Teaching surgery takes time: the impact of surgical education on time in the operating room
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: It is generally accepted that surgical training is associated with increased surgical duration. The purpose of this study was to determine the magnitude of this increase for common surgical procedures by comparing surgery duration in teaching and nonteaching hospitals. METHODS: This retrospective population-based cohort study included all adult residents of Ontario, Canada, who underwent 1 of 14 surgical procedures between 2002 and 2012. We used several linked administrative databases to identify the study cohort in addition to patient-, surgeon- and procedure-related variables. We determined surgery duration using anesthesiology billing records. Negative binomial regression was used to model the association between teaching versus nonteaching hospital status and surgery duration. RESULTS: Of the 713 573 surgical cases included in this study, 20.8% were performed in a teaching hospital. For each procedure, the mean surgery duration was significantly longer for teaching hospitals, with differences ranging from 5 to 62 minutes across individual procedures in unadjusted analyses (all p < 0.001). In regression analysis, procedures performed in teaching hospitals were associated with an overall 22% (95% confidence interval 20%-24%) increase in surgery duration, adjusting for patient-, surgeon- and procedure-related variables as well as the clustering of patients within surgeons and hospitals. CONCLUSION: Our results show that a wide range of surgical procedures require significantly more time to perform in teaching than nonteaching hospitals. Given the magnitude of this difference, the impact of surgical training on health care costs and clinical outcomes should be a priority for future studies.
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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 | 0.003 | 0.001 |
| 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) | 0.001 | 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 it