Impact of income-based deductibles on drug use and health care utilization among older adults
Bibliographic record
Abstract
<h3>BACKGROUND:</h3> Income-based deductibles are present in several provincial public drug plans in Canada and have been the subject of extensive debate. We studied the impact of such deductibles in British Columbia’s Fair PharmaCare plan on drug and health care utilization among older adults. <h3>METHODS:</h3> We used a quasi-experimental regression discontinuity design to compare the impact of deductibles in BC’s PharmaCare plan between older community-dwelling adults registered for the plan who were born in 1928 through 1939 (no deductible) and those born in 1940 through 1951 (deductible equivalent to 2% of household income). We used 1.2 million person-years of data between 2003 and 2015 to study public drug plan expenditures, overall drug use, and physician and hospital resource utilization in these 2 groups. <h3>RESULTS:</h3> The income-based deductible led to a 28.6% decrease in person-years in which public drug plan benefits were received (95% confidence interval [CI] −29.7% to −27.5%) and to a reduction in the per capita extent of annual benefits by $205.59 (95% CI −$247.81 to −$163.37). Despite this difference in public subsidy, we found no difference in the number of drugs received or in total drug spending once privately paid amounts were accounted for (<i>p</i> = 0.4 and 0.8, respectively). Further, we found only small or nonexistent changes in health care resource utilization at the 1939 threshold. <h3>INTERPRETATION:</h3> A modest income-based deductible had a considerable impact on the extent of public subsidy for prescription drugs. However, it had only a trivial impact on overall access to medicines and use of other health services. Unlike copayments, modest income-based deductibles may safely reduce public spending on drugs for some population groups.
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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 | 0.002 |
| 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) | 0.001 | 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".