Applying early health technology assessment (e-HTA) to inform investment in novel health technologies in the US.

Abstract

Objectives: Evaluate how a foundation-supported fellowship employs early health-technology assessment (eHTA) to guide the development and positioning of emerging health innovations.

Methods: We reviewed all eHTA reports conducted under the Fellowship from 2018 to 2021 (n = 10), extracting technology class, development stage, economic modeling, and recommendations. In 2023, we conducted thirty-minute structured video interviews with developers of each technology (eleven invitees, ten responses). The interview comprised Likert questions on perceived usefulness and intention to update the model in later stages, and six open-ended questions on perceived advantages, implementation barriers, and downstream actions. Likert data were summarized descriptively; open-ended responses were summarized and discussed within the research team until consensus on key themes.

Results: The eHTA subject technologies were four diagnostics, three therapeutics, two predictive algorithms, and one curative device, all preclinical. Analyses used six Markov or decision-tree frameworks, four hybrid models or simulations, and six value-based-pricing scenarios. Five technologies were potentially cost-effective, three conditionally cost-effective, one unlikely to be cost-effective without stronger evidence, and one cost-effective yet unlikely to break even. Eight developers rated eHTA "useful" or "very useful"; three had already leveraged results in grant or investor materials and two planned to do so when more data emerged. Reported barriers included evidence gaps, funding constraints, and misalignment with pharmaceutical partners on codevelopment strategies; two projects were discontinued.

Conclusions: eHTA supplies developers with early economic insight, but its guidance is most reliable when interpreted alongside budget impact, feasibility, regulatory, and adoption considerations.