Impact of an acute care surgery service on timeliness of care and surgeon satisfaction at a Canadian academic hospital: a retrospective study
Bibliographic record
Abstract
INTRODUCTION: In January 2012 an acute care surgery (ACS) model was introduced at St. Paul's Hospital, Saskatoon, Saskatchewan. The goal of implementing an ACS service was to improve the delivery of care for emergent, non-trauma surgical patients. We examined whether the ACS model improved wait time to surgery, decreased the proportion of surgeries performed after hours, and shortened post-surgical length of stay. We also assessed whether the surgeons working in an ACS system had higher on-call satisfaction than surgeons working in a non- ACS system. METHODS: A retrospective pre-post analysis was performed using data from the Discharge Abstract Database and the Organizing Medical Networked Information database. Surgeon satisfaction was evaluated using a questionnaire that was mailed to all general surgeons in Saskatoon. RESULTS: An ACS service significantly reduced wait time to surgery for patients with all acute general surgery diagnoses from 221 minutes to 192 minutes (ρ = 0.015; CI = 5.8-52.2). Post-surgery length of stay for patients operated on for acute appendicitis, or acute cholecystitis was not reduced. On average, patients with bowel obstruction had increased length of stay following ACS service implementation. Most surgeries in our study were performed between 16:00 hours and 08:00 hours but the introduction of an ACS significantly reduced the number of afterhours surgeries (60.0% vs. 72.6%) (ρ < 0.0001). Our survey had a response rate of 75%. Overall, surgeons on an ACS service had greater satisfaction with the organization of their call schedule than surgeons not on an ACS service. CONCLUSION: Introduction of an ACS service in Saskatoon has decreased wait time to surgery and reduced the proportion of afterhours emergency surgeries, with no reduction in the length of post-surgery hospital stay. Satisfaction may be higher for surgeons in an ACS service.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 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".