The impact of teaching on the duration of common urological operations
Bibliographic record
Abstract
INTRODUCTION: The ability of academic (teaching) hospitals to offer the same level of efficiency as non-teaching hospitals in a publicly funded healthcare system is unknown. Our objective was to compare the operative duration of general urology procedures between teaching and non-teaching hospitals. METHODS: We used administrative data from the province of Ontario to conduct a retrospective cohort study of all adults who underwent a specified elective urology procedure (2002-2013). Primary outcome was duration of surgical procedure. Primary exposure was hospital type (academic or non-teaching). Negative binomial regression was used to adjust relative time estimates for age, comorbidity, obesity, anesthetic, and surgeon and hospital case volume. RESULTS: 114 225 procedures were included (circumcision n=12 280; hydrocelectomy n=7221; open radical prostatectomy n=22 951; transurethral prostatectomy n=56 066; or mid-urethral sling n=15 707). These procedures were performed in an academic hospital in 14.8%, 13.3%, 28.6%, 17.1%, and 21.3% of cases, respectively. The mean operative duration across all procedures was higher in academic centres; the additional operative time ranged from 8.3 minutes (circumcision) to 29.2 minutes (radical prostatectomy). In adjusted analysis, patients treated in academic hospitals were still found to have procedures that were significantly longer (by 10-21%). These results were similar in sensitivity analyses that accounted for the potential effect of more complex patients being referred to tertiary academic centres. CONCLUSIONS: Five common general urology operations take significantly longer to perform in academic hospitals. The reason for this may be due to the combined effect of teaching students and residents or due to inherent systematic inefficiencies within large academic hospitals.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 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".