Cost Impact Analysis of Enhanced Recovery after Surgery Program Implementation in Alberta Colon Cancer Patients
Bibliographic record
Abstract
BACKGROUND: The Enhanced Recovery After Surgery (eras) colorectal guideline has been implemented widely across Alberta. Our study examined the clinical and cost impacts of eras on colon cancer patients across the province. METHODS: We first used both summary statistics and multivariate regression methods to compare, before and after guideline implementation, clinical outcomes (length of stay, complications, readmissions) in consecutive elective colorectal patients 18 or more years of age and in colon cancer and non-cancer patients treated at the Peter Lougheed Centre and the Grey Nuns Hospital between February 2013 and December 2014. We then used the differences in clinical outcomes for colon cancer patients, together with the average cost per hospital day, to estimate cost impacts. RESULTS: The analysis considered 790 patients (398 cancer and 392 non-cancer patients). Mean guideline compliance increased to 60% in cancer patients and 57% in non-cancer patients after eras implementation from 37% overall before eras implementation. From pre- to post-eras, mean length of stay declined to 8.4 ± 5 days from 9.5 ± 7 days in cancer patients, and to 6.4 ± 4 days from 8.8 ± 5.5 days in non-cancer patients (p = 0.0012 and p = 0.0041 respectively). Complications declined significantly in the renal, hepatic, pancreatic, and gastrointestinal groups (difference in proportions: 13% in cancer patients; p < 0.05). No significant change in the risk of readmission was observed. The net cost savings attributable to eras implementation ranged from $1,096 to $2,771 per cancer patient and from $3,388 to $7,103 per non-cancer patient. CONCLUSIONS: Implementation of eras not only resulted in clinical outcome improvements, but also had a significant beneficial impact on scarce health system resources. The effect for cancer patients was different from that for non-cancer patients, representing an opportunity for further refinement and study.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".