The influence of socioeconomic status on health resource utilization in pediatric epilepsy in a universal health insurance system
Bibliographic record
Abstract
OBJECTIVES: It is unknown if there is a disparity in health resource utilization (HRU) among children with epilepsy in a universal health insurance system. The aims of this study were to evaluate whether socioeconomic status (SES) influenced the pattern of HRU among children with epilepsy, and to determine if neurology visits were associated with emergency department (ED) visits and hospitalizations. METHODS: Health administrative databases were used to identify HRU among children with epilepsy in Ontario, Canada. The frequency of neurology visits, ED visits, and hospitalizations were assessed for 1 year. SES was measured using dissemination area income and deprivation index. The association between SES and HRU was evaluated, adjusting for age, sex, residence, and comorbidities. Subsequently, we assessed whether neurology visits influenced ED visits and hospitalizations, adjusting for age, sex, residence, comorbidities, and SES. RESULTS: Deprivation index was a more sensitive measure of disparity in HRU than dissemination area income. Status epilepticus-related ED visits and hospitalizations were most expensive but accounted for a small proportion of total costs. Higher deprivation was associated with fewer neurology visits (relative risk [RR] 0.85-0.89), more frequent ED visits (RR 1.08-1.36), and hospitalizations (RR 1.27). Increased neurology visits were associated with more frequent ED visits (RR 1.10) and hospitalizations (RR 1.15). The associations between neurology visits and ED visits as well as hospitalizations varied by deprivation index, in that neurology visits were associated with increased ED visits and hospitalizations and the increase was higher in the most deprived relative to the least deprived (all p < 0.0001). SIGNIFICANCE: We found disparity in HRU by SES despite the universal health insurance system. More frequent neurology visits were associated with more frequent ED visits and hospitalizations after adjusting for SES, probably related to epilepsy severity. Our study identified an at-risk population for high resource use that may require additional support to reduce ED visits and hospitalizations.
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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".