Public Drug Plan Coverage for Children Across Canada: A Portrait of Too Many Colours
Bibliographic record
Abstract
BACKGROUND: As debate continues regarding pharmacare in Canada, little discussion has addressed appropriate drug plan coverage for vulnerable populations, such as children. The primary objective of this study was to determine the extent of medication coverage for children in publicly administered programs in each province across Canada. METHODS: Data were collected on provincial, territorial and federal government drug plans, and 2003 formulary updates were obtained. A simulation model was constructed to demonstrate costs to a low-income family with an asthmatic child in each province. Programs were compared descriptively. The extent of interprovincial variation in 2003 formulary approvals was summarized statistically. RESULTS: There was 39% variation between provinces with respect to 2003 formulary approvals (chi-square p < 0.0001) and 48% variation for 2003 paediatric-labelled products (chi-square p < 0.0001). Across Canada, only 8% of 2003 formulary approvals were indicated primarily for paediatric conditions. In the simulation model, costs were less than or equal to 3% of household income in provinces with plans for low-income families, catastrophic costs (Ontario) or for the population. Families who failed to qualify for low income plans or who resided in New Brunswick or Newfoundland faced costs up to 7% of household income. INTERPRETATION: With regard to pharmaceutical benefits for children, provincial drug programs vary considerably in terms of whom they cover, what drugs are covered and how much subscribers must pay out of pocket. Unlike seniors and social assistance recipients, the provinces do not agree on the importance of providing comprehensive coverage for all children. For many Canadian children, significant financial barriers exist to medication access.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".