Modifying NICE's Approach to Equity Weighting.

2021 
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.
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    13
    References
    2
    Citations
    NaN
    KQI
    []
    Baidu
    map