International drug price comparisons: quality assessment.
Bibliographic record
Abstract
OBJECTIVE: To quantitatively summarize results (i.e., prices and affordability) reported from international drug price comparison studies and assess their methodological quality. METHODS: A systematic search of the most relevant databases-Medline, Embase, International Pharmaceutical Abstracts (IPA), and Scopus, from their inception to May 2009-was conducted to identify original research comparing international drug prices. International drug price information was extracted and recorded from accepted papers. Affordability was reported as drug prices adjusted for income. Study quality was assessed using six criteria: use of similar countries, use of a representative sample of drugs, selection of specific types of prices, identification of drug packaging, different weights on price indices, and the type of currency conversion used. RESULTS: Of the 1 828 studies identified, 21 were included. Only one study adequately addressed all quality issues. A large variation in study quality was observed due to the many methods used to conduct the drug price comparisons, such as different indices, economic parameters, price types, basket of drugs, and more. Thus, the quality of published studies was considered poor. Results varied across studies, but generally, higher income countries had higher drug prices. However, after adjusting drug prices for affordability, higher income countries had more affordable prices than lower income countries. CONCLUSIONS: Differences between drug prices and affordability in different countries were found. Low income countries reported less affordability of drugs, leaving room for potential problems with drug access, and consequently, a negative impact on health. The quality of the literature on this topic needs improvement.
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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 | 0.396 | 0.682 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.011 | 0.013 |
| Bibliometrics | 0.039 | 0.049 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.011 | 0.009 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".