A scoping review of the integration of non-medical prescribing for acute common clinical conditions by community pharmacists
Notice bibliographique
Résumé
Abstract Introduction Non-medical prescribing enhances patient care, safety, and medication accessibility, while also maximising expertise1. Some evidence exists for a variety of factors at individual, organisational, regulatory, and policy levels impacting the implementation of PP in community pharmacy2. Common clinical conditions (CCC) can be defined as ‘a broad range of self-limiting conditions that are more complex in their diagnosis and treatment than minor ailments and management that often involves the need for prescription medicines’. Aim To collate and characterise literature on the integration of non-medical prescribing for acute common clinical conditions by community pharmacists. Method This scoping review followed the Arksey and O’Malley framework. The review team comprised a doctoral student (LK), a research fellow (TJ) and a professor of pharmacy (SC), all with experience of review methodology, community pharmacy research and /or practice. Eligibility criteria, search databases and terms were defined. Medline, International Pharmaceutical Abstracts, Cumulative Index to Nursing and Allied Health Literature and Google Scholar were searched for full text, English language, peer reviewed original papers, randomised controlled trials, cross-sectional and cohort studies, papers reporting empirical data from primary research and review articles including systematic reviews /scoping reviews /narrative reviews from January 2006 to October 2023. The (global) focus was on services delivered by pharmacists and pharmacy team members in community pharmacy for the management of CCC, using non-medical prescribing rights. Search terms included “independent prescrib*”, “pharm* independent prescri*”, “pharm* prescrib*”, “non-medical prescri*, “non-medical prescri*”, “pharm* supplementary prescri*” and “collaborative prescrib*”. Following screening and full text review a narrative synthesis approach3 was used to address the aim which involved: preliminary synthesis through data extraction and tabulation of key study characteristics, exploration of relationships and differences across the studies and finally evaluation of the robustness of the synthesis. The Consolidated Framework for Implementation Research provided a theoretical lens to support synthesis, identifying barriers and facilitators for integration. All steps were independently checked by two review team members. Ethics approval was not required because this was a scoping review. Results From a total 1018 records identified, 10 papers remained after removal of duplicates, title /abstract screening and full text review. The majority of studies were from Canada and the aims and linked outcomes of studies focused on pharmacists’ views and experiences, evaluation of safety, effectiveness, and patient satisfaction. A range of CCCs were included with a focus on antibiotic prescribing. A wide range of barriers and facilitators to implementation were identified including “regulatory constraints” and “fiscal challenges” at a macro socio-organisational level and a plethora of dichotomous challenges within organisations including a lack of clarity on the pharmacist’s scope of practice and linked consumer confusion, staffing levels and workload, with specific mention of paperwork and access to patient records. Conclusion The small number of studies included indicates that there is a paucity of research in this area. There is a need for increased efforts to consider this topic further and identify ways to address the challenges for further widespread implementation and uptake of such services. References 1. Department of Health UK A. Improving patients’ access to medicines: A guide to implementing nurse and pharmacist independent prescribing within the NHS in England. [homepage on the internet]. UK Government; 2006 Available from: http://webarchive.nationalarchives.gov.uk/+/www.dh.gov.uk/en/PublicationsandStatistics/Publications/PublicationsPolicyandGuidance/DH_4133743. 2. Isenor JE, Minard LV and Stewart SA,. Identification of the relationship between barriers and facilitators of pharmacist prescribing and self-reported prescribing activity using the theoretical domains framework. Res Social Adm Pharm. 2018; 14 3. Ryan R; Cochrane Consumers and Communication Review Group. ‘Cochrane Consumers and Communication Review Group: data synthesis and analysis’. http://cccrg.cochrane.org, June 2013.
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 | 0,006 | 0,012 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,002 | 0,002 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,004 |
| 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 ».