Frameworks for Health Technology Assessment at an Early Stage of Product Development: A Review and Roadmap to Guide Applications.

OBJECTIVES: Early health technology assessment (eHTA) can be used to evaluate and optimize a medical product's value proposition and to inform go/no-go decisions by using health economic modeling, literature scanning, and stakeholder preference studies at an early stage of development. eHTA frameworks offer high-level guidance on conducting this complex, iterative, and multidisciplinary process. The objective of this study was to review and summarize existing eHTA frameworks, understood as systematic approaches to guide early evidence generation and decision making. METHODS: Using a rapid review methodology, we identified all relevant studies published in English, French, and Spanish from PubMed/MEDLINE and Embase until February 2022. We only included frameworks relevant to the preclinical and early clinical (phase I) stages of medical product development. RESULTS: From 737 reviewed abstracts, 53 publications describing 46 frameworks were selected for inclusion and classified into categories based on their scope: (1) criteria frameworks, which provide an overview of eHTA; (2) process frameworks, which offer stepwise guidance for conducting eHTA, including preferred methods; and (3) methods frameworks, which provide detailed descriptions of specific eHTA methods. Most of the frameworks did not specify their target users or the specific stage of technology development. CONCLUSIONS: Despite some variability and gaps found across existing frameworks, the structure provided by this review helps inform eHTA applications. Remaining challenges are the frameworks' limited accessibility to users without a background in health economics, poor distinctions being made among early lifecycle stages and technology types, and the inconsistent terminology used to describe eHTA in different contexts.

A Rapid Review on the Value of Biobanks Containing Genetic Information.

OBJECTIVES: Increasing access to health data through biobanks containing genetic information has the potential to expand the knowledge base and thereby improve screening, diagnosis, and treatment options for many diseases. Nevertheless, although privacy concerns and risks surrounding genetic data sharing are well documented, direct evidence in favor of the hypothesized benefits of data integration is scarce, which complicates decision making in this area. Therefore, the objective of this study is to summarize the available evidence on the research and clinical impacts of biobanks containing genetic information, so as to better understand how to quantify the value of expanding genomic data access. METHODS: Using a rapid review methodology, we performed a search of MEDLINE/PubMed and Embase databases; and websites of biobanks and genomic initiatives published from 2010 to 2022. We classified findings into 11 indicators including outputs (a direct product of the biobank activities) and outcomes (changes in scientific and clinical capacity). RESULTS: Of 8479 abstracts and 101 gray literature sources were reviewed, 96 records were included. Although most records did not report key indicators systematically, the available evidence concentrated on research indicators such as publications and gene-disorder association discoveries (63% of studies), followed by research infrastructure (26%), and clinical indicators (11%) such as supporting the diagnosis of individual patients. CONCLUSIONS: Existing evidence on the benefits of biobanks is skewed toward easily quantifiable research outputs. Measuring a comprehensive set of outputs and outcomes inspired by value frameworks is necessary to generate better evidence on the benefits of genomic data sharing.