Moving enhanced recovery after surgery from implementation to sustainability across a health system: a qualitative assessment of leadership perspectives
Notice bibliographique
Résumé
Abstract Background Knowledge Translation evidence from health care practitioners and administrators implementing Enhanced Recovery After Surgery (ERAS) care has allowed for the spread and scale of the health care innovation. There is a need to identify at a health system level, what it takes from a leadership perspective to move from implementation to sustainability over time. The purpose of this research was to systematically synthesize feedback from health care leaders to inform further spread, scale and sustainability of ERAS care across a health system. Methods Alberta Health Services (AHS) is the largest Canadian health system with approximately 280,000 surgeries annually at more than 50 surgical sites. In 2013 to 2014, AHS used a structured approach to successfully implement ERAS colorectal guidelines at six sites. Between 2016 and 2018, three of the six sites expanded ERAS to other surgical areas (gynecologic oncology, hepatectomy, pancreatectomy/Whipple’s, and cystectomy). This research was designed to explore and learn from the experiences of health care leaders involved in the AHS ERAS implementation expansion (eg. surgical care unit, hospital site or provincial program) and build on the model for knowledge mobilization develop during implementation. Following informed consent, leaders were interviewed using a structured interview guide. Data were recorded, coded and analyzed qualitatively through a combination of theory-driven immersion and crystallization, and template coding using NVivo 12. Results Forty-four individuals (13 physician leaders, 19 leading clinicians and hospital administrators, and 11 provincial leaders) were interviewed. Themes were identified related to Supportive Environments including resources, data, leadership; Champion and Nurse coordinator role; and Capacity Building through change management, education, and teams. The perception and role of leaders changed through initiation and implementation, spread, and sustainability. Barriers and enablers were thematically aligned relative to outcome assessment, consistency of implementation, ERAS care compliance, and the implementation of multiple guidelines. Conclusions Health care leaders have unique perspectives and approaches to support spread, scale and sustainability of ERAS that are different from site based ERAS teams. These findings inform us what leaders need to do or need to do differently to support implementation and to foster spread, scale and sustainability of ERAS.
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 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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 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 ».