescribers' peer networks. Future implementation strategies to support PSS or other policies would benefit from leveraging networks of prescribers.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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 tête enseignante, 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 ».