Impact on mortality of increasing surgical volumes within hospitals after regionalization of thoracic surgery in Ontario, Canada.
Bibliographic record
Abstract
225 Background: The causal direction of the volume-outcome relationship in surgery has not yet been established. Our objective was to study the effect of absolute hospital volume of anatomic lung resections and volume changes within hospitals on mortality, length of stay (LOS), readmission (RA), and post-discharge visits to the emergency room (ER visits), during a period of regionalization for lung surgery in Ontario, Canada, to test the theory of "practice makes perfect". Methods: For each anatomic lung resection in Ontario from 2004-2010 we determined the volume change within hospital as the difference in hospital operative volume between the year immediately prior to the date of surgery and year prior to that (Dvolume). We used generalized estimating equations and logistic regression, controlling for clustering within hospitals, to examine the effect of Dvolume, patient factors and year on operative mortality, RA and ER visits. Negative binomial regression was used for LOS. The absolute effect of volume, measured as the 12-month hospital volume prior to each procedure, on outcomes was also examined with the same models. Results: Higher hospital volumes were associated with significant improvements in mortality and length of stay, (for increases of 10 cases, mortality OR=0.98 [95%CI: 0.96-1.00] and LOS RR=0.98 [95% CI: 0.97-0.99]), but not for RA or ER visits. However, increases in within-hospital volume did not lead to changes in mortality (OR=1.00, 95% CI: 0.96-1.10), RA (OR=1.00, 95% CI: 0.99-1.00), or ER visits (OR=0.99, 95% CI: 0.98-1.00). Volume increases within hospitals did lead to small improvements in LOS (RR=0.996, 95% CI: 0.993-0.999). Conclusions: Increasing volumes within hospitals did not lead to improvements in mortality in our study, but did result in small improvements in LOS. The decrease in LOS was likely appropriate as it was not associated with changes in RA or ER visits. A volume-outcome relationship between absolute hospital volume and improved mortality was observed, but was not explained by increasing volumes within hospitals; thus practice did not make perfect for mortality.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 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".