Building High‐Performing Primary Care Systems: After a Decade of Policy Change, Is Canada “Walking the Talk?”
Notice bibliographique
Résumé
Policy Points Considerable investments have been made to build high-performing primary care systems in Canada. However, little is known about the extent to which change has occurred over the last decade with implementing programs and policies across all 13 provincial and territorial jurisdictions. There is significant variation in the degree of implementation of structural features of high-performing primary care systems across Canada. This study provides evidence on the state of primary care reform in Canada and offers insights into the opportunities based on changes that governments elsewhere have made to advance primary care transformation. CONTEXT: Despite significant investments to transform primary care, Canada lags behind its peers in providing timely access to regular doctors or places of care, timely access to care, developing interprofessional teams, and communication across health care settings. This study examines changes over the last decade (2012 to 2021) in policies across 13 provincial and territorial jurisdictions that address the structural features of high-performing primary care systems. METHODS: A multiple comparative case study approach was used to explore changes in primary care delivery across 13 Canadian jurisdictions. Each case consisted of (1) qualitative interviews with academics, provincial health care leaders, and health care professionals and (2) a literature review of policies and innovations. Data for each case were thematically analyzed within and across cases, using 12 structural features of high-performing primary care systems to describe each case and assess changes over time. FINDINGS: The most significant changes include adopting electronic medical records, investments in quality improvement training and support, and developing interprofessional teams. Progress was more limited in implementing primary care governance mechanisms, system coordination, patient enrollment, and payment models. The rate of change was slowest for patient engagement, leadership development, performance measurement, research capacity, and systematic evaluation of innovation. CONCLUSIONS: Progress toward building high-performing primary care systems in Canada has been slow and variable, with limited change in the organization and delivery of primary care. Canada's experience can inform innovation internationally by demonstrating how preexisting policy legacies constrain the possibilities for widespread primary care reform, with progress less pronounced in the attributes that impact physician autonomy. To accelerate primary care transformation in Canada and abroad, a national strategy and performance measurement framework is needed based on meaningful engagement of patients and other stakeholders. This must be accompanied by targeted funding investments and building strong data infrastructure for performance measurement to support rigorous research.
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 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 | 0,009 | 0,016 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,007 |
| Études des sciences et des technologies | 0,026 | 0,018 |
| Communication savante | 0,015 | 0,005 |
| Science ouverte | 0,004 | 0,005 |
| Intégrité de la recherche | 0,003 | 0,005 |
| 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 ».