Routine Distributional Analysis of Health Inequality Impact by Socioeconomic Group: Technical Feasibility Study in Queensland, Australia

Objectives This study aimed to evaluate the technical feasibility of routine distributional analyses of healthcare interventions in Australia, by adapting a Health Inequality Impact Calculator for Queensland. Building on methods established in a previous study in England, the calculator compares the magnitude of health inequality impact across interventions for different diseases. Methods The calculator was adapted for adults in Queensland using the Index of Relative Socio-economic Advantage and Disadvantage quintiles, Australian Bureau of Statistics population estimates, 2023 hospital admissions (International Classification of Diseases-10 th edition 3-digit level) from Queensland Health, and published quality-adjusted life expectancy. It was used to conduct aggregate distributional cost-effectiveness analysis of 5 interventions for diseases with relatively high prevalence in disadvantaged groups, based on existing cost-effectiveness results identified by a targeted review. The health inequality impact was summarized using the slope index of inequality in quality-adjusted life-years (QALYs). Results The selected interventions were 2 screening interventions for diabetes and hypertension, and 3 treatment interventions for chronic kidney disease. The calculator demonstrated that all 5 interventions would reduce health inequality. Population screening for diabetes had the greatest impact on reducing health inequality of 8562 QALYs. Among the 3 treatment interventions, intensive blood pressure control had the greatest impact, with a health inequality benefit of 514 QALYs. Conclusions Routine aggregate distributional cost-effectiveness analysis of interventions in Queensland is feasible, once standard cost-effectiveness estimates are available. The calculator for Queensland enables fast, transparent, and replicable analysis of health inequality impacts using minimal data, with visual outputs to explore trade-offs between health outcomes, inequality, and cost-effectiveness.