A Retrospective Cohort Analysis of Mental Health-Related Emergency Department Visits Among Veterans and Non-Veterans Residing in Ontario, Canada: Une analyse de cohorte rétrospective des visites au service d’urgence liées à la santé mentale parmi les vétérans et non-vétérans résidant en Ontario, Canada
Bibliographic record
Abstract
OBJECTIVES: Emergency departments (EDs) are a vital part of healthcare systems, at times acting as a gateway to community-based mental health (MH) services. This may be particularly true for veterans of the Royal Canadian Mounted Police who were released prior to 2013 and the Canadian Armed Forces, as these individuals transition from federal to provincial healthcare coverage on release and may use EDs because of delays in obtaining a primary care provider. We aimed to estimate the hazard ratio (HR) of MH-related ED visits between veterans and non-veterans residing in Ontario, Canada: (1) overall; and by (2) sex; and (3) length of service. METHODS: This retrospective cohort study used administrative healthcare data from 18,837 veterans and 75,348 age-, sex-, geography-, and income-matched non-veterans residing in Ontario, Canada between April 1, 2002, and March 31, 2020. Anderson-Gill regression models were used to estimate the HR of recurrent MH-related ED visits during the period of follow-up. Sex and length of service were used as stratification variables in the models. RESULTS: Veterans had a higher adjusted HR (aHR) of MH-related ED visits than non-veterans (aHR, 1.97, 95% CI, 1.70 to 2.29). A stronger effect was observed among females (aHR, 3.29; 95% CI, 1.96 to 5.53) than males (aHR, 1.78; 95% CI, 1.57 to 2.01). Veterans who served for 5-9 years had a higher rate of use than non-veterans (aHR, 3.76; 95% CI, 2.34 to 6.02) while veterans who served for 30+ years had a lower rate compared to non-veterans (aHR, 0.60; 95% CI, 0.42 à 0.84). CONCLUSIONS: Rates of MH-related ED visits are higher among veterans overall compared to members of the Ontario general population, but usage is influenced by sex and length of service. These findings indicate that certain subpopulations of veterans, including females and those with fewer years of service, may have greater acute mental healthcare needs and/or reduced access to primary mental healthcare.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".