A comparison of the policy and institutional environment relevant to community-based primary health care in Ontario, Quebec and New Zealand
Notice bibliographique
Résumé
Introduction: Community-based primary health care (CBPHC) describes a model of service provision that is oriented to the population health needs and wants of service users and communities, and has particular relevance to supporting the growing proportion of the population with multiple chronic conditions. Internationally, aspirations for CBPHC have stimulated local initiatives and influenced the design of policy solutions. However, the ways in which these ideas and influences find their way into policy and practice is strongly mediated by policy settings and institutional path dependencies. This paper compares key features of the policy and institutional environments relevant to community-based primary health care in Ontario, Quebec and New Zealand.Theory/Methods: Drawing on existing literature and our collective expertise, we sought to identify the key organisational landscapes, service models, integrating mechanisms, and relevant policy developments within each jurisdiction. From these descriptions we develop a comparative analysis of enablers and facilitators.Results: Our analysis suggests that Ontario has the most significant institutional barriers to organisational integration and the fewest available policy levers, whilst New Zealand has the most conducive organisational landscape and strongest policy levers. Quebec has significant capacity for reform the structure of the health system, but reforms to date these have not incorporated primary health care.Conclusions: (comprising key findings) Our analysis suggests that two key conditions include the integration of relevant health and social sector organisations, and the range of policy levers available and used by governments. On both dimensions, the New Zealand environment appears to offer the largest scope, with Ontario’s environment significantly less conducive, with Quebec situated in between. Nevertheless, in each case there remain important institutional barriers to implementation of policies that promote CBPHC.Lessons Learned: Although New Zealand has more powerful policy levers, the effectiveness of levers is largely dependent on implementation strategies. Here the differences between New Zealand, Quebec and Ontario are less marked.Limitations: This research constitutes a preliminary, high-level understanding of the complex policy environments of three comparable policy and institutional environments. However, the degree to which the factors identified are key facilitators and inhibitors of CBPHC requires empirical investigation such that other significant policy and institutional constraints and enablers can be identified.Suggestions for Future Research: This research serves to inform the broader iCoach research collaboration, which investigates a range of specific local CBPHC initiatives and embedded practices that focus on older adults with complex conditions. Moving forward our research will focus on the analysis of key stakeholder interviews conducted within Ontario, Quebec and New Zealand to identify key institutional and policy settings that may enable and constrain the implementation and diffusion of these initiatives.
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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 | 0,002 | 0,007 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 0,004 |
| Études des sciences et des technologies | 0,006 | 0,005 |
| Communication savante | 0,005 | 0,001 |
| Science ouverte | 0,001 | 0,003 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 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 ».