Implementation of Enhanced Recovery After Surgery (ERAS) Across a Provincial Healthcare System: The ERAS Alberta Colorectal Surgery Experience
Bibliographic record
Abstract
BACKGROUND: Enhanced recovery after surgery (ERAS) colorectal guideline implementation has occurred primarily in standalone institutions worldwide. We implemented the guideline in a single provincial healthcare system, and our study examined the effect of the guideline on patient outcomes [length of stay (LOS), complications, and 30-day post-discharge readmissions] across a healthcare system. METHODS: We compared pre- and post-guideline implementation in consecutive elective colorectal patients, ≥ 18 years, from six Alberta hospitals between February 2013 and December 2014. Participants were followed up to 30 days post discharge. We used summary statistics, to assess the LOS and complications, and multivariate regression methods to assess readmissions and to estimate cost impacts. RESULTS: A total of 1333 patients (350 pre- and 983 post-ERAS) were analysed. Of this number, 55 % were males. Median overall guideline compliance was 39 % in pre- and 60 % in post-ERAS patients. Median LOS was 6 days for pre-ERAS compared to 4.5 days in post-ERAS patients with the longest implementation (p value <0.0001). Adjusted risk ratio (RR) was 1.71, 95 % CI 1.09-2.68 for 30-day readmission, comparing pre- to post-ERAS patients. The proportion of patients who developed at least one complication was significantly reduced, from pre- to post-ERAS, difference in proportions = 11.7 %, 95 % CI 2.5-21.0, p value: 0.0139. The net cost savings attributable to guideline implementation ranged between $2806 and $5898 USD per patient. CONCLUSION: The findings in our study have shown that ERAS colorectal guideline implementation within a healthcare system resulted in patient outcome improvements, similar to those obtained in smaller standalone implementations. There was a significant beneficial impact of ERAS on scarce health system resources.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".