Can pharmacare reduce suicide-related behaviors? A quasi-experimental study in Ontario Youth
Bibliographic record
Abstract
Background Canada’s OHIP+ program, implemented in 2018, provided free comprehensive prescription drug coverage to individuals under 25. Given that youths face elevated risks of suicide-related behaviors (SRBs) and frequently encounter cost-related barriers to accessing mental health medications, this study evaluated whether OHIP+ impacted emergency department (ED) visits for SRBs among Ontario youth aged 19–24. Methods We used linked data from the 2016 Canadian Census and the National Ambulatory Care Reporting System, identifying SRB-related ED visits between April 2016 and March 2020. A single interrupted time series (ITS) and a comparative ITS (CITS) with Coarsened Exact Matching were employed to assess changes in SRB-related ED visits associated with the implementation of OHIP+. The CITS compared low- versus high-socioeconomic status (SES) youths, based on the assumption that low-SES youths are more likely to benefit from public drug coverage due to greater financial barriers. Results OHIP+ implementation was associated with an immediate reduction of 9.4 SRB-related ED visits per 100,000 youth per month (95% CI: -18.2 to -0.6). In the CITS analysis, low-SES youth experienced a significantly greater reduction compared to high-SES youth (difference: -19.6; 95% CI: -37.7 to -1.5). Sex-stratified models indicated that these effects were driven primarily by reductions among females. Conclusion Public drug coverage through OHIP+ was associated with a significant reduction in ED visits for suicide-related behaviors, particularly among low-income and female youth. Our findings underscore the potential of pharmacare to reduce acute mental health crises and promote health equity among vulnerable youth populations.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".