Is There a Relationship Between Patient Beliefs or Communication About Generic Drugs and Medication Utilization?
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Insurers and policymakers strive to stimulate more cost-effective prescribing and, increasingly, are educating beneficiaries about generics. OBJECTIVES: To evaluate the relationship between patient beliefs and communication about generic drugs and actual drug use. RESEARCH DESIGN AND SUBJECTS: We performed a national mailed survey of a random sample of 2500 commercially-insured adults. Patient responses were linked to pharmacy claims data to assess actual generic medication use. MEASURES: We used factor analysis to develop 5 multi-item scales from patient survey responses that measured: (1) general preferences for generics, (2) generic safety/effectiveness, (3) generic cost/value, (4) comfort with generic substitution, and (5) communication with providers about generics. The relationship between each scale and the proportion of prescriptions filled for generics was assessed using linear regression, controlling for demographic, health, and insurance characteristics. Separate models were created for each scale and then all 5 scales were included simultaneously in a fully-adjusted model. RESULTS: The usable response rate was 48%. When evaluated independently, a 1 SD increase in each of the 5 scales was associated with a 3.1% to 6.3% increase in generic drug use (P < 0.05 for each). In the fully adjusted model, only 2 scales were significantly associated with generic drug use: comfort with generic substitution (P = 0.021) and communication with providers about generic drugs (P = 0.012). CONCLUSIONS: Generic drug use is most closely associated with the 2 actionable items we evaluated: communication with providers about generics and comfort with generic substitution. Educational campaigns that focus on these 2 domains may be most effective at influencing generic drug use.
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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) | 0.001 | 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 it