Sociodemographic characteristics and emergency department visits and inpatient hospitalizations for atopic dermatitis in Ontario: a cross-sectional study
Bibliographic record
Abstract
BACKGROUND: Some jurisdictions experience sociodemographic disparities in atopic dermatitis care, including emergency department visits, but data from Canada are limited. Our objectives were to estimate the prevalence of atopic dermatitis in Ontario and to identify sociodemographic factors associated with emergency department visits and hospitalizations for this condition. METHODS: We conducted a cross-sectional analysis of patients in the Electronic Medical Record Primary Care database linked with administrative health data for Ontario, Canada. We estimated period prevalence and health service utilization for atopic dermatitis from 2005 to 2015. We used multivariable log-binomial regression to calculate adjusted risk ratios (RRs) and 95% confidence intervals (CIs) for associations between local dermatologist density and the proportion of emergency department visits and hospitalizations for atopic dermatitis. RESULTS: Among 249 984 patients, we identified 7812 with atopic dermatitis (period prevalence 2005-2015: 3.1%). Almost all physician visits for atopic dermatitis were to primary care physicians (> 99%). For every additional dermatologist per 100 000 population, the proportions of emergency department visits and hospitalizations for atopic dermatitis increased by 29% (RR 1.29, 95% CI 1.05-1.57). This relationship occurred in and around Toronto but was not consistent across the province. INTERPRETATION: In Ontario, higher dermatologist density was not associated with lower emergency department utilization and hospitalization for atopic dermatitis; the association varied in different locales with similar dermatologist densities. Strategies to improve access to care for atopic dermatitis should be tailored to local contexts.
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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".