Catastrophic drug coverage: utilization insights from the Ontario Trillium Drug Program
Bibliographic record
Abstract
<h3>Background:</h3> Catastrophic drug coverage programs help those with high drug-costs to reduce the burden of out-of-pocket expenses. We set out to measure changes in utilization, spending and demographic profiles of people accessing Ontario9s catastrophic drug program, the Trillium Drug Program. <h3>Methods:</h3> We conducted a cross-sectional time-series analysis examining quarterly utilization and spending trends among medications reimbursed by the Trillium Drug Program in Ontario, Canada from Jan. 1, 2000, to Dec. 31, 2016. In each of 2000, 2005, 2010 and 2015, we described the population of beneficiaries, including demographic information, health care utilization and medication utilization. <h3>Results:</h3> Over our study period, use of the Trillium Drug Program increased threefold from 3.6 beneficiaries per 1000 to 10.9 beneficiaries per 1000 Ontarians, and total government spending on the program increased by over 700%, reaching $487 million in 2016. Between 2000 and 2015, there was an increase in the number of beneficiaries who were under the age of 35 years (19.6% to 25.3%; <i>p</i> < 0.0001), did not have a hospital admission (68.3% to 80.5%; <i>p</i> < 0.0001) and had medium to high deductibles (2.3% to 8.0%; <i>p</i> < 0.0001). Further, there was a large increase in the percentage of users with drug claims greater than $1000 (3.4% to 10.4%; <i>p</i> < 0.0001) and those dispensed a high-cost biologic drug (1.6% to 5.5%; <i>p</i> < 0.0001). <h3>Interpretation:</h3> Increasing use of Ontario9s catastrophic drug program highlights the growing burden of high drug prices for Canadians. With a growing number of expensive drugs being approved in Canada, we anticipate that spending and use of the catastrophic drug program will continue to expand.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.003 |
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; both teacher heads agree on what is shown here.
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".