Background
A common aim of health expenditure is to reduce unfair inequalities in health. Whilst 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 NHS. Evidence on the health effects of expenditure across 23 disease areas is combined with data on the distribution of disease-specific hospital utilisation by age, sex and area level deprivation.
Results
We find that the health effects from NHS expenditure changes are produced largely through disease areas where individuals from more deprived areas account for a large share of healthcare utilisation, namely respiratory and neurological 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 programmes. However, it requires robust estimates of how health expenditure affects health outcomes. Our example analysis also relied on strong assumptions about the relationship between healthcare utilisation and health effects across population groups.

Objective: To investigate whether continuity of care in family practice reduces unplanned hospital use for people with serious mental illness (SMI). Data Sources Linked administrative data on family practice and hospital utilization by people with SMI in England, 2007-2014. Study Design: This observational cohort study used discrete-time survival analysis to investigate the relationship between continuity of care in family practice and unplanned hospital use: emergency department (ED) presentations, and unplanned admissions for SMI and ambulatory care-sensitive conditions (ACSC). The analysis distinguishes between relational continuity and management/ informational continuity (as captured by care plans) and accounts for unobserved confounding by examining deviation from long-term averages. Data Collection/Extraction Methods: Individual-level family practice administrative data linked to hospital administrative data. Principal Findings: Higher relational continuity was associated with 8-11 percent lower risk of ED presentation and 23-27 percent lower risk of ACSC admissions. Care plans were associated with 29 percent lower risk of ED presentation, 39 percent lower risk of SMI admissions, and 32 percent lower risk of ACSC admissions. Conclusions: Family practice continuity of care can reduce unplanned hospital use for physical and mental health of people with SMI.