Using Cost-Effectiveness Analysis to Quantify the Value of Genomic-Based Diagnostic Tests: Recommendations for Practice and Research

Genet Test Mol Biomarkers. 2017 Dec;21(12):705-716. doi: 10.1089/gtmb.2017.0105. Epub 2017 Oct 13.

Abstract

Aims: New sequencing technologies allow increased opportunities to use genomic-based diagnostic tests (genomic tests) in routine clinical practice, which will impact healthcare budgets and patients' outcomes. This article aims to generate a list of recommendations on how the principles and methods of cost-effectiveness analysis (CEA) can be used to quantify the costs and benefits of genomic tests.

Methods: A systematic literature search identified publications describing the use of CEA to evaluate genomic tests. Data were extracted as key concepts to produce a thematic list of previously described challenges and solutions to using CEA to evaluate genomic tests. Defining features of evaluating genomic tests were categorized into a list of key recommendations for applying methods in practice and for research needs.

Results: Features producing challenges in the implementation of CEA to evaluate genomic tests were as follows: the ability of the tests to diagnose multiple disorders; potential consequences for future generations suggesting an infinite time horizon; and the potential need to consider nonhealth benefits.

Conclusions: CEA was identified as an appropriate evaluative framework for genomic tests, although standard methods may need modification and important method research questions remain. Key recommendations suggest a need for research to reflect: sharing genomic information across generations; genomic tests for multiple disorders; and health and nonhealth benefits.

Keywords: cost-effectiveness analysis; genomic testing; health economics; methods.

Publication types

  • Review

MeSH terms

  • Cost-Benefit Analysis / methods*
  • Diagnostic Tests, Routine
  • Evidence-Based Medicine
  • Genetic Testing / statistics & numerical data*
  • Genomics
  • High-Throughput Nucleotide Sequencing / methods
  • Humans