How health inequalities accumulate and combine to affect treatment value:a distributional cost-effectiveness analysis of smoking cessation interventions

Introduction Reduction of health inequality is a goal in health policy, but commissioners lack information on how policies change health inequality. This study illustrates how decision models can be readily extended to produce information on health inequality impacts as well as for population health, using the example of smoking cessation therapies. Methods We retrospectively adapt a model developed for public health guidance to undertake distributional cost effectiveness analysis. We identify and incorporate evidence on how inputs vary by area-level deprivation. Therapies are evaluated in terms of total population health, extent of inequality, and a summary measure of equally distributed equivalent health based on a societal value for inequality aversion. Last, we examine how accounting for social variation in different sets of parameters affects our results. Results All interventions increase population health and reduce the slope index of inequality. At estimated levels of health inequality aversion for England, our results indicate that the increases in inequality account for between 8%-10% of the overall social value of the interventions. Discussion The inequality impacts are driven by the greater proportion of smokers in disadvantaged groups, despite higher benefits of quitting and higher intervention uptake amongst advantaged groups. Failure to account for differential effects between groups leads to changes about the magnitude of the health inequality impact but does not alter conclusions about value for money.