Smith Hadley Stevens, Buchanan James, Goranitis Ilias, IJzerman Maarten J, Lavelle Tara A, Marshall Deborah A, Regier Dean A, Ungar Wendy J, Weymann Deirdre, Wordsworth Sarah, Phillips Kathryn A, Jansen Jeroen P
Department of Population Medicine, Harvard Medical School, Boston, MA, USA; Center for Bioethics, Harvard Medical School, Boston, MA, USA.
Health Economics and Policy Research Unit, Center for Evaluation and Methods, Wolfson Institute of Population Health, Queen Mary University of London, London, England, UK; National Institute for Health Research, Barts Biomedical Research Center, Queen Mary University of London, London, England, UK.
Value Health. 2025 May 6. doi: 10.1016/j.jval.2025.04.2162.
Distributional cost-effectiveness analysis (DCEA) supports equitable resource allocation by quantifying equity-efficiency trade-offs. DCEA may be particularly useful to understand equity impacts in the context of genomic medicine, a rapidly growing clinical area that has prompted concerns about its potential to exacerbate health inequities by differentially benefitting some population groups over others because of disparities in research inclusion and access to specialty care. This article critically examines the application of DCEA in the context of genomic medicine.
We articulate steps for distributional impact assessment in the context of genomic medicine by adapting an existing conceptual framework for understanding the causal pathway between a healthcare intervention and the distribution of costs and effects among social groups, the inequality staircase. We discuss related data equity considerations and evidence requirements specific to genomic medicine interventions.
The need for and receipt of a genomic medicine intervention, as well as an intervention's short-term and long-term effects, may vary across equity-relevant subgroups. Research to enhance the relevance of DCEA in genomic medicine should avoid conflation of biological and social factors, empower populations that are underrepresented in genomics research, accurately assess variation in outcomes across equity-relevant subgroups, and develop methods for incorporation of nonhealth outcomes within a DCEA framework.
Best practice-aligned applications of DCEA may facilitate transparent discussions of health equity in coverage and implementation decisions. This article provides guidance to researchers on the use of DCEA in genomic medicine and other clinical areas with similarly complex considerations around equity.
分布成本效益分析(DCEA)通过量化公平与效率之间的权衡来支持公平的资源分配。在基因组医学背景下,DCEA可能特别有助于理解公平影响。基因组医学是一个快速发展的临床领域,由于研究纳入和获得专科护理方面的差异,可能会使某些人群比其他人群受益更多,从而加剧健康不平等,这引发了人们对其可能性的担忧。本文批判性地审视了DCEA在基因组医学背景下的应用。
我们通过调整现有的概念框架来阐述基因组医学背景下分布影响评估的步骤,该框架用于理解医疗保健干预与社会群体之间成本和效果分配的因果途径,即不平等阶梯。我们讨论了基因组医学干预特有的相关数据公平考虑因素和证据要求。
基因组医学干预的需求和接受情况,以及干预的短期和长期效果,在与公平相关的亚组中可能会有所不同。加强DCEA在基因组医学中相关性的研究应避免混淆生物和社会因素,增强基因组学研究中代表性不足人群的权能,准确评估与公平相关亚组间结果的差异,并开发在DCEA框架内纳入非健康结果的方法。
与最佳实践一致的DCEA应用可能有助于在覆盖范围和实施决策中就健康公平进行透明的讨论。本文为研究人员在基因组医学以及其他在公平性方面有类似复杂考量的临床领域中使用DCEA提供了指导。