Key characteristics and critical junctures for successful Interprofessional networks in healthcare – a case study
Notice bibliographique
Résumé
BACKGROUND: The use of networks in healthcare has been steadily increasing over the past decade. Healthcare networks reduce fragmented care, support coordination amongst providers and patients, improve health system efficiencies, support better patient care and improve overall satisfaction of both patients and healthcare professionals. There has been little research to date on the implementation, development and use of small localized networks. This paper describes lessons learned from a successful small localized primary care network in Southwestern Ontario that developed and implemented a regional respiratory care program (The ARGI Respiratory Health Program - ARGI is a not-for-profit corporation leading the implementation and evaluation of a respiratory health program. Respiratory therapists (who have a certified respiratory educators designation), care for patients from all seven of the network's FHTs. Patients rostered within the network of FHTs that have been diagnosed with a chronic respiratory disease are referred by their family physicians to the program. The RTs are integrated into the FHTs, and work in a triad along with patients and providers to educate and empower patients in self-management techniques, create exacerbation action plans, and act as a liaison between the patient's care providers. ARGI uses an eTool designed specifically for use by the network to assist care delivery, choosing education topics, and outcome tracking. RTs are hired by ARGI and are contracted to the participating FHTs in the network.). METHODS: This study used an exploratory case study approach. Data from four participant groups was collected using focus groups, observations, interviews and document analysis to develop a rich understanding of the multiple perspectives associated with the network. RESULTS: This network's success can be described by four characteristics (growth mindset and quality improvement focus; clear team roles that are strengths-based; shared leadership, shared success; and transparent communication); and five critical junctures (acknowledge a shared need; create a common vision that is flexible and adaptable depending on the context; facilitate empowerment; receive external validation; and demonstrate the impacts and success of their work). CONCLUSIONS: Networks are used in healthcare to act as integrative, interdisciplinary tools to connect individuals with the aim of improving processes and outcomes. We have identified four general lessons to be learned from a successful small and localized network: importance of clear, flexible, and strengths-based roles; need for shared goals and vision; value of team support and empowerment; and commitment to feedback and evaluations. Insight from this study can be used to support the development and successful implementation of other similar locally developed networks.
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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 | 0,004 | 0,001 |
| 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 | 0,002 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 ».