The impact of reference pricing system on brand name’s prices : the case of Tunisia
Bibliographic record
Abstract
Many policies are planned to face the increasing rate in health costs. In such circumstances and in order to reduce the pharmaceutical expenses, Tunisia adopted a reform of Health Insurance System. We study the effect of the introduction of reference pricing on \npharmaceuticals’ price. In this study we use data for four molecules from IMS Health \ndatabase. The data span from the third quarter 2002 to fourth quarter 2008. First, we study competition effect on brand-names’ price and generic one. We find that the brand name price’s drop is more important than the average price of generic. Then, we examine the effect \nof the introduction of reference pricing (RP) on prices. It shows that the brand name’s price decline after the introduction of RP and generic competition has an important role in this \nprocess. We find that the RP system has a strong effect in terms of reducing prices of \npharmaceuticals; the effect is stronger for brand-name than generic versions. This confirms that the RP encourages generic competition and induces generic switching.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".