ArticlePharmacoEconomics2021
Modifying NICE's Approach to Equity Weighting.
Article in PharmacoEconomics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
8 citing papers in PubMed, 29 citations in OpenAlex.
- Practical Considerations for Incorporating Equity More Explicitly in Australian Health Technology Assessment Processes.PharmacoEconomics · 2026Review
- Aligning Indigenous and Western Concepts of Health Resource Decision Making in a Western Canadian First Nations Context.Applied health economics and health policy · 2026Article
- Do We Understand Unmet Need? A Proposal to Use Length-Of-Life Equivalent (LOLE) as a Patient-Centric Measure of Unmet Need.PharmacoEconomics - open · 2025Article
- An empirical ethics study of the coherence of NICE technology appraisal policy and its implications for moral justification.BMC medical ethics · 2024Article
- Distributional Cost-Effectiveness of Equity-Enhancing Gene Therapy in Sickle Cell Disease in the United States.Annals of internal medicine · 2023Article
- The Broader Opportunity Costs in the Broader Cost-Effectiveness Analysis Framework.Applied health economics and health policy · 2023Article
- Making the rules make sense: valuation of constrained resources.The European journal of health economics : HEPAC : health economics in prevention and care · 2023Article
- Estimating the shares of the value of branded pharmaceuticals accruing to manufacturers and to patients served by health systems.Health economics · 2021Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The UK's National Institute for Health and Care Excellence (NICE) recently launched a consultation on the methods it uses to evaluate new health technologies, and has highlighted the issue of how 'modifiers', including equity weights, should be incorporated into its processes. The practice of applying equity weights to specific population subgroups, as a means for increasing the effective cost-effectiveness threshold for some new health technologies, is well established in health technology assessment. It is also the subject of extensive discussion in the academic literature. In this paper, we demonstrate that NICE's current approach to equity weighting has the effect of reducing both population health and equity-weighted population health, a fundamental problem that appears to place NICE in contravention of its principles and obligations. We consider two potential methods for modifying NICE's current approach to address this problem. We also consider the merits of NICE abandoning its current approach to equity weighting and adopting a standard 'net benefit' approach in its place. We find that adopting a standard 'net benefit' approach is the most desirable option, as it provides for the most transparency while avoiding specific issues that arise when attempting to modify NICE's current approach. Regardless of the approach NICE uses for equity weighting, we find that protecting the health of National Health Service patients requires that some new technologies be evaluated using an effective cost-effectiveness threshold lower than the 'supply-side' cost-effectiveness threshold. This poses a particular challenge for NICE, given its obligations under the 2019 'Voluntary Scheme' between the UK pharmaceutical industry, the National Health Service, and the UK Government. We conclude by making some recommendations as to how NICE can move forward with the use of 'modifiers' in its decision making.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.