ArticleInternational journal of technology assessment in health care2025
Recommendations for the use of early cost-effectiveness analysis to inform the health technology development process with an application to cutaneous squamous cell carcinoma.
Article in International journal of technology assessment in health care, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
objectivesCost-effectiveness analyses are used to help to inform resource-allocation decision-making in healthcare systems. The manufacturers of new health technologies may choose to employ "early cost-effectiveness analysis" (eCEA) to inform the technology development process in anticipation of a value-based assessment if and when the technology is launched. We aim to provide guidance on how eCEA can effectively inform health technology development processes, presenting novel methodological approaches to address key decision-making questions.
methodsWe present three core health technology development questions that eCEAs can address, as well as recommendations for deriving and presenting insights from eCEA models. A hypothetical treatment for cutaneous squamous cell carcinoma (CSCC) called "dummymab" demonstrates the analytic techniques and presentation formats.
resultsWe provide guidance for addressing: 1. What is a health technology's value-based price (VBP) under a range of scenarios? 2. To what extent do different attributes of the technology contribute to its value? 3. Regarding what model parameters is further evidence most valuable? A novel net benefit approach for value driver analysis provides more reliable estimates than traditional 'switch-on' methods by avoiding parameter interaction effects. The manufacturer-perspective value-of-information framework enables evidence prioritization aligned with commercial decision-making while maintaining cost-effectiveness principles.
conclusionseCEA can systematically inform technology development through value-based price estimation, value driver identification, and evidence prioritization. Implementing development decision-making based on eCEA insights can foster alignment with value-based principles of HTA-orientated decision-making systems while supporting more efficient resource allocation in technology development.
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