Recent trends in the dispensing of 90-day-supply prescriptions at retail pharmacies: implications for improved convenience and access.
Bibliographic record
Abstract
BACKGROUND: Mail-service pharmacies offer consumers the convenience of prescriptions filled with a 90-day supply of medication. Unlike mail-service pharmacies, retail pharmacies traditionally dispensed maintenance medication prescriptions with a 30-day supply. However, the retail landscape changed in May 2008 with Walmart's announcement of an extension of its $4 Prescription Program to include 90-day-supply prescriptions. OBJECTIVE: To evaluate recent changes in access to and use of 90-day-supply maintenance medications dispensed via retail pharmacy. SUMMARY: As of the first quarter of 2007, the proportion of retail-dispensed maintenance medications with a 90-day supply (compared with all maintenance prescriptions dispensed) among Medicare Part D plans, self-insured employers, and private health plans was 5.1%, 5.1%, and 5.0%, respectively. As of December 2009, this ratio had risen to 8.0% for Medicare plans and 8.1% for commercial health plans; the ratio among employers had risen more modestly to 6.1%. Of particular interest and importance, the proportion increased similarly for brand and for generic medications. CONCLUSION: There has been substantial growth in 90-day prescriptions dispensed via retail pharmacy, a trend that is likely to continue as more insurance providers adopt compatible benefit designs. It is important to continue monitoring these trends and to identify opportunities to rigorously evaluate their impact on medication adherence and healthcare costs.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".