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Enregistrement W4416057512 · doi:10.1093/ijpp/riaf093.072

(ID: 220) Dispensing practices for oral liquid medicines: a survey of UK community pharmacies

2025· article· en· W4416057512 sur OpenAlexaff
M Tylek, M Punton, M Sadr-Kazemi, Stephen Tomlin, Mandy Wan

Notice bibliographique

RevueInternational Journal of Pharmacy Practice · 2025
Typearticle
Langueen
DomaineMedicine
ThématiquePharmaceutical studies and practices
Établissements canadiensNorthlands College
Organismes subventionnairesnon disponible
Mots-clésPharmacyCommunity pharmacyMedical prescriptionDescriptive statisticsAlternative medicinePharmacy practiceComputer-assisted web interviewing

Résumé

récupéré en direct d'OpenAlex

Abstract Introduction In the UK, community pharmacies dispense over one billion prescription items per year, playing an integral role in the safe and effective use of medicine [1]. Their involvement is thus crucial in shaping medicine-related practice standards to drive system-wide improvements in medication safety. Published studies have shown that oral liquid medicines present particular challenges, including the availability of multiple concentrations of the same medicine, variations in how doses are expressed on dispensing labels (e.g. ml, ml(mg), spoonful), and the need for patients or caregivers to measure doses accurately [2–4]. While these findings have prompted efforts to develop professional standards for dispensing such medicines, there is limited insight of how these medicines are dispensed in community pharmacy settings. Aim To explore current dispensing practices for oral liquid medicines in community pharmacies. Methodology An anonymous, self-administered online survey consisting of 8 questions was conducted over an 8-week period between January and March 2025. The survey was distributed to community pharmacy staff through the Community Pharmacy Patient Safety Group, a network hosted by the Company Chemists’ Association. The group collectively represents both large chains and independent community pharmacies. Data were analysed using R and summarised using descriptive statistics. Ethical approval was not required. Results The 237 respondents were based across 53 integrated care/ health boards. Among all respondents, 76% (179/237) reported that doses of oral liquid medicines were ‘almost always’ or ‘frequently’ expressed in millilitres on prescriptions, while 45% (106/237) indicated that spoonful was also commonly used. Pharmacies stocked a median of five dosing device types (range: 2–7), with availability ranging from 24% to 98%. The 2.5 mL syringe was least available, and the 5 mL syringe most common. When supplying dosing devices, 67% (159/237) of respondents indicated that they ‘often’ or ‘always’ check patients’ or carers’ preferences. Scenario-based questions showed variations in practice. In the 5.7 mL dose scenario, 12 variations in response were reported. In the scenarios where manufacturer-supplied dosing devices lacked the accuracy required for the prescribed dose, a range of responses were also noted in how these devices were managed and in the provision of suitable alternatives. In response to the question on excipient content in oral liquid medicines, 45% (107/237) of respondents indicated a need for more educational resources or guidance. Discussion In community pharmacies, prescription dosing is more commonly expressed in volume, while hospitals typically use dose-based units like milligrams [5]. The study found variation in dosing device availability and use, highlighting potential need to standardise professional practices. Any future standardisation in practice would also need to align with patient understanding of dosage instructions to avoid subsequent administration errors [3]. While some differences may reflect efforts to offer patients choices, the potential of unintended impact of practice variation warrants further exploration. Although the study relied on self-reported data, and interpretation of scenarios may have varied among respondents, the findings highlight an opportunity to improve patient safety through the development of system-wide standards informed by an integrated perspective of hospital and community pharmacy practices.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,007
score de la tête « metaresearch » (Gemma)0,040
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMétarecherche
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,815
Score d'incertitude au seuil0,968

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0070,040
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,001
Science ouverte0,0010,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,252
Tête enseignante GPT0,555
Écart entre enseignants0,303 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeSans objet
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2025
Routes d'admission1
Résumé présentoui

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