Regional variation in the use of surgery in Ontario
Bibliographic record
Abstract
BACKGROUND: Regional variation in the use of surgery implies that there is uncertainty regarding appropriate use. The objectives of this study were to identify which surgical procedures are most commonly performed in the province of Ontario and measure the extent of variation in the use of surgical procedures across Ontario counties. METHODS: We used the Canadian Institute for Health Information Discharge Abstract Database, Same Day Surgery Database and National Ambulatory Care Reporting System to retrieve information on all inpatient and day surgery visits in Ontario between Apr. 1, 2002, and Mar. 31, 2011. We identified the 84 most common procedures according to Canadian Classification of Interventions codes. We calculated rates of use for each procedure throughout the 49 Ontario counties and then calculated measures of variation (quartile ratio and systematic component of variation) in use between the counties. RESULTS: Colonoscopy was the most commonly performed procedure during the study period, with an average adjusted rate of 2012 per 100 000 population. The procedure with the highest measure of variation was iridectomy, with a quartile ratio of 6.7, followed by colposcopy (5.2), cervical biopsy (4.2) and femoral arteriography (4.1). These procedures were less commonly performed. Common procedures such as colonoscopy, cataract extraction and vaginal delivery had lower quartile ratios. Analysis using the systematic component of variation as the measure of variation gave similar results. INTERPRETATION: Colonoscopy was the most commonly performed procedure in Ontario, and cataract extraction was the most common surgical procedure. Procedures with the highest measures of variation between counties tended to be those that occurred less commonly in Ontario, and common procedures were associated with less regional variation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| 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) | 0.000 | 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".