90 Impact of the choosing wisely Canada recommendations on potentially inappropriate antibiotic prescribing in emergency medicine across Alberta, Canada: an interrupted time-series analysis
Notice bibliographique
Résumé
Campaigns such as Choosing Wisely Canada have encouraged physicians to consider whether antibiotics are needed when treating presumably viral infections to decrease inappropriate antibiotic prescribing rates; however, the impacts of such campaigns are not well characterized. Objectives In Alberta, Canada, we quantified the rate of potentially inappropriate oral antibiotic prescribing in emergency departments for viral infections or conditions not likely requiring antibiotics from 2010–2020 and assessed the impact of two Choosing Wisely Canada (CWC) campaigns (2015/2016 and 2018) discouraging inappropriate antibiotic prescribing in emergency medicine. Methods In Alberta, we linked all emergency department adult and pediatric records from the National Ambulatory Care Reporting System and medication dispensations from community-based pharmacies in the Pharmaceutical Information Network. From January 2010 to February 2020, we identified emergency department visits for 5 conditions that were potentially inappropriately treated using antibiotics per CWC recommendations (bronchitis, asthma, bronchiolitis, pharyngitis, and acute otitis media). We used an interrupted time series design to detect changes in the proportion of emergency departments visits with subsequent antibiotic dispensing by fitting Autoregressive Integrated Moving Average (ARIMA) models to account for secular trends and seasonality, allowing for changes in slope to measure the effect of each CWC intervention. Results Antibiotics were commonly prescribed in emergency departments for bronchitis (proportion of visits with antibiotics: 57%) and asthma (22%) in adults; bronchiolitis in children (43%); pharyngitis (39%) and acute otitis media (54%) in adults and children. Based on visual inspection, the proportion of emergency department visits for each condition where antibiotics were dispensed remained relatively consistent. The ARIMA models demonstrated mixed impacts on potentially inappropriate antibiotic prescribing associated with two interruptions: the 2015/2016 CWC recommendations and subsequent 2018 CWC Using Antibiotics Wisely campaign. Following each interruption, antibiotic prescribing was slightly reduced for bronchitis (-1.0%/year,p=0.03; -4.4%/year,p=0.004, respectively) and bronchiolitis (not significant) (-0.7%/year,p=0.57; -2.5%/year,p=0.34), but unchanged for asthma (-0.6%/year,p=0.30; 0.7%/year,p=0.74) and pharyngitis (0.0%/year,p=0.95; -0.2%/year,p=0.93), and slightly increased for acute otitis media (not significant) (1.4%/year,p=0.07; 5.9%/year,p=0.052). Conclusion Rates of potentially inappropriate antibiotic prescribing remained constant over the past 10 years in Alberta. Campaigns to rethink antibiotic use in emergency medicine may have resulted in small decreases in antibiotic use for some conditions; however, further initiatives building upon existing campaigns are required to substantially reduce rates of inappropriate antibiotic prescribing.
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 | 0,004 | 0,012 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,004 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,000 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 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 ».