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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".