Written by Paloma Charlesworth, Assistant Project Manager
background
health inequality There are systematic, avoidable, and unjustified differences in health outcomes between patient groups. Despite decades of policy and research, this phenomenon not only persists, but in some cases is expanding. Over the past 10 years, the gap in life expectancy between the most deprived and most deprived areas of England has increased. 9.1~10.5 years among men, and 6.9~8.3 years old Among women.
These inequalities are mainly driven by socioeconomic factors; health services It plays an important role in alleviating The National Health Service (NHS) statutory duty Taking inequality into account, it is essential that decision-makers balance efforts to reduce disparities with overall health benefits. Key to this balance is how healthcare resources are allocated.
The National Institute for Health and Care Excellence (NICE) is at the heart of these decisions, guiding which technologies and interventions are funded. Traditionally, NICE relies on cost-effectiveness analyzes (CEA), which evaluate treatments based on cost per quality-adjusted life year (QALY). But implicit in this is the philosophy that all QALYs should be treated equally – “a QALY is a QALY.” As a result, in recent years NICE has introduced disease-like mechanisms. severity modifier and Higher willingness-to-pay threshold for highly specialized skills (HST) – effectively applies contextual or stock-specific weighting to QALYs in certain situations. However, no comparable intervention exists to specifically address health inequalities and NICE’s current approach therefore overlooks how benefits and harms are distributed across different patient groups. As a result, CEA itself fails to account for the possibility that compensation decisions may disproportionately affect already disadvantaged populations.
this conflict The gap between NICE’s commitment to reducing inequalities and its reliance on traditional cost-per-QALY methods has long been noted. Long-standing guidance on technical methods for reporting health inequalities has provided partial solutions, but gaps remain. For example, according to a December 2023 systematic review: 42% of single skill assessments (STA) Inequalities were not mentioned at all in NHS England’s CORE20plus5 priority areas, and where they were, the methods were inconsistent and there was a lack of methodological transparency.
To address this, NICE launched a public consultation in January 2025. Proposed Update Please refer to the Health Technology Assessment Manual. These changes will be implemented by May 2025, allowing more Systematic and transparent An approach that considers health inequalities in decision-making and utilizes distribution cost-effectiveness analysis (DCEA) methods.
update
Latest updates from NICE Health Technology Assessment Manualsets out the manufacturer submission framework for reimbursement and provides revised, clear, and detailed guidance on:
- When should evidence on health inequalities be included?
- Type of evidence to submit
- How will NICE use this evidence?
This is explained in more detail below.
When should evidence on health inequalities be included?
- Businesses should engage with NICE as early as possible in the Health Technology Assessment (HTA) process, from early NICE advice to the HTA scoping stage, to determine the relevance of the technology to health inequalities.
- Relevance is judged based on:
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- the scale of existing inequalities in patient populations;
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- Size of expected impact
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- Level of uncertainty in the analysis.
- The Committee will consider quantitative evidence only if the expected effects are proportionately meaningful.
Type of evidence to submit
- The main method is DCEA, which estimates incremental costs and outcomes by social subgroup, scales across populations, and explicitly accounts for opportunity costs.
- DCEA should only be used as a supplement to CEA and should also be presented as a standalone analysis to help decision makers understand the balance between equity and efficiency.
- DCEA requires more detailed data, including parameters stratified by social characteristics and disease prevalence. NICE reference practices typically specify stratification groups based on the Index of Multiple Deprivation (IMD), which provides the best data availability.
- Unless strong evidence indicates otherwise or the technology is expected to improve accessibility or compliance, uptake should be assumed to be the same across groups.
- For opportunity costs, the Commission should apply a flat slope in the base case analysis, but should also test mild and moderate slopes to reflect higher costs for more vulnerable groups.
- A full probabilistic sensitivity analysis is not necessary, but a deterministic sensitivity analysis should test key uncertainties such as disease prevalence and health benefit distribution.
- NICE has stated that it will not allow social welfare-based measures, such as the Atkinson Index, often used in DCEA, to apply QALY aversion weighting. All QALYs should remain unweighted.
- The output should report the following for each IMD quintile:
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- health opportunity cost
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- Net health benefits (in QALYs)
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- Descriptive inequality measures such as gaps, ratios, or regression results.
- The strongest submissions come with DCEA, along with a qualitative description of the health equity benefits of the technology.
How will NICE use this evidence?
- The Commission will assess the relevance of health inequality impacts. Flexibility may be applied to cost-effectiveness thresholds if significant reductions are demonstrated.
- Recommendations cannot be optimized for subgroups defined solely by social characteristics.
- Higher levels of evidential uncertainty may be acceptable if structural or social barriers to data collection are clearly demonstrated. The Committee will be aware of such limitations when making its recommendations.
- Presenting gross health benefits, opportunity costs and net health benefits by IMD quintile will enable the Commission to make more thoughtful judgments about the added value of reducing health inequalities.
DCEA’s expected challenges
The challenges in performing DCEA primarily arise from the larger data demands compared to standard CEA. While traditional CEAs may rely on population-level averages, DCEAs require data to be disaggregated by social group to assess equity impacts.
NICE currently recommends stratification by IMD, but this may not always be appropriate. For example, if inequalities are concentrated among specific social groups (e.g. ethnic minorities or people with certain health conditions), alternative stratification approaches may be more appropriate. However, justifying these alternatives requires strong evidence, and such evidence is not always readily available.
The standard assumption taken by NICE is equal uptake across interventions. However, this may not always be appropriate, and is further complicated when health inequalities arise due to differences in access to care. In these cases, additional data are needed to capture changes in intake and inform realistic assumptions about how the intervention will be adopted across patient groups.
Evidence requirements vary depending on the type of DCEA performed.
- The overall DCEA integrates equity considerations throughout the modeling process and relies heavily on subgroup-specific data. Subgroup-specific data are not always readily available for all subgroups, and evidence gaps can increase uncertainty, making performing a full DCEA more difficult.
- In contrast, aggregate DCEA is applied after the standard CEA has been completed. Aggregate data are used to estimate the distribution of health outcomes across subgroups, requiring less detailed subgroup-specific evidence. Although less data are needed, aggregate DCEA is limited in that it cannot convey the full impact of interventions on health inequalities.
The decision whether to perform a full or total DCEA may be based on the available data. When considering the additional data requirements and resulting resource investment required to conduct a full DCEA, one should also consider the impact that interventions may have on health inequalities and whether looking at a full DCEA would be of interest to HTA bodies such as NICE.
In addition to data considerations, there are also strategic considerations before submitting to the HTA agency. From a UK perspective, although NICE is increasingly highlighting health inequalities, there is no universal requirement to provide evidence on the distributional cost-effectiveness of interventions. Failure to provide this evidence may be seen as a missed opportunity, but manufacturers must balance the potential decision-making benefits against the risk of increased uncertainty resulting from incomplete or weak data.
Implications for companies and next steps
The inclusion of DCEA in NICE’s module updates provides new opportunities for companies to strengthen their submissions. By calling for clearer and more formal consideration of health inequalities, NICE paves the way for companies to demonstrate the wider societal value of technologies that target clinical areas where there are large inequalities in treatments.
To make the most of this opportunity, companies should work with NICE early on to establish the relevance of DCEA. Incorporating inequality considerations into strategic planning from the beginning ensures evidence generation addresses the right questions and minimizes the risk of costly data gaps later in the process.
We specialize in incorporating these considerations into HTA strategies. Our experienced team can provide expert support to ensure your submission meets NICE’s evolving requirements and fully reflects the value of your skills. If you want to know more about us HTA For submissions (including economic modeling), please contact: SOURCE Health EconomicsHEOR is a consulting firm specializing in evidence generation, health economics and communications.
