Distributional consequences of the transition from age‐based to income‐based prescription drug coverage in British Columbia, Canada
Bibliographic record
Abstract
In May, 2003, British Columbia transitioned from an age-based public drug program, with public subsidy primarily based on age, to an age-irrelevant income-based drug program, in which public subsidy is based primarily on household income. As one of the specific aims of the policy change was to improve fairness by increasing the extent to which payment for drugs is based on ability to pay, we measure the progressivity of pharmaceutical financing before and after the policy change in BC using Kakwani indices. Our results suggest that pharmaceutical financing became less regressive after the policy change. However, this decrease in regressivity arose primarily because high-income seniors were making greater direct contributions to pharmaceutical financing and not because low-income households were making smaller direct contributions. Our results also suggest that if the public financing of pharmaceuticals were maintained or increased, a change from age-based to income-based eligibility can unambiguously improve equity in finance. As populations in developed countries age, governments will increasingly consider reforms to publicly financed health-care programs with age-based eligibility. In assessing policy options, financial equity is likely to be a key consideration. These results suggest that income-based pharmacare can improve financial equity especially when implemented with a commitment to maintain or increase public funding for prescription drugs.
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".