Feasibility study to characterize price and reimbursement decision-making criteria for the inclusion of new drugs in the Spanish National Health System: the cefiderocol example
Bibliographic record
Abstract
OBJECTIVES: The reimbursement of medicines by the Spanish National Health System (NHS) is based on a set of criteria included in the Royal Legislative Decree 1/2015 (RDL 1/2015). The Interministerial Committee on Pricing of Medicines and Healthcare Products (CIPM) is responsible for the final price and reimbursement (P&R) decision, including on its resolutions the criteria listed in the law by which the reimbursement of a drug is approved or denied. Nevertheless, the information behind its reasoning is not provided. The present study aims to characterize the P&R criteria of the RDL 1/2015 through criteria definitions from other countries to improve the P&R evaluation in Spain. RESULTS: A multidisciplinary experts panel with relevant experience in drug evaluation and decision making at national, regional, and local level in Spain was selected for this study. A literature review to characterize the criteria listed in the RDL 1/2015 was performed based on the most relevant and recognized Health Technology Assessment (HTA) agencies in Europe, UK, and Canada. Eventually, a feasibility study was performed to evaluate the novel drug cefiderocol using the characterized criteria, including a reflective discussion of the results. CONCLUSIONS: Consensus was reached among the multidisciplinary experts on the characterization of the criteria set by the law. The feasibility of their application to a new drug was exploratory, notwithstanding it showed the potential to improve the transparency as well as to offer a more structured rationale for the CIPM to evaluate the inclusion of new drugs in the Spanish NHS.
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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 | 0.068 | 0.160 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| 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".