A Systematic Review of Cost-Sharing Strategies Used within Publicly-Funded Drug Plans in Member Countries of the Organisation for Economic Co-Operation and Development
Bibliographic record
Abstract
BACKGROUND: Publicly-funded drug plans vary in strategies used and policies employed to reduce continually increasing pharmaceutical expenditures. We systematically reviewed the utilization of cost-sharing strategies and physician-directed prescribing regulations in publicly-funded formularies within member nations of the Organization of Economic Cooperation and Development (OECD). METHODS & FINDINGS: Using the OECD nations as the sampling frame, a search for cost-sharing strategies and physician-directed prescribing regulations was done using published and grey literature. Collected data was verified by a system expert within the prescription drug insurance plan in each country, to ensure the accuracy of key data elements across plans. Significant variation in the use of cost-sharing mechanisms was seen. Copayments were the most commonly used cost-containment measure, though their use and amount varied for those with certain conditions, most often chronic diseases (in 17 countries), and by socio-economic status (either income or employment status), or with age (in 15 countries). Caps and deductibles were only used by five systems. Drug cost-containment strategies targeting physicians were also identified in 24 countries, including guideline-based prescribing, prescription monitoring and incentive structures. CONCLUSIONS: There was variable use of cost-containment strategies to limit pharmaceutical expenditures in publicly funded formularies within OECD countries. Further research is needed to determine the best approach to constrain costs while maintaining access to pharmaceutical drugs.
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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 | 0.022 | 0.105 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.007 |
| Bibliometrics | 0.024 | 0.028 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 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".