A Blended Educational Program to Promote Dialogue on Patient Safety Between Patient and Family Advisory Councils and Health Care Organizations: Codevelopment Study
Notice bibliographique
Résumé
Background: Reducing patient harm and improving patient safety is a central objective in global health care. Effective communication and meaningful patient engagement are considered essential strategies to achieve this goal. However, implementation of structured and strategic patient engagement at the organizational level remains limited, particularly in the context of patient safety. Patient and family advisory councils (PFACs) offer a promising model to enhance organizational-level patient engagement, yet guidance on implementation and targeted training for PFAC members is scarce. Objective: This study aimed to codevelop an evidence-informed, blended educational program designed to strengthen PFAC members' competencies in patient safety and communication, and to foster strategic collaboration between PFACs and health care organizations. Methods: The intervention was systematically developed using a logic model framework that structures the development process from available and required resources to the ultimate objectives and impacts. The primary target group included PFAC members, such as patients, relatives, and advocates, as well as health care representatives in leadership, quality management, or coordination roles. The program's content and structure were informed by a nationwide needs and requirements analysis among PFAC members, conducted using a mixed methods Delphi approach, and by a rapid scoping review on existing educational resources and evidence on PFAC engagement in patient safety. Results: Our Partners for Patient Safety blended educational program consisted of 2 modular components: a self-paced e-learning module and a subsequent on-site workshop module. Content addressed three core topics: (1) fundamentals of patient safety, (2) engagement of PFACs, and (3) communication and collaborative goal setting. The e-learning module provided theoretical knowledge using diverse didactic formats, such as interactive tasks, videos, and downloadable materials, and included applied examples using established decision-making and goal-setting frameworks. The workshop module built on the e-learning module and facilitated local implementation through collaborative exercises focused on stakeholder perspectives, communication barriers, and joint goal development. Both modules were aligned with defined learning objectives and combined passive and active learning strategies to promote engagement and practical application. Conclusions: The Partners for Patient Safety program seeks to develop PFAC members' competencies, promote collaboration in patient safety, and foster a culture of safety and partnership within health care organizations. By combining theoretical knowledge with practical, collaborative learning, the program addresses key barriers to effective PFAC engagement at the organizational level. Its modular design allows flexible implementation and has the potential to strengthen cooperation between PFACs and health care representatives, ultimately improving patient safety outcomes. Further evaluation of the program's implementation and effectiveness is needed.
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 | 0,007 | 0,010 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,002 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,002 | 0,004 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,001 |
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 ».