Evaluating the Impact of Prescription Drug Coverage on Emergency Department Visits in Youth: Evidence From Ontario's OHIP+ Program
Bibliographic record
Abstract
This thesis examines the impact of Ontario’s OHIP+ program (introduced January 2018) to provide prescription coverage to youths <25, on suicide-related behavior (SRB) emergency department (ED) visits among youth. Using interrupted time series (ITS) and comparative ITS (CITS) analyses, the study assessed changes in SRB-related ED visits per 100,000 population overall and by socioeconomic status (SES). Youth with low-SES, less likely to have private insurance and more likely to benefit from OHIP+, were compared to high-SES youth. ITS results showed a significant immediate reduction in SRB-related ED visits after OHIP+ implementation (-9.39, 95% CI: -18.21 to -0.56). CITS results showed a larger immediate decline among low-SES youth (-19.61, 95% CI: -37.71 to -1.50), reducing rates from 54.11 to 45.90 per 100,000, with stronger effects among women. Findings suggest drug coverage can reduce youth mental health crises and support expanded pharmacare.
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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 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".