Regional variations and associations between colonoscopy resource availability and colonoscopy utilisation: a population-based descriptive study in Ontario, Canada
Bibliographic record
Abstract
OBJECTIVE: There is substantial variation in colonoscopy use and evidence of long wait times for the procedure. Understanding the role of system-level resources in colonoscopy utilisation may point to a potential intervention target to improve colonoscopy use. This study characterises colonoscopy resource availability in Ontario, Canada and evaluates its relationship with colonoscopy utilisation. DESIGN: We conducted a population-based study using administrative health data to describe regional variation in colonoscopy availability for Ontario residents (age 18-99) in 2013. We identified 43 colonoscopy networks in the province in which we described variations across three colonoscopy availability measures: colonoscopist density, private clinic access and distance to colonoscopy. We evaluated associations between colonoscopy resource availability and colonoscopy utilisation rates using Pearson correlation and log binomial regression, adjusting for age and sex. RESULTS: There were 9.4 full-time equivalent colonoscopists per 100 000 Ontario residents (range across 43 networks 0.0 to 21.8); 29.5% of colonoscopies performed in the province were done in private clinics (range 1.2%-55.9%). The median distance to colonoscopy was 3.7 km, with 5.9% travelling at least 50 km. Lower colonoscopist density was correlated with lower colonoscopy utilisation rates (r=0.53, p<0.001). Colonoscopy utilisation rates were 4% lower in individuals travelling 50 to <200 km and 11% lower in individuals travelling ≥200 km to colonoscopy, compared to <10 km. There was no association between private clinic access and colonoscopy utilisation. CONCLUSION: The substantial variations in colonoscopy resource availability and the relationship demonstrated between colonoscopy resource availability and use provides impetus for health service planners and decision-makers to address these potential inequalities in access in order to support the use of this medically necessary procedure.
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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".