Differences in Access to Services in Rural Emergency Departments of Quebec and Ontario
Bibliographic record
Abstract
INTRODUCTION: Rural emergency departments (EDs) are important safety nets for the 20% of Canadians who live there. A serious problem in access to health care services in these regions has emerged. However, there are considerable geographic disparities in access to trauma center in Canada. The main objective of this project was to compare access to local 24/7 support services in rural EDs in Quebec and Ontario as well as distances to Levels 1 and 2 trauma centers. MATERIALS AND METHODS: Rural EDs were identified through the Canadian Healthcare Association's Guide to Canadian Healthcare Facilities. We selected hospitals with 24/7 ED physician coverage and hospitalization beds that were located in rural communities. There were 26 rural EDs in Quebec and 62 in Ontario meeting these criteria. Data were collected from ministries of health, local health authorities, and ED statistics. Fisher's exact test, the t-test or Wilcoxon-Mann-Whitney test, were performed to compare rural EDs of Quebec and Ontario. RESULTS: All selected EDs of Quebec and Ontario agreed to participate in the study. The number of EDs visits was higher in Quebec than in Ontario (19 322 ± 6 275 vs 13 446 ± 8 056, p = 0.0013). There were no significant differences between Quebec and Ontario's local population and small town population density. Quebec's EDs have better access to advance imaging services such as CT scanner (77% vs 15%, p < .0001) and most the consultant support and ICU (92% vs 31%, p < .0001). Finally, more than 40% of rural EDs in Quebec and Ontario are more than 300 km away from Levels 1 and 2 trauma centers. CONCLUSIONS: Considering that Canada has a Universal health care system, the discrepancies between Quebec and Ontario in access to support services are intriguing. A nationwide study is justified to address this issue.
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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 | 0.000 | 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".