46 enhance: supporting integrated care systems in meeting their local healthcare priorities and workforce development needs
Notice bibliographique
Résumé
Introduction Integrated care systems (ICSs) were established in 2022 to meet the needs of local populations ICSs have responsibility for workforce development of health and care staff in the locality NHS England’s enhance programme is an educational development offer, applicable to all health and care staff (including non-clinical), with emphasis on system working, health inequalities, environmental sustainability and population health, aligning to ICS priorities Learners are encouraged to develop their leadership skills through service improvement projects and collaborative learning activities. Aims and objectives of the research project or activity enhance aims to address the educational requirements that can support sustainable workforce planning and delivery of integrated person-centred care through initiatives which prioritise staff wellbeing and self-directed professional development. Its flexible place-based offer aims to allow ICSs to address their local health priorities whilst encompassing the values of enhance and developing and retaining their workforce. Method or approach enhance was piloted by seven regional trailblazers, with two (NEY and SW) closely aligned to local ICSs. Tailored offers were developed for multi-professional teams covering different geographical footprints. Mixed methods delivery included expert presentations, access to online learning resources, Action Learning sets, community and cross-sector ‘field trips’, and quality improvement projects. Building on this success, ICSs across England were given the opportunity to bid for funding to run their own place-based enhance offer. Two ICS pilot bids in Norfolk & Waveney and Kent & Medway were accepted and will launch in 2024. Further ICS bid submission opportunities will be available in 2024. These will use enhance domains and values to encourage and explore system working, and to engage and equip the workforce to address local priorities. Findings enhance delivered effective and enjoyable multi-professional training to clinical and non-clinical health and care workers, breaking down professional silos. Feedback (qualitative and quantitative) showed improvements in knowledge, skills and attitudes about health and care systems and teams. Participants gained accredited CPD with some progressing to PGCert. Quality improvement projects delivered benefits for patients, teams and the environment, whilst developing leadership skills for learners. The NHS Long Term Workforce Plan (LTWP) has identified expansion of enhance programmes to ICSs as a priority to further develop generalist skills for all health and care professionals. Key messages Enhancing generalist skills within the workforce is critical in managing increased patient complexity in a changing healthcare environment, as highlighted by the NHS LTWP. enhance trailblazer pilots demonstrated that learning across multi-professional teams, based on local population health needs, can enhance the skills of the local workforce and deliver service improvements whilst developing generalist skills. Further expansion through ICS pilots will provide more place-based offers tailored to local health needs which prioritise patient care and professional development of staff.
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 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 | 0,007 | 0,010 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,004 | 0,002 |
| Communication savante | 0,006 | 0,004 |
| Science ouverte | 0,002 | 0,018 |
| Intégrité de la recherche | 0,003 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,032 | 0,005 |
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 ».