Practice Variation between Salaried and Fee-for-Service Surgeons for Lumbar Surgery
Bibliographic record
Abstract
OBJECTIVE: To examine differences in surgical practices between salaried and fee-for-service (FFS) surgeons for two common degenerative spine conditions. Surgeons may offer different treatments for similar conditions on the basis of their compensation mechanism. METHODS: The study assessed the practices of 63 spine surgeons across eight Canadian provinces (39 FFS surgeons and 24 salaried) who performed surgery for two lumbar conditions: stable spinal stenosis and degenerative spondylolisthesis. The study included a multicenter, ambispective review of consecutive spine surgery patients enrolled in the Canadian Spine Outcomes and Research Network registry between October 2012 and July 2018. The primary outcome was the difference in type of procedures performed between the two groups. Secondary study variables included surgical characteristics, baseline patient factors, and patient-reported outcome. RESULTS: < 0.05). There were no statistical differences in patient-reported outcomes between the two groups. CONCLUSIONS: Surgeon compensation was associated with different approaches to stable lumbar spinal stenosis and degenerative lumbar spondylolisthesis. Salaried surgeons chose a more conservative approach to spinal stenosis and a more aggressive approach to degenerative spondylolisthesis, which highlights that remuneration is likely a minor determinant in the differences in practice of spinal surgery in Canada. Further research is needed to further elucidate which variables, other than patient demographics and financial incentives, influence surgical decision-making.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 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".