A descriptive study of access to services in a random sample of Canadian rural emergency departments
Bibliographic record
Abstract
OBJECTIVE: To examine 24/7 access to services and consultants in a sample of Canadian rural emergency departments (EDs). DESIGN: Cross-sectional study-mixed methods (structured interview, survey and government data bases) with random sampling of hospitals. SETTING: Canadian rural EDs (rural small town (RST) definition-Statistics Canada). PARTICIPANTS: 28% (95/336) of Canadian rural EDs providing 24/7 physician coverage located in hospitals with acute care hospitalisation beds. MAIN OUTCOME MEASURES: General characteristics of the rural EDs, information about 24/7 access to consultants, equipment and services, and the proportion of rural hospitals more than 300 km from levels 1 and 2 trauma centres. RESULTS: Of the 336 rural EDs identified, 122 (36%) were randomly selected and contacted. Overall, 95 EDs participated in the study (participation rate, 78%). Hospitals had, on an average, 23 acute care beds, 7 ED stretchers and 13 500 annual ED visits. The proportion of rural hospitals with local access to the following 24/7 services was paediatrician, 5%; obstetrician, 10%; psychiatrist, 11%; internist, 12%; intensive care unit, 17%; CT scanner, 20%; surgeon, 26%; ultrasound, 28%; basic X-ray, 97% and laboratory services, 99%. Forty-four per cent and 54% of the RST EDs were more than 300 km from a level 1 and level 2 trauma centre, respectively. CONCLUSIONS: This is the first study describing the services available in Canadian rural EDs. Apart from basic laboratory and X-ray services, most rural EDs have limited access to consultants, advanced imaging and critical care services. A detailed study is needed to evaluate the impact of these limited services on patient outcomes, costs and interfacility transport demands.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".