Evaluation of the Implementation of Multiple Enhanced Recovery After Surgery Pathways Across a Provincial Health Care System in Alberta, Canada
Notice bibliographique
Résumé
Importance: Engaging multidisciplinary care teams in surgical practice is important for the improvement of surgical outcomes. Objective: To evaluate the association of multiple Enhanced Recovery After Surgery (ERAS) pathways with ERAS guideline adherence and outcomes. Design, Setting, and Participants: This quality improvement study compared a pre-ERAS cohort (2013-2017) with a post-ERAS cohort (2014-2018). All patients were from Alberta Health Services in Alberta, Canada, and had available ERAS and up to 1-year postsurgery administrative data. Data collected included age, sex, body mass index, tobacco and alcohol use, diabetes, comorbidity index, and surgical characteristics. Data analysis was performed from May 7, 2020, to February 1, 2021. Interventions: Implementation of 5 ERAS pathways (colorectal, liver, pancreas, gynecologic oncology, and radical cystectomy) across 9 sites. Main Outcomes and Measures: Adherence to ERAS guidelines was measured by the percentage of patients whose care met the common ERAS pathway care element criteria. Surgical procedures were grouped by complexity; complications were classified by severity. Outcome measures for the pre-post-ERAS cohorts included length of stay (LOS), readmission, complications, and mortality. Results: A total of 7757 patients participated in the study, including 984 in the pre-ERAS cohort (median [interquartile range] age, 62 [53-71] years; 526 [53.5%] female) and 6773 in the post-ERAS cohort (median [interquartile range] age, 62 [53-71] years; 3470 [51.2%] male). In the total cohort, care-element adherence improved from 52% to 76% (P < .001), no significant differences were found in serious complications (from 6.2% to 4.9%; P = .08) or 30-day mortality (from 0.71% to 0.93%; P = .50), 1-year mortality decreased from 7.1% to 4.6% (P < .001), mean (SD) LOS decreased from 9.4 (7.0) to 7.8 (5.0) days (P < .001), and 30-day readmission rates were unchanged (from 13.4% to 11.7%; P = .12). After adjustment for patient characteristics, the LOS mean difference decreased 0.71 days (95% CI, -1.13 to -0.29 days; P < .001), with no significant differences in adjusted 30-day readmission (-3.5%; 95% CI, -22.7% to 20.4%; P = .75), serious complications (1.3%; 95% CI, -26.2% to 39.0%; P = .94), or mortality (30-day mortality: 42% [95% CI, -35.4% to 212.3%]; P = .38; 1-year mortality: 8% [95% CI, -20.5% to 46.8%]; P = .62). The adjusted 1-year readmission rate was -15.6% (95% CI, -27.7% to -1.5%; P = .03) in favor of ERAS, and readmission LOS was shorter by 1.7 days (95% CI, -3.3 to -0.1 days; P = .04). Conclusions and Relevance: The results of this quality improvement study suggest that implementation of ERAS across multiple pathways may improve health care practitioner adherence to ERAS guidelines, LOS, and readmission rates at a system level.
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 | 0,006 | 0,012 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,002 | 0,005 |
| Études des sciences et des technologies | 0,004 | 0,002 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,003 | 0,003 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».