The NICE Cost-Effectiveness Threshold: What it is and What that Means
Bibliographic record
Abstract
The National Institute for Health and Clinical Excellence (NICE) has been using a cost-effectiveness threshold range between £20 000 and £30 000 for over 7 years. What the cost-effectiveness threshold represents, what the appropriate level is for NICE to use, and what the other factors are that NICE should consider have all been the subject of much discussion. In this article, we briefly review hese questions, provide a critical assessment of NICE’s utilization of the incremental cost-effectiveness ratio (ICER) threshold to inform its guidance, and suggest ways in which NICE’s utilization of the ICER threshold could be developed to promote the efficient use of health service resources. We conclude that it is feasible and probably desirable to operate an explicit single threshold rather than the current range; the threshold should be seen as a threshold at which ‘other’ criteria beyond the ICER itself are taken into account; interventions with a large budgetary impact may need to be subject to a lower threshold as they are likely to displace more than the marginal activities; reimbursement at the threshold transfers the full value of an innovation to the manufacturer. Positive decisions above the threshold on the grounds of innovation reduce population health; the value of the threshold should be reconsidered regularly to ensure that it captures the impact of changes in efficiency and budget over time; the use of equity weights to sustain a positive recommendation when the ICER is above the threshold requires knowledge of the equity characteristics of those patients who bear the opportunity cost. Given the barriers to obtaining this knowledge and knowledge about the characteristics of typical beneficiaries of UK NHS care, caution is warranted before accepting claims from special pleaders; uncertainty in the evidence base should not be used to justify a positive recommendation when the ICER is above the threshold. The development of a programme of disinvestment guidance would enable NICE and the NHS to be more confident that the net health benefit of the Technology Appraisal Programme is positive.
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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 | 0.169 | 0.460 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.013 | 0.008 |
| Bibliometrics | 0.012 | 0.008 |
| Science and technology studies | 0.003 | 0.015 |
| Scholarly communication | 0.028 | 0.032 |
| Open science | 0.012 | 0.008 |
| Research integrity | 0.023 | 0.029 |
| Insufficient payload (model declined to judge) | 0.007 | 0.004 |
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".