The Impact of the Type of Insurance Plan on Adherence and Persistence with Antidepressants: A Matched Cohort Study
Bibliographic record
Abstract
OBJECTIVE: To compare adherence to, and persistence with, antidepressants (AD) in Quebec patients who are covered by private and public drug insurance. METHOD: A matched cohort study was conducted using prescription claims databases: reMed, a medication data registry for Quebec residents covered by private drug insurance, and Régie de l'assurance maladie du Québec database for Quebec residents with public drug insurance. Patients were aged 18 to 64 years and filled at least 1 prescription for an AD in monotherapy between December 2007 and September 2009 (194 privately and 2055 publicly insured patients). Adherence over 1 year was estimated using the proportion of prescribed days covered (PPDC). The difference in mean PPDC between patients with private and public drug insurance was estimated with linear regression. Persistence was compared between the groups with a Cox regression model. RESULTS: The PPDC was 86.4% (95% CI 83.3% to 89.5%) in privately insured and 82.2% (95% CI 78.5% to 85.9%) in publicly insured patients and the adjusted mean difference was 5.1% (95% CI 1.6% to 8.6%). Persistence was 51.0% in the private group and 19.7% in the public group at 1 year (P < 0.001); the adjusted hazard ratio was 0.49 (95% CI 0.30 to 0.79). CONCLUSION: Better adherence and persistence were observed in privately insured patients. Adherence difference may be due to lower copayment among privately insured patients.
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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 | 0.000 | 0.000 |
| 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) | 0.000 | 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".