Effect of a Psychiatric Emergency Department Expansion on Acute Mental Health and Addiction Service Use Trends in a Large Urban Center
Bibliographic record
Abstract
OBJECTIVE: This study examined recent growth in demand for acute mental health and addiction (MHA) care in a large urban center and changes in patient flow following the expansion of a psychiatric emergency department (ED). METHODS: A retrospective observational design used administrative data in adjusted negative binomial regression models to identify time trends at seven hospitals over a 6-year period in central Toronto. Two-part linear spline models compared trends before and after a psychiatric ED expansion. RESULTS: Per capita MHA-related ED visits grew rapidly across the acute care system over the study period, although admissions per MHA ED visit decreased. Expanding a psychiatric ED did not influence overall system-level growth, but it significantly shifted traffic; the annual MHA ED visit growth rate increased at the expanded ED while decreasing at surrounding hospitals. CONCLUSIONS: Given increasing demand systemwide, individual hospital ED expansions may be inappropriate; planning should consider the whole system.
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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 | 0.001 | 0.001 |
| 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".