The Impact of an Acute Care Surgical Service on the Quality and Efficiency of Care Outcome Indicators for Patients with General Surgical Emergencies
Bibliographic record
Abstract
Background Acute care surgery (ACS) models address high volumes of emergency general surgery and emergency room (ER) overcrowding. The impact of ACS service model implementation on the quality and efficiency of care (EOC) outcomes in acute appendicitis (AA) and acute cholecystitis (AC) cohorts was evaluated. Methods A retrospective chart review (N=1,229) of adult AA and AC patients admitted prior to (pre-ACS; n=507; three hospitals; 2007) and after regionalization (R-ACS; n=722; one hospital; 2011). Results R-ACS time to ER physician assessment was significantly longer for AA (3.4 ± 2.3 versus 2.4 ± 2.6 hr; p ≤ 0.001). Surgical response times (1.3 ± 1.2 vs 2.6 ± 4.3 hr for AA; 1.8 ± 1.5 vs 4.1 ± 5.0 hr for AC; p ≤ 0.0001) and acquisition of imaging (4.1 ± 4.1 vs 6.9 ± 9.9 hr for AA, p ≤ 0.0001; 7.8 ± 1.9 vs 13.2 ± 18.5 hr for AC, p ≤ 0.008) occurred significantly faster with R-ACS. R-ACS resulted in a significant increase in night-time appendectomies (21.7% vs 11.1%; p ≤ 0.002), perforated appendices (29.1 % vs 18.9 %; p ≤ 0.006), 30-day readmissions (4.56% vs 0.82%; p ≤ 0.01), and lower rate of intraoperative complications for AC patients (2.78% vs 7.69%; p ≤ 0.02). Conclusions Despite the increased volume of patients seen with the implementation of R-ACS, surgical assessments and diagnostic imaging were significantly more prompt. EOC measures were maintained. Worse AA outcomes highlight areas for improvement in delivering R-ACS.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".