Background. A common aim of health expenditure is to reduce unfair inequalities in health. Although previous research has attempted to estimate the total health effects of changes in health expenditure, little is known about how changes affect different groups in the population. Methods. We propose a general framework for disaggregating the total health effects of changes in health expenditure by social groups. This can be performed indirectly when the estimate of the total health effect has first been disaggregated by a secondary factor (e.g., disease area) that can be linked to social characteristics. This is illustrated with an application to the English National Health Service. Evidence on the health effects of expenditure across 23 disease areas is combined with data on the distribution of disease-specific hospital utilization by age, sex, and area-level deprivation. Results. We find that the health effects from NHS expenditure changes are produced largely through disease areas in which individuals from more deprived areas account for a large share of health care utilization, namely, respiratory and neurologic disease and mental health. We estimate that 26% of the total health effect from a change in expenditure would accrue to the fifth of the population living in the most deprived areas, compared with 14% to the fifth living in the least deprived areas. Conclusions. Our approach can be useful for evaluating the health inequality impacts of changing health budgets or funding alternative health programs. However, it requires robust estimates of how health expenditure affects health outcomes. Our example analysis also relied on strong assumptions about the relationship between health care utilization and health effects across population groups.

Distributional cost effectiveness analysis is a new method that can help to redesign prevention programmes by explicitly modelling the distribution of health opportunity costs as well as the distribution of health benefits. Previously we modelled cardiovascular disease (CVD) screening audit data from Liverpool, UK to see if the city could redesign its cardiovascular screening programme to enhance its cost effectiveness and equity. Building on this previous analysis, we explicitly examined the distribution of health opportunity costs and we looked at new redesign options co-designed with stakeholders. We simulated four plausible scenarios: a) no CVD screening, b) ‘current’ basic universal CVD screening as currently implemented, c) enhanced universal CVD screening with ‘increased’ population-wide delivery, and d) ‘universal plus targeted’ with top-up delivery to the most deprived fifth. We also compared assumptions around whether displaced health spend would come from programmes that might benefit the poor more and how much health these programmes would generate. The main outcomes were net health benefit and change in the slope index of inequality (SII) in QALYs per 100,000 person years. ‘Universal plus targeted’ dominated ‘increased’ and ‘current’ and also reduced health inequality by −0.65 QALYs per 100,000 person years. Results are highly sensitive to assumptions about opportunity costs and, in particular, whether funding comes from health care or local government budgets. By analysing who loses as well as who gains from expenditure decisions, distributional cost effectiveness analysis can help decision makers to redesign prevention programmes in ways that improve health and reduce health inequality.