From Fragmentation to Standardization: A Systematic Review Update and Critical Appraisal of Genetic and Genomic Testing Assessment Frameworks and Their Alignment With the HTA Core Model
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Updated: Oct 31, 2026

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Valentina Baccolini1,2, Antonio Sciurti1,3, Erica Pitini4
1Department of Public Health and Infectious Diseases Sapienza University of Rome Rome Italy.
Background And Aims:
Owing to their distinct features, genetic/genomic technologies have traditionally been assessed using tailored approaches, with no standardized methodology emerging to date. The Health Technology Assessment (HTA) Core Model (version 3.0), adopted within the European Union HTA Regulation, is a rigorous framework for health technology assessment, but its suitability for genetic/genomic testing remains unclear. This study examined whether the Model could serve as a standardized framework for the evaluation of genetic/genomic applications.
Methods:
A search was conducted to identify evaluation frameworks for genetic/genomic applications (PROSPERO CRD42023429403), and a critical analysis was performed. The methodological characteristics of the identified frameworks, including their assessment domains and components, were systematically compared to the domains and issues of the HTA Core Model. Findings were synthesized narratively.
Results:
Overall, 24 evaluation frameworks for genetic/genomic testing were analysed: half were based on the ACCE model, four on the HTA approach, one combined both methodologies, and seven were heterogeneous in structure. Only one framework covered all relevant assessment aspects but lacked validation. Conversely, the HTA Core Model captured all core questions and addressed every identified assessment component, although with varying degrees of coverage (Cohen's κ between researchers: 0.71, 95% CI: 0.59-0.82).
Conclusion:
Existing frameworks for genetic/genomic technologies are fragmented and mostly incomplete. As the HTA Core Model encompasses all relevant components of these technologies, it may offer a suitable basis for standardizing their evaluation process. Future research could integrate it with a few genomic-specific items to maximize its exhaustiveness.
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