Developments in next-generation sequencing technologies have driven the clinical application of diagnostic tests that interrogate the whole genome, which offer the chance to diagnose rare inherited diseases or inform the targeting of therapies. New genomic diagnostic tests compete with traditional approaches to diagnosis, including the genetic testing of single genes and other clinical strategies, for finite health-care budgets. In this context, decision analytic model-based cost-effectiveness analysis is a useful method to help evaluate the costs versus consequences of introducing new health-care interventions. This Perspective presents key methodological, technical, practical and organizational challenges that must be considered by decision-makers responsible for the allocation of health-care resources to obtain robust and timely information about the relative cost-effectiveness of the increasing numbers of emerging genomic tests.

下一代测序技术的发展推动了询问整个基因组的诊断测试的临床应用，这提供了诊断罕见遗传性疾病或告知治疗目标的机会。新的基因组诊断测试与传统的诊断方法（包括单基因的基因测试和其他临床策略）竞争，以争取有限的医疗保健预算。在这种情况下，基于决策分析模型的成本效益分析是一种有用的方法，可以帮助评估引入新的医疗保健干预措施的成本与后果。本视角提出了关键的方法论、技术、实践和组织挑战，负责分配卫生保健资源的决策者必须考虑这些挑战，以获得有关日益增多的新兴基因组测试的相对成本效益的可靠而及时的信息。