Association of an Enhanced Recovery Pilot With Length of Stay in the National Surgical Quality Improvement Program
Notice bibliographique
Résumé
Importance: Enhanced recovery protocols (ERPs) are standardized care plans of best practices that can decrease morbidity and length of stay (LOS). However, many hospitals need help with implementation. The Enhanced Recovery in National Surgical Quality Improvement Program (ERIN) pilot was designed to support ERP implementation. Objective: To evaluate the association of the ERIN pilot with LOS after colectomy. Design, Setting, and Participants: Using a difference-in-differences design, pilot LOS before and after ERP implementation was compared with matched controls in a hierarchical model, adjusting for case mix and random effects of hospitals and matched pairs. The setting was 15 hospitals of varied size and academic status from the National Surgical Quality Improvement Program. Preimplementation and postimplementation colectomy cases (July 1, 2013, to December 31, 2015) were collected using novel ERIN variables. Emergency and septic cases were excluded. A propensity score match identified a 2:1 control cohort of patients undergoing colectomy at non-ERIN hospitals. Interventions: Pilot hospitals developed and implemented ERPs that included expert guidance, multidisciplinary teams, data audits, and opportunities for collaboration. Main Outcomes and Measures: The primary outcome was LOS, and the secondary outcome was serious morbidity or mortality composite. Results: There were 4975 colectomies performed by 15 ERIN pilot hospitals (3437 before implementation and 1538 after implementation) compared with a control cohort of 9950 colectomies (4726 before implementation and 5224 after implementation). The mean LOS decreased by 1.7 days in the pilot (6.9 [interquartile range (IQR), 4-8] days before implementation vs 5.2 [IQR, 3-6] days after implementation, P < .001) compared with 0.4 day in controls (6.4 [IQR, 4-7] days before implementation vs 6.0 [IQR, 3-7] days after implementation, P < .001). Readmission did not differ pre-post for the pilot or controls. Serious morbidity or mortality decreased for pilot participants (485 [14.1%] before implementation vs 162 [10.5%] after implementation, P < .001), with no difference in controls, and remained significant after risk adjustment (adjusted odds ratio, 0.76; 95% CI, 0.60-0.96). After adjusting for differences in case mix and for clustering in hospitals and matched pairs, the adjusted difference-in-differences model demonstrated a decrease in LOS by 1.1 days in the pilot over controls (P < .001). Conclusions and Relevance: Participating ERIN pilot hospitals achieved shorter LOS and decreased complications after elective colectomy, without increasing readmissions. The ability to implement ERPs across hospitals of varied size and resources is essential. Lessons from the ERIN pilot may inform efforts to scale this effective and evidence-based intervention.
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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 | 0,005 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| 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 ».