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Using Cost-Effectiveness Analysis to Quantify the Value of Genomic-Based Diagnostic Tests: Recommendations for
Eldon Spackman1, Sebastian Hinde2, Laura Bojke2
11 Community Health Sciences, University of Calgary , Canada .
Genetic Testing and Molecular Biomarkers
|October 14, 2017
Summary
Cost-effectiveness analysis (CEA) provides a framework for evaluating genomic tests. Recommendations address challenges like multi-disorder diagnosis and intergenerational data, guiding future research and clinical integration of genomic medicine.
Area of Science:
- Genomic medicine
- Health economics
- Clinical diagnostics
Background:
- Advancements in sequencing technologies are increasing the clinical use of genomic tests.
- Genomic tests impact healthcare budgets and patient outcomes.
- Standardized methods for evaluating these tests are needed.
Purpose of the Study:
- To provide recommendations on using cost-effectiveness analysis (CEA) for genomic tests.
- To quantify the costs and benefits associated with genomic testing.
- To guide the integration of genomic tests into clinical practice.
Main Methods:
- Systematic literature search on CEA for genomic tests.
- Extraction of key concepts to identify challenges and solutions.
- Categorization of evaluation features into practical recommendations.
Main Results:
- Genomic tests present unique challenges for CEA, including diagnosing multiple disorders.
- The potential for long-term, intergenerational consequences requires consideration of infinite time horizons.
- Non-health benefits may need to be incorporated into analyses.
Conclusions:
- Cost-effectiveness analysis (CEA) is suitable for evaluating genomic tests but requires methodological adaptation.
- Further research is recommended on sharing genomic information across generations.
- Evaluation frameworks should encompass multi-disorder genomic tests and both health and non-health benefits.
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