Little quantitative assessment of health inequality impacts occurs in the economic evaluation of health care. Distributional cost-effectiveness analysis (DCEA) offers an extension to cost-effectiveness analysis, estimating health inequality changes alongside population health. This thesis addresses two important methodological and empirical challenges for DCEAs. First, in order to measure inequality change, a baseline level distribution of health needs to be estimated. English health survey and national mortality data to are used to predict lifetime health, finding a gap between the most and least healthy fifths of the population of 10.97 quality-adjusted life years (QALYs). The second chapter estimates how the health effects of health care budget changes in England are allocated between social groups. Socioeconomic distributions of health care utilisation by disease, age and gender are used to disaggregate results from a previous study that estimated effects of expenditure by disease area. A substantial gradient in health effects is found, with 27% and 13% incurred by the most and least deprived fifths of the population, respectively. We apply the findings of the previous chapters to two different types of DCEA. The fourth chapter proposes a simplified version of DCEA, in which intervention health benefits follow the gender and socioeconomic patterns of health care utilisation. This approach is applied to 27 technology appraisals conducted by NICE: five interventions increase population health and worsen inequality and all still increase social welfare even when inequality aversion is high. The fifth chapter covers a full DCEA to evaluate smoking cessation interventions. A decision model is adapted to incorporate a wide range of key model inputs varied by socioeconomic status. As effectiveness and uptake are greater in the least deprived groups, all interventions increase health inequality, despite the greater number of smokers in the more deprived groups.