Regional Medical Campuses in Canada
Notice bibliographique
Résumé
Background: Regional Medical Campuses (RMCs) are an established part of the Distributed Medical Education (DME) landscape in Canada. Combined model RMCs, offering both preclinical and clinical education have shown promising results in producing physicians who work in rural and regional settings and are currently a key avenue of expansion of medical training in Canada. Existing literature suggests that new RMCs carefully consider the communities and health systems they are a part of, and lessons learned from comparable RMCs as part of their development. Methods: We identified 4 specific domains of interest for comparing RMCs across Canada based on important elements identified in existing literature: Community, Organization, Hospitals, and Physicians. We searched high quality, publicly accessible data sources for information relevant to these domains, aggregated relevant information, and used statistical techniques to understand the range of settings for existing and proposed RMCs in Canada. Results: We found that Canadian RMCs have been deployed into a wide variety of small to medium size urban settings and have a variety of organizational profiles. RMCs were associated with 1 to 3 large hospitals, but the size of these associate hospitals also varied greatly. We found that the environments of proposed RMCs differed somewhat from existing RMCs and included examples of novel organizational constructs, settings with smaller urban population sizes, smaller hospitals, and settings with smaller and decreasing physician workforce. Discussion: The combined model RMC has proven to be a robust construct across Canada, deployed in a wide variety of different settings. Our data shows that the settings and structure of proposed new RMCs are somewhat different than existing RMCs. While the robust nature of the RMC model suggests that deployment into new settings is reasonable, the data also clearly shows areas that may be opportunities and challenges for each of these new, proposed, settings. Conclusion: There is a wealth of publicly accessible data is available about Canadian communities and health systems, which can be compiled into domains of interest for RMCs. Our study establishes a baseline data set for Canadian RMCs that will be useful for those contemplating future implementations. Proposed RMCs may be able to use this data to predict both challenges and opportunities, as well as to identify existing RMCs with similar profiles, where information exchange may be of highest value.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 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 tête enseignante, 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 ».