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Enregistrement W4390956968 · doi:10.5334/ijic.icic23012

Creating a system wide third sector - health system partnership

2023· article· en· W4390956968 sur OpenAlexaffabout
Richard Lewanczuk

Notice bibliographique

RevueInternational Journal of Integrated Care · 2023
Typearticle
Langueen
DomaineHealth Professions
ThématiquePrimary Care and Health Outcomes
Établissements canadiensAlberta Health Services
Organismes subventionnairesnon disponible
Mots-clésGeneral partnershipHealth careGovernment (linguistics)Public relationsBusinessPopulationIntegrated careEconomic growthMedicinePolitical scienceEconomicsEnvironmental health

Résumé

récupéré en direct d'OpenAlex

Introduction: The volunteer (third) sector provides double the care in the community than does the healthcare system. However, within the geographic jurisdictions that a health system operates, there may be thousands of third sector organizations. In order to best meet individual and population medical and social needs, care provided by the third sector needs to be integrated with health system care. This can be challenging given the complexity of a health care system and the number of third sector organizations. The process by which the province of Alberta, Canada approached this integration challenge is described below. Target audience: This topic is pertinent to those working at a systems level in healthcare, government and the third sector. Who was engaged: In developing this approach government, health system planners, and a variety of third sector representatives, typically “umbrella” organizations representing a number of individual groups, were involved. What was done: With a single healthcare system divided into five administrative zones, we used the approach of doing centrally, zonally and locally that which made sense to do at those levels. Third sector actors functioning at those levels were engaged with their health system counterparts. Joint committees, accountable only to the members, were typically established to set a common vision and to coordinate activities in support of that joint vision. Wherever possible, an asset-based community development approach was used to identify what services existed at the various levels, service deficits, the wants and needs of individuals and communities, and the way in which the community could be supported to address those needs and wishes. From an infrastructure perspective, the health system, government and third sector leadership established mechanisms to facilitate cooperation. Results: Creating formal linkages between the health system and third sector, at all levels, was extremely helpful for the healthcare system to understand community needs and factors impacting health. The third sector found the relationship helpful to focus their efforts on programs or interventions which most effectively impacted health and wellness. Individuals and communities benefitted from an integrated approach to health and wellness. Learnings: Giving up control, on the part of the health system, was initially uncomfortable. However, the effectiveness of joint committees accountable to the members, rather than to a hierarchy, was found to be an extremely effective way of working together. At a more local level, allowing communities to determine priorities and approaches similarly resulted in much more effective and productive relationships in meeting the needs of the community, the healthcare system and its providers. Components of the quadruple/quintuple aim were much more effectively addressed than by using a medical model of community engagement. Next steps: From a health system perspective, we plan to use this approach at a community level. However, we find that our workforce will need to be adapted to include those who have skills in developing and maintaining relationships, are comfortable working in complex systems and with uncertainty, and an ability to adapt in keeping with a learning health system.

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)0,040
score de la tête « metaresearch » (Gemma)0,018
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,040
Score d'incertitude au seuil0,214

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0400,018
Méta-épidémiologie (sens strict)0,0000,001
Méta-épidémiologie (sens large)0,0000,001
Bibliométrie0,0010,002
Études des sciences et des technologies0,0140,009
Communication savante0,0190,013
Science ouverte0,0020,042
Intégrité de la recherche0,0040,007
Charge utile insuffisante (le modèle a refusé de juger)0,0190,004

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 Opus0,067
Tête enseignante GPT0,425
Écart entre enseignants0,359 · 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'étudeObservationnel
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
Publié2023
Routes d'admission2
Résumé présentoui

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