Bibliographic record
Abstract
As high-cost medicines put increasing pressure on public health care budgets, the need to identify 'fair' prices for medicines has never been greater. This paper proposes a framework, built upon fundamental economic principles, that allows for the consideration of 'fair' prices for medicines. The framework incorporates key considerations from conventional supply-side and demand-side approaches for specifying a cost-effectiveness 'threshold', including the health opportunity cost borne by other patients ([Formula: see text]) and society's willingness to pay for marginal improvements in population health ([Formula: see text]). The costs incurred by manufacturers in developing and supplying new medicines are also considered, as are the incentives for manufacturers to strategically price up to any common price per unit of benefit (cost-effectiveness 'threshold') specified by the payer. The framework finds that, at any 'fair' price, a medicine's dynamically calculated incremental cost-effectiveness ratio (ICER) lies below [Formula: see text]. When pricing medicines collectively, the framework finds that a common price below [Formula: see text] is required to maximize population health (consumer surplus) or to maximize total welfare (consumer and producer surplus). This framework has important policy implications for payers who wish to improve population health outcomes from constrained health care budgets. In particular, existing approaches to 'value-based pricing' should be reconsidered to ensure that patients receive a 'fair' share of the resulting economic surplus.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".