Physician and Population Determinants of Rates of Middle-Ear Surgery in Ontario
Bibliographic record
Abstract
CONTEXT: Small-area variations in surgical rates raise concerns about access to care, treatment appropriateness, and the quality and cost of care. OBJECTIVE: To measure small-area variations in rates of myringotomy with insertion of tympanostomy tubes (TTs) and to identify determinants of rate variation. DESIGN AND SETTING: Retrospective analyses using hospital discharge data for patients who had undergone a myringotomy with insertion of TT by county in Ontario between April 1, 1996, and March 31, 1999. Information on possible determinants was taken from a survey of otolaryngologists and primary care physicians in 1996 and from the 1996 Canadian census and physician demographic databases for 1996-1999. PARTICIPANTS: A total of 75 358 hospitalizations for TT placement of children and adolescents (aged </=14 years). MAIN OUTCOME MEASURE: Small-area variation in rates of TT. RESULTS: An almost 10-fold difference between the areas with the highest and lowest rates was found (extremal quotient, 9.6; 95% confidence interval [CI], 8.2-11.1; P<.001). Higher rates occurred in counties with higher percentages of high school graduates (parameter estimate, 0.01; 95% CI, 0-0.02; P =.049); and where referring physicians were more likely to be male (parameter estimate, 0.01; 95% CI, 0-0.02; P =.01), North American-trained (parameter estimate, 0.01; 95% CI, 0.01-0.02; P<.001), and have higher propensities to refer for surgery (parameter estimate, 0.40; 95% CI, 0.09-0.72; P =.02). Otolaryngologist opinion was not a significant predictor. CONCLUSION: Substantial area variation in TT rates was observed. The opinion of primary care physicians was the dominant modifiable determinant, suggesting an area of research that may be important in reducing area variation in TT procedures.
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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 | 0.000 |
| 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) | 0.002 | 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".