Plain Language Summary

This research can be used to improve health equity in genomic medicine. Genomic medicine, which includes advanced genetic testing and treatments, has the potential to enhance healthcare by offering personalized medical solutions. However, it also risks worsening health disparities because certain groups may benefit more due to differences in access to specialized care and research participation.

Distributional cost-effectiveness analysis is a method that helps balance the trade-offs between efficiency and equity when allocating healthcare resources. It enables policy makers to evaluate how different genomic interventions might affect various social groups, ensuring that these decisions are more equitable. The article emphasizes the importance of considering social factors alongside biological ones to advance health equity in genomic medicine.

Current challenges in genomic medicine include disparities in access and outcomes, which are influenced by the healthcare system, research designs, and data collection practices. To achieve health equity, it is important to provide fair and unbiased access to genomic services and to ensure data are collected on all who may be affected. Yet, policy makers often struggle with deciding whether to prioritize equal access over maximizing overall population health, which can lead to unequal health outcomes.

The article suggests several steps to enhance the relevance of distributional cost-effectiveness analysis in genomic medicine. These include empowering underrepresented populations in genomics research, collecting data to accurately assess variations in genomic medicine outcomes across different groups, and considering nonhealth outcomes that are significant to patients and families. Additionally, it calls for improved diversity in genomics research and workforce to ensure equitable representation and understanding of genetic diversity.

For policy makers and healthcare decision makers, the article provides guidance on using distributional cost-effectiveness analysis in genomic medicine to make informed decisions that promote health equity. By incorporating distributional cost-effectiveness analysis into health technology assessment processes, stakeholders can better address the equity implications of resource allocation decisions.

In conclusion, distributional cost-effectiveness analysis offers a promising approach to explicitly quantify the health equity impacts of genomic medicine interventions. While challenges remain, such as data collection and methodological advancements, applying distributional cost-effectiveness analysis can lead to more transparent discussions and decisions that prioritize equitable healthcare outcomes for all social groups.

^{Note: This content was created with assistance from artificial intelligence (AI) and has been reviewed and edited by ISPOR staff. For more information or for inquiries on ISPOR’s AI policy, click here or contact us at info@ispor.org.}