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SP11 Family integrated care: a way forward for medicines optimisation on the special care baby unit

2018· article· en· W2785266640 on OpenAlexaboutno aff
Stephen Morris, A Clifton David, Hollwey Alex, Jackson Jenny

Bibliographic record

VenueArchives of Disease in Childhood · 2018
Typearticle
Languageen
FieldMedicine
TopicNeonatal Health and Biochemistry
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePharmacyUnit (ring theory)Service (business)NursingNeonatal intensive care unitMedical educationPediatricsPsychology

Abstract

fetched live from OpenAlex

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 medicines 2013. London: Royal Pharmaceutical Society.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.787
Threshold uncertainty score0.423

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.013
GPT teacher head0.279
Teacher spread0.266 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Published2018
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