PP46 A cross country comparison of the effect of co-payments for prescriptions on adherence to medications
Bibliographic record
Abstract
Background Generalisability has been reported as a barrier to using evidence in policy making. Little data are available on whether US and Canadian based evidence on cost-sharing and medication adherence is generalizable to international populations. To explore external validity, we compared the impact of two similar cost sharing policies, one in the US and one in Ireland, on medication adherence. Methods A repeated measures longitudinal study design was employed to measure individual drug adherence before and after the introduction of drug cost-sharing policies. The Irish policy introduced a 50 cent copayment/prescription item in a publicly insured population in 2010. A similar policy occurred in the Massachusetts Medicaid population in 2003. Prescription data were obtained from centrally held pharmacy claims databases; HSE-PCRS, in Ireland and Medicaid Analytical Extract in the US New users of anti-hypertensive, anti-hyperlipidaemic and anti-diabetes drugs entered the cohort 6 months prior to initiation of cost-sharing polices and were followed for 12 months post-policy change. Segmented regression with generalised estimating equations and an autoregressive correlation structure was used. Results The Irish policy change resulted in a 3.9% (95% CI, 2.91%-5.02%) immediate drop in adherence to anti-hypertensive drugs in Ireland, whereas the US policy did not affect anti-hypertensive adherence. Relative to the US, the Irish population had a 5.3% (95% CI, 3.68% - 6.92%) additional decrease in adherence to anti-hypertensive drugs immediately after the policy change. Adherence to anti-hyperlipidaemic drugs was insignificantly reduced (-0.6235%, 95% CI, - 2.41%-1.16%) immediately post-policy change in the U. S. However, adherence to anti-hyperlipidaemics was reduced in Ireland by 3.4% (95% CI, 2.25%-4.62%). Compared to the US, Irish patients decreased their adherence to anti-hyperlipidaemics by 2.8% (95% CI, 0.673%-4.945%). Adherence to anti-diabetic drugs did not differ internationally post-policy change. There was no evidence for international differences in the long-term impact (12 months) of policy changes. Conclusion Irish and US populations had different changes in adherence to anti-hypertensive and anti-hyperlipidaemic drugs directly after implementation of cost-sharing policies, with greater reductions in adherence in the Irish population. However, changes in adherence to anti-diabetic drugs were similar between the populations. This study suggests that North American and Canadian evidence may not be automatically internationally generalizable. Rather, the specific attributes of a setting should always be considered before applying evidence to policy. This novel study will be of interest to global policymakers as they seek to develop evidence based cost-sharing policies.
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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 | 0.006 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.004 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".