Canadian Post-licensure Education for Primary Care Nurses Addressing the Patient’s Medical Home Model and Canadian Competencies for Registered Nurses in Primary Care: An Environmental Scan
Notice bibliographique
Résumé
Purpose: Nurses constitute the largest non-medical primary care workforce in Canada and play an integral role in promoting health equity and improving access, continuity of care, patient satisfaction, and clinical outcomes. In 2019, the Canadian Family Practice Nurses Association (CFPNA) published Canadian competencies unique to registered nurses (RNs) in primary care. However, primary care–focused content has not been well integrated into Canadian nursing curriculum, and additional education is required to enable nurses to enact these competencies in practice. To address this gap, the purpose of this paper was to identify post-licensure education programs available to nurses in primary care across Canada and explore their alignment with the CFPNA Competencies for RNs in Primary Care and the College of Family Physicians of Canada Patient’s Medical Home (PMH) model. Method: An environmental scan was conducted, consisting of a literature review and expert consultations. The literature review involved a search of electronic databases (CINAHL Plus, MEDLINE via EBSCOhost) using relevant keywords/search strings and grey literature collected from websites of academic institutions, government/professional organizations, and nursing regulatory bodies. Studies considered for inclusion reported on programs available to RNs and nurse practitioners involving high-level primary care education, with properties related to the CFPNA competencies and/or PMH model. Data were extracted and grouped according to the type of program, content, targeted skills/knowledge, CFPNA competency domains and/or PMH model pillars, and delivery methods. Expert consultations involved data verification by key informants and an electronic questionnaire. Key informants, who had expertise in primary care, nursing, and/or continuing education, were contacted via email and asked to verify data retrieved from the literature review. An electronic questionnaire (via Qualtrics) was sent to primary care nurses/administrators to gather additional data on education programs and identify factors that support or hinder nurse involvement. Responses were categorized narratively based on overarching themes. Results: Ten unique programs were identified across 12 sources. All identified programs offered high-level primary care content that was generally tailored to specific practice areas (e.g., chronic disease management). Programs addressed some of the CFPNA competency domains (i.e., clinical practice; leadership) and the PMH model pillars (i.e., patient- and family-centred care; training, education, and continuing professional development; measurement, continuous improvement, and research). Courses contained theory and/or clinical components and most were limited to provincial-level delivery. A total of 63 respondents completed the electronic questionnaire across multiple provinces and reported that education programs differed within provinces and that there was no required education to practise in primary care beyond entry-to-practice preparation. Key factors that supported or hindered their ability to participate in education were identified, and consensus was expressed that a national, standardized program tailored to the nursing role in primary care is needed. Conclusion: These findings highlight notable gaps in primary care nursing education and emphasize the need for an education program that aligns with established primary care frameworks to guide clinical practice, nurses’ scope of practice, and their unique contributions to primary care. A standardized education program has the potential to improve quality of patient care, increase nurse satisfaction, and enhance overall collaborative practice within team-based care.
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 | 0,025 | 0,085 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,003 |
| Bibliométrie | 0,030 | 0,050 |
| Études des sciences et des technologies | 0,005 | 0,002 |
| Communication savante | 0,006 | 0,003 |
| Science ouverte | 0,003 | 0,003 |
| Intégrité de la recherche | 0,002 | 0,002 |
| 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 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 ».