Primary Care Physician Engagement in Integrated Health System Transformation: A Case Study 
Notice bibliographique
Résumé
Background: Primary care physician (PCP) engagement is essential in enhancing health system performance, efficacy and collaboration, however; limited research exists in terms of how PCPs are engaged in health system reform. Aims & Methods: Ontario is undergoing a healthcare transformation with the introduction of Ontario Health Teams (OHTs). OHTs provide a new way of organizing and delivering care that is more connected to patients in their local communities. In response to the need for a coordinated sector approach, a group of PCPs in Southwestern Ontario formed a primary care organization: London-Middlesex Primary Care Alliance (LMPCA). This grassroots organization aims to support unified PCP engagement within the health system reform. The aim of our study is to explore the development of the grassroots LMPCA organization and understand how physicians are engaged within the regional health system. The first phase of our study consisted of a literature review which identified that PCP engagement is critical to the success of OHTs. Using an integrated knowledge translation approach (i.e.: in collaboration with members of the LMPCA and Middlesex-London OHT), the second phase of our study involves a case study to explore the development of a regional primary care organization and physician engagement. We will use key informant interviews with physicians, nurse practitioners (NPs) and health care administrators to explore the LMPCA development and understand PCP engagement. The objectives of the overall study are to 1) plot key junctures in the development of the regional organization, 2) explore PCP engagement at local and regional levels and 3) discuss the barriers and facilitators to PCP engagement. Results: Despite PCP engagement being recognized as an important aspect of health systems integration, several barriers exist: ineffective communication within organizations, administrative and legal hurdles, remuneration and reimbursement and other local contextual factors. Results from our literature review indicate that greater levels of PCP engagement can lead to improved primary care performance and efficacy. Engagement in primary care settings has been facilitated both top-down and bottom-up; however, empirical evidence on bottom-up approaches is limited. Three over-arching themes were evident: lack of physician voice, insufficient renumeration, and unsuitable strategies. We anticipate that results of our interviews can provide recommendations to increase physician voice, compensate appropriately, suggest alternative strategies for PCP engagement and gain physician buy-in. Moreover, we expect our results to help shape the LMPCA and the Middlesex-London OHT with their physician engagement efforts within the region. Implications: Findings of our study will benefit researchers, PCPs, NPs, and health care administrators by highlighting barriers and recommendations to support and improve physician engagement efforts. The findings may encourage the international audience to use similar PCP engagement strategies within their organization. Next Steps: We will provide a rich narrative of the development of a grassroots primary care organization as well as an empirical example of PCP engagement in health system reform. We anticipate our results will describe effective strategies for engaging physicians and by extension, provide recommendations to improve organizational efficacy and patient care.
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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 | 0,006 | 0,010 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,003 |
| Études des sciences et des technologies | 0,015 | 0,005 |
| Communication savante | 0,004 | 0,002 |
| Science ouverte | 0,002 | 0,006 |
| Intégrité de la recherche | 0,003 | 0,004 |
| 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 ».