Inequity in publicly funded physician care: what is the role of private prescription drug insurance?
Bibliographic record
Abstract
This study examines the impact that private financing of prescription drugs in Canada has on equity in the utilization of publicly financed physician services. The complementary nature of prescription drugs and physician service use alongside the reliance on private finance for drugs may induce an income gradient in the use of physicians. We use established econometric methods based on concentration curves to measure equity in physician utilization and its contributors in the province of Ontario. We find that individuals with prescription drug insurance make more physician visits than do those without insurance, and the effect on utilization is stronger for the likelihood of a visit than the conditional number of visits, and stronger for individuals with at least one chronic condition than those with no conditions. Results of the equity analyses reveal that the most important contributors to the pro-rich inequity in physician utilization are income and private prescription drug insurance, while public insurance, which covers older people and those on social assistance, has a pro-poor effect. These findings highlight that inequity in access to and use of publicly funded services may arise from the interaction with privately financed health services that are complements to the use of public services.
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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 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".