Hadley Stevens Smith, James Buchanan, Ilias Goranitis, Maarten J IJzerman, Tara A Lavelle, Deborah A Marshall, Dean A Regier, Wendy J Ungar, Deirdre Weymann, Sarah Wordsworth, Kathryn A Phillips, Jeroen P Jansen
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This article critically examines the application of DCEA in the context of genomic medicine.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusions: </strong>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.</p>","PeriodicalId":23508,"journal":{"name":"Value in Health","volume":" ","pages":""},"PeriodicalIF":4.9000,"publicationDate":"2025-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Distributional Cost-Effectiveness Analysis in Genomic Medicine: Considerations for Addressing Health Equity.\",\"authors\":\"Hadley Stevens Smith, James Buchanan, Ilias Goranitis, Maarten J IJzerman, Tara A Lavelle, Deborah A Marshall, Dean A Regier, Wendy J Ungar, Deirdre Weymann, Sarah Wordsworth, Kathryn A Phillips, Jeroen P Jansen\",\"doi\":\"10.1016/j.jval.2025.04.2162\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objectives: </strong>Distributional cost-effectiveness analysis (DCEA) supports equitable resource allocation by quantifying equity-efficiency trade-offs. 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This article provides guidance to researchers on the use of DCEA in genomic medicine and other clinical areas with similarly complex considerations around equity.</p>\",\"PeriodicalId\":23508,\"journal\":{\"name\":\"Value in Health\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":4.9000,\"publicationDate\":\"2025-05-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Value in Health\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1016/j.jval.2025.04.2162\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ECONOMICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Value in Health","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1016/j.jval.2025.04.2162","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ECONOMICS","Score":null,"Total":0}
Distributional Cost-Effectiveness Analysis in Genomic Medicine: Considerations for Addressing Health Equity.
Objectives: 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.
Methods: 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.
Results: 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.
Conclusions: 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.
期刊介绍:
Value in Health contains original research articles for pharmacoeconomics, health economics, and outcomes research (clinical, economic, and patient-reported outcomes/preference-based research), as well as conceptual and health policy articles that provide valuable information for health care decision-makers as well as the research community. As the official journal of ISPOR, Value in Health provides a forum for researchers, as well as health care decision-makers to translate outcomes research into health care decisions.