An analysis of benign prostatic hyperplasia surgical treatment reimbursement trends across Canada
Bibliographic record
Abstract
INTRODUCTION: A variety of procedures for the endoscopic surgical treatment of symptomatic benign prostatic hyperplasia (BPH) refractory to medical therapy have existed for decades. The present study examined trends in surgeon compensation for these treatments within Canada. METHODS: The physician fee schedule for BPH surgery across 10 Canadian provinces for the years 2010 and 2023 were obtained. A descriptive study examined first the provincial reimbursement for transurethral resection of prostate (TURP) and laser ablative/enucleation surgery; second, the difference in TURP reimbursement between 2010 and 2023; and third, the annual change in TURP reimbursement juxtaposed with the annual change in the provincial Consumer Price Index (CPI) and annual salary for the working population aged 35-44. RESULTS: Seven of 10 Canadian provinces reimburse laser BPH surgery equally to TURP. The average provincial TURP reimbursement is $545, ranging from $451 in Ontario to $688 in Saskatchewan. Since 2010, TURP reimbursement has varied by province from a 0% net change in Ontario to an increase of 21% in Nova Scotia. Reimbursement for TURP has increased at a slower pace than the local CPI, and for half of the provinces at a slower pace than the annual salary for people aged 35-44. CONCLUSIONS: The compensation model for endoscopic BPH surgery does not have a unified structure in Canada that is consistent across provinces, nor does it keep up with inflation, possibly impacting future recruitment, increasing geographic disparities, and most importantly, limiting the adoption of new BPH therapies.
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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 | 0.005 | 0.014 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".