Transformation of primary care settings implementing a co-located team-based care model: a scoping review
Notice bibliographique
Résumé
BACKGROUND: In Canada, primary care reforms led to the implementation of various team-based care models to improve access and provide more comprehensive care for patients. Despite these advances, ongoing challenges remain. The aim of this scoping review is to explore current understanding of the functioning of these care models as well as the contexts in which they have emerged and their impact on the population, providers and healthcare costs. METHODS: The Medline and CINAHL databases were consulted. To be included, team-based care models had to be co-located, involve a family physician, specify the other professionals included, and provide information about their organization, their relevance and their impact within a primary care context. Models based on inter-professional intervention programs were excluded. The organization and coordination of services, the emerging contexts and the impact on the population, providers and healthcare costs were analysed. RESULTS: A total of 5952 studies were screened after removing duplicates; 15 articles were selected for final analysis. There was considerable variation in the information available as well as the terms used to describe the models. They are operationalized in various ways, generally consistent with the Patient's Medical Home vision. Except for nurses, the inclusion of other types of professionals is variable and tends to be associated with the specific nature of the services offered. The models primarily focus on individuals with mental health conditions and chronic diseases. They appear to generally satisfy the expectations of the overarching framework of a high-performing team-based primary care model at patient and provider levels. However, economic factors are seldom integrated in their evaluations. CONCLUSIONS: The studies rarely provide an overarching view that permits an understanding of the specific contexts, service organization, their impacts, and the broader context of implementation, making it difficult to establish universal guidelines for the operationalization of effective models. Negotiating the inherent complexity associated with implementing models requires a collaborative approach between various stakeholders, including patients, to tailor the models to the specific needs and characteristics of populations in given areas, and reflection about the professionals to be included in delivering these services.
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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 | 0,020 | 0,076 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,003 | 0,005 |
| Bibliométrie | 0,014 | 0,020 |
| Études des sciences et des technologies | 0,002 | 0,002 |
| Communication savante | 0,008 | 0,005 |
| Science ouverte | 0,003 | 0,003 |
| Intégrité de la recherche | 0,003 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,000 |
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.
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 ».