SP11 Family integrated care: a way forward for medicines optimisation on the special care baby unit
Notice bibliographique
Résumé
Introduction Family Integrated Care (FIC) is a new model of care within the neonatal unit that aims to empower parents to take a more active role in caring for their newborn child. FIC has been shown to have many positive effects including reducing length of admission.1 FIC involves building a relationship with parents and training them to deliver many aspects of care to their newborn baby whilst on the neonatal unit. As neonatal units implement FIC, this presents both a challenge and opportunity to pharmacy. Many aspects of FIC complement medicines optimisation, as described by the Royal Pharmaceutical Society,2 such as understanding the patient and parent experience. The aim of this project was to plan, design and implement a clinical pharmacy service on the local neonatal units by combining FIC and medicines optimisation. Methods Guidelines regarding medicines optimisation were reviewed along with existing local policies. Parents and members of the multi-professional team (MDT) involved in FIC where then interviewed. Open-ended questions were used to establish what their needs were and what pharmacy could do to support them. This information was then used to finalise the methods for delivering medicines optimisation. Results The interviews provided useful feedback for how medicines optimisation should be delivered. Parents were very receptive to learning more about their child’s medicines and being trained to administer them. They felt it would give them a better understanding of why a medicine was being used and also prepare them for discharge. In addition, they also wanted to be provided with written information and a structured training plan to reduce anxiety and build confidence. Nursing staff wanted documentation to ensure that there would be accountability for who was responsible for administering medicines. They also highlighted that there needed to be a process to communicate prescription changes to parents. Managers asked that processes complied with medicines governance policies. Pharmacists worked closely alongside the FIC project team to agree on the processes for medicines optimisation. This included drop-in group teaching sessions on medicines every fortnight for parents, regular medication reviews by pharmacists with parents at the cotside, using the hospital self-administration policy to assess parent competency to administer medicines, using one stop dispensing to supply medicines, and producing an information leaflet for parents. Conclusion FIC has provided an excellent opportunity to plan and develop a neonatal clinical pharmacy service for the future. Specifically, to tailor it so that parents and patients are at the centre. Involving parents in this process provided valuable information and resulted in changes to the delivery of care. Empowering parents to become more involved with medicines, supported by pharmacy, has the potential to benefit everyone. References O’Brien K, Bracht M, Macdonell K, et al. A pilot cohort analytic study of family integrated care in a Canadian neonatal intensive care unit. BMC Pregnancy and Childbirth2013;13(Suppl. 1):S12. Royal Pharmaceutical Society. Medicines optimisation: Helping patients to make the most of medicines2013. London: Royal Pharmaceutical Society.
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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 | 0,006 | 0,011 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,002 | 0,003 |
| Science ouverte | 0,003 | 0,007 |
| Intégrité de la recherche | 0,003 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,031 | 0,003 |
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 ».