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Assessing the expected value of research resolving uncertainty and improving implementation

Abstract

Background: With low implementation of cost-effective health technologies being a problem in many health systems, it may be worth considering the potential effect of research on implementation at the time of technology appraisal. Objective: To demonstrate methods for assessing the value of research in terms of both reduction of uncertainty and improvement in implementation, considering the dynamic nature of implementation. Methods: We extend an existing framework to assess the values of information and implementation to account for the relationship between information and implementation and to reflect implementation dynamics. The resulting framework is applied to a genuine technology in the area of pre-term birth screening and results obtained from static and dynamic analyses are compared. The data to inform the effect of research evidence on implementation dynamics was obtained through a previous elicitation of expert opinion on quantities that informed the parameterisation of a dynamic implementation curve based on diffusion theory. Results: Incorporating the relationship between information and implementation in the assessment of research led to an expected value of research much larger than the one based on reduction of uncertainty alone in the exemplar case study. Considering the dynamics of implementation makes a significant difference to the expected value of research and accounting for the time when research reports may do so as well, both making existing analyses more realistic. However, such analyses require additional data and therefore resources. Conclusions: Assessing the expected value of research in terms of both, the reduction in uncertainty and improvements in implementation dynamics, has the potential to complement currently used analyses in health technology assessments, especially in Recommendation with Research decision

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