Barriers to timely medication access in Canada: Implications for healthcare policy
Bibliographic record
Abstract
During the past few years, rapid access to medication has been important for having effective healthcare delivery, nevertheless Canadian patients encounter growing delays in getting treatment. In 2024, patients had to wait for an average of 30 weeks from referral by a general practitioner to actual treatment, which was the worst ever recorded—up from 27.7 weeks in 2023 and 222% longer than the 9.3-week benchmark in 1993. These delays are aggravated by diagnostic bottlenecks, with wait times of 16.2 weeks for MRI scans and 8.1 weeks for CT scans. Such prolonged intervals are more than clinically acceptable thresholds and risk compromising patient outcomes. This paper investigates systemic barriers—including specialist shortages, infrastructure limitations, and regional disparities—and evaluates their applications for healthcare policy. By identifying key inefficiencies, the investigation plans to inform evidence-based reforms that enhance medication access and equity across Canada.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".