Modeled Pediatric Emergency Visits Under Counterfactual Scenarios, 2023-2024

Estimated pediatric emergency department (PED) visits for the 2023-2024 period, predicted by an adjusted regression model under real-world conditions and four counterfactual scenarios. Results are stratified by Canadian Triage Acuity Scale (CTAS) levels 2 (emergent), 3 (urgent), and 4/5 (less urgent/non-urgent) for cases where the model provided significant effects. The dataset, authored by Denis Mongin, is a 9.5 KB Excel file shared under a CC-BY-4.0 license.

Use Cases

• Analyze the impact of geographic distance on pediatric emergency visits based on the '5 km from the PED' scenario.
• Model the effect of socio-economic status on healthcare demand based on the 'socio-economically wealthy neighborhoods' scenario.
• Evaluate the relationship between pediatrician density and emergency department utilization based on the '2 per 1,000 children' scenario.
• Assess combined policy impacts on triage acuity levels based on the scenario combining all modeled conditions.

Strengths

• Model outputs are stratified by specific Canadian Triage Acuity Scale (CTAS) levels (2, 3, 4/5).
• Includes predictions for four distinct, policy-relevant counterfactual scenarios.
• Dataset is small (9.5 KB), facilitating quick inspection and analysis.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Data is modeled estimates, not observed counts, limiting use for descriptive analysis.

Provenance

Source

Denis Mongin via figshare

Collection Method

Predictions from an adjusted regression model.

Time Range

2023-2024

Freshness

Last updated 2026-05-28 17:22:15; freshness should be verified.

Geography

Geneva, Switzerland (inferred from description mentioning Geneva neighborhoods)