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, 40 (2), 170-182

Estimating Social Variation in the Health Effects of Changes in Health Care Expenditure


Estimating Social Variation in the Health Effects of Changes in Health Care Expenditure

James Love-Koh et al. Med Decis Making.


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.

Keywords: distributional cost-effectiveness analysis; health equity; health inequality; health opportunity cost.

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