Why equal treatment is not always equitable: the impact of existing ethnic health inequalities in cost-effectiveness modeling
AuthorMcLeod, M; Blakely, T; Kvizhinadze, G; Harris, R
Source TitlePopulation Health Metrics
University of Melbourne Author/sBlakely, Antony
AffiliationMelbourne School of Population and Global Health
Document TypeJournal Article
CitationsMcLeod, M., Blakely, T., Kvizhinadze, G. & Harris, R. (2014). Why equal treatment is not always equitable: the impact of existing ethnic health inequalities in cost-effectiveness modeling. POPULATION HEALTH METRICS, 12 (1), https://doi.org/10.1186/1478-7954-12-15.
Access StatusOpen Access
BACKGROUND: A critical first step toward incorporating equity into cost-effectiveness analyses is to appropriately model interventions by population subgroups. In this paper we use a standardized treatment intervention to examine the impact of using ethnic-specific (Māori and non-Māori) data in cost-utility analyses for three cancers. METHODS: We estimate gains in health-adjusted life years (HALYs) for a simple intervention (20% reduction in excess cancer mortality) for lung, female breast, and colon cancers, using Markov modeling. Base models include ethnic-specific cancer incidence with other parameters either turned off or set to non-Māori levels for both groups. Subsequent models add ethnic-specific cancer survival, morbidity, and life expectancy. Costs include intervention and downstream health system costs. RESULTS: For the three cancers, including existing inequalities in background parameters (population mortality and comorbidities) for Māori attributes less value to a year of life saved compared to non-Māori and lowers the relative health gains for Māori. In contrast, ethnic inequalities in cancer parameters have less predictable effects. Despite Māori having higher excess mortality from all three cancers, modeled health gains for Māori were less from the lung cancer intervention than for non-Māori but higher for the breast and colon interventions. CONCLUSIONS: Cost-effectiveness modeling is a useful tool in the prioritization of health services. But there are important (and sometimes counterintuitive) implications of including ethnic-specific background and disease parameters. In order to avoid perpetuating existing ethnic inequalities in health, such analyses should be undertaken with care.
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