ASSESSING THE EXPECTED VALUE OF RESEARCH STUDIES IN REDUCING UNCERTAINTY AND IMPROVING IMPLEMENTATION DYNAMICS

Purpose: With low implementation of cost-effective health technologies being a problem in many health systems, it may be worth considering the potential effects of research on implementation at the time of technology appraisal. Meaningful and realistic implementation estimates must be of dynamic nature. The objective was to extend existing methods for assessing the value of research studies in terms of both reduction of uncertainty and improvement in implementation by considering the dynamic nature of implementation.

Method(s): We use expected value of sample information and expected value of specific implementation measure concepts accounting for the effects of specific research studies on implementation dynamics and the reduction of uncertainty. Implementation dynamics are informed by diffusion theory and an elicitation of expert beliefs about the shape of diffusion curves. We illustrate the use of the resulting dynamic expected value of research analysis in a genuine pre-term birth screening technology and results are compared with those from a static analysis.

Result(s): Allowing for the dynamics of implementation had a significant impact on the expected value of research in the case study, suggesting that mistakes are made where assumptions of static implementation levels are made. Incorporating the effects of research on implementation resulted in an increase in the expected value of research compared to expected value of sample information alone. 

Conclusion(s): Assessing the expected value of research in reducing uncertainty and improving implementation dynamics has the potential to complement currently used analyses in health technology assessments, especially in recommendations for further research. The combination of expected value of research, diffusion theory and elicitation described in this paper is an important addition to the existing methods of health technology assessment.