Researchers reported that explicit inclusion of disparities in cost-effectiveness analysis, would allow policy makers to identify strategies that would reduce overall cancer risk, reduce disparities between racial ethnic subgroups, and be cost-effective, according to a study published online September 6 in the Journal of the National Cancer Institute.
Disease simulation models can be used to identify effective and cost-effective strategies for reducing overall cancer incidence and mortality, but are sometimes criticized for not considering how the benefits are distributed within the population. Advances in computer-based modeling, together with the availability of better data, allows details to now be included that account for inequalities between different population subgroups.
To provide a framework for how health inequities could be more explicitly considered in model-based cost-effectiveness analysis, Sue J. Goldie, MD, MPH, and Norman Daniels, Ph.D., of the Harvard School of Public Health, devised a typology of cancer disparities among black, white, and Hispanic populations in the United States that differentiated inequalities resulting from different factors, such as access and quality of treatment and prevention. They used this typology to guide an evaluation of different cervical cancer screening and vaccination strategies in which the health and economic outcomes were calculated for the average population, and also for the three racial subgroups separately.
The researchers identified strategies that reduced the overall risk of cervical cancer from 60% to 74.5%, and that improved cancer outcomes in all racial subgroups. However, they also found that the benefits were unequally distributed; for example, while current screening patterns would resulted in a 60% reduction in overall cancer incidence, reductions ranged from 54.8% for Hispanic women to 62.5% for white women.
The researchers found that screening
|Contact: Zack Rathner|
Journal of the National Cancer Institute