Select whether the intervention population is defined by disease (ICD) code (e.g. C50, breast cancer) or risk factor (e.g. smokers). Multiple ICD codes and risk factors can be included.
A list of ICD-10 code descriptions can be found here
Select within range of 1-100
Once complete, proceed to the 'CEA inputs' tab
Cost-effectiveness analysis results
It is strongly recommended that users define their own recipient population sizes. The estimates are automatically derived from the disease/risk factor population data and do not relate to specific interventions.
Once complete, proceed to the 'Distributional inputs' tab
Socioeconomic differences are analysed using the Index of Multiple Deprivation (IMD), which computes an index score for over 30,000 neighbourhoods in England based on information on education, training, employment, housing, health, crime and income in the area.
IMD1 contains people living in the most deprived 20% of neighbourhoods in England. IMD5 contains those living in the least deprived 20%.
The uptake rate (a value between 0 and 1) defines the proportion of the eligible population utilising the intervention in each IMD quintile group.
Base case uptake
Alternative uptake scenario
The per person incremental QALY effect of an intervention can vary by IMD quintile group. Ticking the box below allows you to modify a set of multipliers for each IMD quintile group that are applied to the average incremental QALY effect defined in 'CEA inputs' tab (a value of 1 yields the average effect).
The cost impact of the intervention(s) fall on those across the health service and not just the intervention population. By default, an empirical estimate of the distribution of opportunity costs is used. A custom distribution can be defined by ticking the box below.
Results can now be viewed on the 'Equity impact analysis' and 'Equity trade-off analysis' pages in the top menu