Geographic inequalities in paediatric emergency department visits in Ontario and Alberta: a multilevel analysis of 2.5 million visits
Bibliographic record
Abstract
BACKGROUND: Research on intra- and inter-regional variations in emergency department (ED) visits among children can provide a better understanding of the patterns of ED utilization and further insight into how contextual features of the urban environment may be associated with these health events. Our objectives were to assess intra-urban and inter-urban variation in paediatric emergency department (PED) visits in census metropolitan areas (CMAs) in Ontario and Alberta, Canada and explore if contextual factors related to material and social deprivation, proximity to healthcare facilities, and supply of family physicians explain this variation. METHODS: A retrospective, population-based analysis of data on PED visits recorded between April 1, 2015 and March 31, 2017 was conducted. Random intercept multilevel regression models were constructed to quantify the intra- (between forward sortation areas [FSAs]) and inter- (between CMAs) variations in the rates of PED visits. RESULTS: In total, 2,537,442 PED visits were included in the study. The overall crude FSA-level rate of PED visits was 415.4 per 1,000 children population. Across CMAs, the crude rate of PED visits was highest in Thunder Bay, Ontario (771.6) and lowest in Windsor, Ontario (237.2). There was evidence of substantial intra- and inter-urban variation in the rates of PED visits. More socially deprived FSAs, FSAs with decreased proximity to healthcare facilities, and CMAs with a higher rate of family physicians per 1,000 children population had higher rates of PED visits. CONCLUSIONS: The variation in rates of PED visits across CMAs and FSAs cannot be fully accounted for by age and sex distributions, material and social deprivation, proximity to healthcare facilities, or supply of family physicians. There is a need to explore additional contextual factors to better understand why some metropolitan areas have higher rates of PED visits.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| 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".