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Enregistrement W2734580412 · doi:10.5334/ijic.3158

What does one learn from the implementation of a mandated integrated network for older adults across three different settings in Quebec

2017· article· en· W2734580412 sur OpenAlexaffabout
Mylaine Breton, Paul Wankah, Louise Belzile, Maxime Guillette, Dominique Gagnon, Yves Couturier, Jean‐Louis Denis

Notice bibliographique

RevueInternational Journal of Integrated Care · 2017
Typearticle
Langueen
DomaineMedicine
ThématiqueClinical practice guidelines implementation
Établissements canadiensUniversité de Sherbrooke
Organismes subventionnairesnon disponible
Mots-clésHealth careIntegrated careBusinessContext (archaeology)Multidisciplinary approachSocial workLocal communityPublic healthNursingPublic relationsMedicineEconomic growthPolitical scienceGeography

Résumé

récupéré en direct d'OpenAlex

Context: In 2004, Quebec mandated its 94 Health and social services centers to lead in the implementation of local integrated health networks. The Health and social services centers, which were created by the fusion of some public establishments (local community health centers, long term care facilities and acute care hospitals in some cases), provide a broad range of health and social services to their populations. To ensure the provision of a comprehensive continuum of care, theses Health and social services centers create partnerships with community organisations, pharmacies and primary healthcare providers of their territories. Objective: To compare the implementation of 3 mandated local integrated health networks for seniors in 3 geographical settings; highly urban, urban and rural.Methods: This research is part of an international research program ICOACH where 3 case studies were carried out in each jurisdiction: Quebec, Ontario and New Zealand. This presentation is based on data collected from 46 semi-structured interviews of healthcare providers and managers in Quebec, as well as the analysis of official documents.Results: The mandated networks for older adults were based on the local implementation of 9 components; 1) a joint governing board, 2) a centralized access point, 3) case management, 4) a common multidisciplinary evaluation tool, 5) an individualized service plan, 6) a common healthcare information system, 7) a geriatric team, 8) the involvement of the family physician in the community and 9) an administrator for the local network. All the main components of the local network were mandated, and several components were implemented with local variations. For instance, each local integrated network for older people had its joint governing board, but the composition and the dynamism of these boards differed considerably. These local integrated networks for older people used the general access point of their Health and social services centers, and in each of these local networks, a common evaluation tool was used to assess the needs of each patient. Services plan would be based on this assessment but a gap can be observed between addressed problems and proposed solutions that are more the services offered by the health and social services centers than by assessed needs. The type of case management varied across networks. For instance, in the highly urban setting, only social workers of the home care team could be case managers while in the urban setting, case managers included different health professionals such as nurses, occupational therapist and social workers. The healthcare information systems were not well implemented. Across the 3 cases studied, few professional teams and healthcare organizations were connected by an information system. Finally, across the 3 cases studied, the primary healthcare practices were not well integrated with public services of the networks. They mostly worked in parallel with respect to the other services of the network.Conclusion: Ten years after the creation of mandated local integrated networks for older people, several implementation challenges are still observed. The implementation of components of the network show local variations and some key components are poorly developed.

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)0,013
score de la tête « metaresearch » (Gemma)0,026
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: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,110
Score d'incertitude au seuil0,797

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0130,026
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0010,003
Études des sciences et des technologies0,0090,007
Communication savante0,0070,005
Science ouverte0,0040,004
Intégrité de la recherche0,0020,003
Charge utile insuffisante (le modèle a refusé de juger)0,0020,000

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 Opus0,058
Tête enseignante GPT0,448
Écart entre enseignants0,390 · 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
Publié2017
Routes d'admission2
Résumé présentoui

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