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Enregistrement W3009122258 · doi:10.3310/hsdr08120

Factors influencing utilisation of ‘free-standing’ and ‘alongside’ midwifery units for low-risk births in England: a mixed-methods study

2020· article· en· W3009122258 sur OpenAlexaboutno aff
Denis Walsh, Helen Spiby, Christine McCourt, Dawn Coleby, Celia P. Grigg, Simon Bishop, Miranda Scanlon, Lorraine Culley, Jane Wilkinson, Lynne Pacanowski, Jim Thornton

Notice bibliographique

RevueHealth Services and Delivery Research · 2020
Typearticle
Langueen
DomaineMedicine
ThématiqueMaternal and Perinatal Health Interventions
Établissements canadiensnon disponible
Organismes subventionnairesUniversity of OxfordHealth Services and Delivery Research ProgrammeNational Institute for Health and Care Research
Mots-clésPsychological interventionQuarter (Canadian coin)ExcellenceStakeholderAuditClosure (psychology)MedicineNursingFamily medicineGeographyBusinessPublic relationsPolitical scienceAccounting

Résumé

récupéré en direct d'OpenAlex

Background Midwifery-led units (MUs) are recommended for ‘low-risk’ births by the National Institute for Health and Care Excellence but according to the National Audit Office were not available in one-quarter of trusts in England in 2013 and, when available, were used by only a minority of the low-risk women for whom they should be suitable. This study explores why. Objectives To map the provision of MUs in England and explore barriers to and facilitators of their development and use; and to ascertain stakeholder views of interventions to address these barriers and facilitators. Design Mixed methods – first, MU access and utilisation across England was mapped; second, local media coverage of the closure of free-standing midwifery units (FMUs) were analysed; third, case studies were undertaken in six sites to explore the barriers and facilitators that have an impact on the development of MUs; and, fourth, by convening a stakeholder workshop, interventions to address the barriers and facilitators were discussed. Setting English NHS maternity services. Participants All trusts with maternity services. Interventions Establishing MUs. Main outcome measures Numbers and types of MUs and utilisation of MUs. Results Births in MUs across England have nearly tripled since 2011, to 15% of all births. However, this increase has occurred almost exclusively in alongside units, numbers of which have doubled. Births in FMUs have stayed the same and these units are more susceptible to closure. One-quarter of trusts in England have no MUs; in those that do, nearly all MUs are underutilised. The study findings indicate that most trust managers, senior midwifery managers and obstetricians do not regard their MU provision as being as important as their obstetric-led unit provision and therefore it does not get embedded as an equal and parallel component in the trust’s overall maternity package of care. The analysis illuminates how provision and utilisation are influenced by a complex range of factors, including the medicalisation of childbirth, financial constraints and institutional norms protecting the status quo. Limitations When undertaking the case studies, we were unable to achieve representativeness across social class in the women’s focus groups and struggled to recruit finance directors for individual interviews. This may affect the transferability of our findings. Conclusions Although there has been an increase in the numbers and utilisation of MUs since 2011, significant obstacles remain to MUs reaching their full potential, especially FMUs. This includes the capacity and willingness of providers to address women’s information needs. If these remain unaddressed at commissioner and provider level, childbearing women’s access to MUs will continue to be restricted. Future work Work is needed on optimum approaches to improve decision-makers’ understanding and use of clinical and economic evidence in service design. Increasing women’s access to information about MUs requires further studies of professionals’ understanding and communication of evidence. The role of FMUs in the context of rural populations needs further evaluation to take into account user and community impact. Funding This project was funded by the National Institute for Health Research (NIHR) Health Services and Delivery Research programme and will be published in full inHealth Services and Delivery Research; Vol. 8, No. 12. See the NIHR Journals Library website for further project information.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,006
score de la tête « metaresearch » (Gemma)0,014
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Qualitatif · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,040
Score d'incertitude au seuil0,080

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0060,014
Méta-épidémiologie (sens strict)0,0000,001
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0010,001
Études des sciences et des technologies0,0010,001
Communication savante0,0020,002
Science ouverte0,0010,002
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0030,000

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 Opus0,189
Tête enseignante GPT0,471
Écart entre enseignants0,282 · 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 source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeQualitatif
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

Citations7
Publié2020
Routes d'admission1
Résumé présentoui

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