Adherence to Statin Therapy Under Drug Cost Sharing in Patients With and Without Acute Myocardial Infarction
Bibliographic record
Abstract
BACKGROUND: As medication spending grows, Medicare Part D will need to adapt its coverage policies according to emerging evidence from a variety of insurance policies. We sought to evaluate the consequences of copayment and coinsurance policies on the initiation of statin therapy after acute myocardial infarction and adherence to therapy in statin initiators using a natural experiment of all British Columbia residents aged 66 years and older. METHODS AND RESULTS: Three consecutive cohorts that included all patients who began statin therapy during full drug coverage (2001), coverage with a $10 or $25 copay (2002), and coverage with a 25% coinsurance benefit (2003-2004) were followed up with linked healthcare utilization data (n=51,561). Follow-up of cohorts was 9 months after each policy change. Adherence to statin therapy was defined as > or = 80% of days covered. Relative to full-coverage policies, adherence to new statin therapy was significantly reduced, from 55.8% to 50.5%, under a fixed copayment policy (-5.4% points; 95% CI, -6.4% to -4.4%) and the subsequent coinsurance policy (-5.4% points; 95% CI, -6.3% to -4.4%). An uninterrupted increase in the proportion of patients initiating statin therapy after an acute myocardial infarction (1.7% points per quarter) was observed over the study period, similar to a Pennsylvania control population with full coverage. Sudden changes to full out-of-pocket spending, similar to Medicare's Part D "doughnut hole," almost doubled the risk of stopping statins (adjusted odds ratio, 1.94, 95% CI, 1.82 to 2.08). CONCLUSIONS: Fixed patient copayment and coinsurance policies have negative effects on adherence to statin lipid-lowering drug therapy but not on their initiation after myocardial infarction.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".