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There is a need for formal cost-effectiveness evidence to better model the real-world payer decision context in which general economic models are currently being used, specifically regarding clinical genomics health services (for next-generation sequencing (NGS) tests). We reviewed literature focused on cost-effectiveness studies after completion of the Human Genome Project within the Tufts Cost-Effectiveness Analysis (CEA) Registry and found that only 33% of eligible studies were conducted from the U.S. payer perspective. Additional interpretation challenges include economic models that do not account for true payer-negotiated costs, limits in internal expertise for quality-adjusted life-year inferences, and limited internal policies to use CEA research in decision making. This Viewpoints article highlights numerous opportunities to increase the translational effect of economic modeling work. Specifically, geographically relevant cost and outcomes data should be considered for integration within best practices for economic evaluations of NGS tests. Such data integration may provide more informed decision making regarding the allocation of constrained resources for health care services and technology. DISCLOSURES: No outside funding supported the writing of this article. Hart is supported by an unrestricted gift from Pfizer, which played no role in the study referred to in this article. The authors have no conflicts of interest to report.

Consideration for Employer-Based and Geographic Attributes Included in Value Assessment Methods of Next-Generation Sequencing Tests