Improving primary care antimicrobial stewardship by implementing a peer audit and feedback intervention in Cape Town community healthcare centres
Notice bibliographique
Résumé
BACKGROUND: The increasing prevalence of antibiotic resistance is a major threat to public health. Primary care, where 80% of antibiotics are consumed, is a pivotal setting to direct antimicrobial stewardship (AMS) efforts. However, the ideal model to improve antibiotic prescribing in primary care in low-resource settings is not known. OBJECTIVE: To implement a multidisciplinary audit and feedback AMS intervention with the aim to improve appropriate antibiotic prescribing at primary care level. METHODS: The intervention was implemented and monitored in 10 primary care centres of the Cape Town metropole between July 2017 and June 2019. The primary and secondary outcome measures were monthly adherence to a bundle of antibiotic quality process measures and monthly antibiotic consumption, respectively. Multidisciplinary audit and feedback meetings were initiated and integrated into facility clinical meetings. Two Excel tools were utilised to automatically calculate facility audit scores and consumption. Once a month, 10 antibiotic prescriptions were randomly selected for a peer review audit by the team. The prescriptions were audited for adherence to a bundle of seven antibiotic process measures using the standard treatment guidelines (STG) and Essential Medicines List (EML) as standard. Concurrently, primary care pharmacists monitored monthly antibiotic consumption by calculating defined daily doses (DDDs) per 100 prescriptions dispensed. Adherence and consumption feedback were regularly provided to the facilities. Learning collaboratives involving representative multidisciplinary teams were held twice-yearly. Pre-, baseline and post-intervention periods were defined as 6 months before, first 6 months and last 6 months of the study, respectively. RESULTS: The mean overall adherence increased from 19% (baseline) to 47% (post intervention) (p<0.001). Of the 2 077 prescriptions analysed, 33.7% had an antibiotic prescribed inappropriately. No diagnosis had been captured in patient notes, and the antibiotic chosen was not according to the STG and EML in 30.1% and 31.7% of cases, respectively. Seasonal variation was observed in prescribing adherence, with significantly lower adherence in winter and spring months (adjusted odds ratio 0.60). A reduction of 12.9 DDDs between the pre- and post-intervention periods (p=0.0084) was documented, which represented a 19.3% decrease in antibiotic consumption. CONCLUSION: The study demonstrated that peer reviewed audit and feedback is an effective AMS intervention to improve antibiotic prescribing in primary care in a low-resource setting. The intervention, utilising existing resources and involving multidisciplinary engagement, may be incorporated into existing quality improvement processes at facility level, to ensure sustainable change.
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 | 0,011 | 0,026 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,003 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,003 | 0,004 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 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 ».