Effect of an acute care surgical service on the timeliness of care
Bibliographic record
Abstract
BACKGROUND: In the spring of 2008, St. Boniface General Hospital in Winnipeg, Man., created an acute care surgical service (ACSS) designed to improve care for emergent, nontrauma surgical patients. We sought to assess the effect of the ACSS on patient care timeliness. METHODS: We retrospectively examined the time intervals in care for patients admitted with acute appendicitis, acute cholecystitis and small bowel obstruction in 3 study periods: pre-ACSS, newly formed ACSS and established ACSS. RESULTS: There was a 2-fold increase in patient volume after the ACSS was created. Patient characteristics were similar in all 3 groups. Time from triage to surgical consultation was also similar. The ACSS significantly reduced the duration of the surgical consultation (1 h 43 min in period 1 v. 62 min in period 2 and 49 min in period 3, p = 0.029). Time from admission to operation was similar despite a significant increase in patient load after the ACSS was created. Total length of hospital stay was similar except in the subgroup analysis (appendicitis + cholecystitis only), where the length of stay was reduced after creation of the ACSS (2 d 15 h pre- v. 1 d 19 h post-ACSS, p = 0.009). Most operations occurred between 4 pm and midnight. CONCLUSION: With the implementation of an ACSS, the number of surgical patients assessed and treated doubled. Despite the increased volume, consultations were completed significantly faster, there was no significant difference in time to operation, and on subgroup analysis length of hospital stay was significantly faster.
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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 | 0.003 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".