Support document: Health inequalities
Distributional cost-effectiveness analysis methods
| Component of DCEA | NICE's preferred approach |
|---|---|
|
Stratification of social groups |
Based on IMD. This should be supported by rationale |
|
Uncertainty |
Select sensitivity analyses. Full probabilistic analysis can be done but is not required |
|
Uptake |
Equal uptake across groups should be assumed No change in uptake should be assumed, unless supported by robust evidence |
|
Health inequality aversion weights |
Health inequality aversion weights should not be applied to QALYs |
|
Health opportunity cost |
Equally distributed across social groups with scenario analyses provided for alternative gradients |
|
Discounting |
The same annual rate of 3.5% for both costs and health effects |
|
Outputs |
Net health benefit, total health benefit, and health opportunity costs should be presented for each IMD quintile |
Abbreviations: DCEA, distributional cost-effectiveness analysis; IMD, Index of Multiple Deprivation; QALYs, quality-adjusted life years.
Stratification of social groups
Social groups should be stratified by the Index of Multiple Deprivation (IMD). The IMD reflects different aspects of deprivation, is widely collected in research studies, and is often used to estimate health inequalities. A rationale for the appropriateness of IMD to the health inequalities relating to a disease or health technology should be provided.
Some inequalities may be concentrated in specific social groups. For example, certain ethnic or inclusion health groups (see NHS England's Equality, diversity and health inequalities section on inclusion health groups). In these cases, other approaches to stratification may be considered if there is an evidence-based rationale. In some circumstances, it may be appropriate for a condition to be stratified by 2 characteristics. But, this can lower the quality and interpretability of the data.
Supplementary indices of the IMD, such as for children or older people, should not be used. The IMD can be used for these groups.
Uncertainty
A full probabilistic sensitivity analysis is not needed for the health inequality analysis. But, committees should consider it to be the best approach to quantifying uncertainty in health inequality impacts. Deterministic sensitivity and scenario analyses should be done for the main sources of uncertainty that determine the health inequality impacts. These will likely include the distributions of disease prevalence and incremental health benefits. Sources of uncertainty should be specified in the submission, whether or not they are measured.
Uptake
Health inequalities can occur because of differences in access to care or in health-seeking behaviour. Equal uptake should be assumed across all groups, unless there is evidence to support a different distribution. Differences in uptake across groups or technologies should be justified. This should be based on the best available evidence on the technology under evaluation or on similar treatments for the same condition. All data sources must be explicitly stated, quality assessed and justified.
DCEAs should assume that the new technology has no impact on uptake, unless evidence comparing it with existing treatment suggests it would improve access or adherence for certain groups. Impact on uptake should be justified by robust evidence, for example, from prescribing data for similar treatments or conditions.
Health inequality aversion weights
The results of the DCEA should not weight the costs or benefits of a technology differently based on the social characteristics of the people affected by the recommendation. This includes using mathematical functions that use health inequality aversion parameters to reflect social preferences around health inequalities.
Health opportunity cost
Committees can use a range of values when deliberating on the maximum acceptable incremental cost-effectiveness ratio above which a technology is not cost effective or below which it is. DCEAs require a value to be specified to determine net health benefit for each social group. So results should be based on multiple values within the ranges specified in sections 6.3.4 to 6.3.8 of the health technology evaluations manual. Where this range is between £20,000 and £30,000 per QALY gained, DCEAs should present results using £20,000 and £30,000 per QALY gained.
To calculate the distribution of net health benefit, an estimate of the distribution of health opportunity cost is needed. This shows the differences between social groups of:
-
forgone health benefits from displaced interventions when a technology or test is cost incurring, or
-
health benefits from freed-up resources when a technology or test is cost saving.
Health opportunity costs should be equally distributed between social groups in the base-case analysis. This should be accompanied by scenario analyses of light and moderate gradients that reflect a higher proportion of displacement in more disadvantaged groups to show how changing assumptions impacts the results. Alternative gradients should be justified with evidence where possible. The opportunity costs used for all gradients should be expressed in QALYs and presented in a summary table.
Table 2 outlines the recommended scenarios for modelling the share of health opportunity costs across 5 IMD groups. When a different approach to stratification is used, the appropriate scenarios may differ based on:
-
the relative size of the groups being considered
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the burden of disease across the groups and
-
the use of health services across the groups.
Rationale for why different distributions of health opportunity cost have been used should be provided, supported by evidence.
| Scenario | IMD1 (most deprivation) | IMD2 | IMD3 | IMD4 | IMD5 (least deprivation) |
|---|---|---|---|---|---|
|
Equally distributed |
20% |
20% |
20% |
20% |
20% |
|
Slight gradient |
22% |
21% |
20% |
19% |
18% |
|
Moderate gradient |
24% |
22% |
20% |
18% |
16% |
Abbreviation: IMD, Index of Multiple Deprivation.
Outputs
The following outputs should be presented:
-
The distribution of the technology's population health benefits across social groups, excluding any health opportunity costs. Evidence on cost-effectiveness for individual subgroups defined by social characteristics will not be considered.
-
The distribution of the health opportunity costs across social groups, showing the differences in QALYs forgone in each of the scenarios described in table 2.
-
Net health benefit, which shows the distribution of health benefits across social groups taking into account health opportunity costs. Net health benefit can be either:
-
negative, which suggests that a technology's health benefits do not outweigh the health losses caused by displacing other healthcare to fund the technology, or
-
positive, which suggests that the new technology will increase population health
-
-
Descriptive inequality metrics. These can include simple gaps and ratios between the top and bottom of the distribution, or the results of simple regressions that can incorporate information on the net health benefit of groups in the middle of the distribution.
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