OBJECTIVES: Assessing the potential value of medical devices under development is necessary to guide further research and investment decisions, yet such assessments remain challenging.This study illustrates the utility of a mixed methods approach including qualitative methods, decision-analytic modelling, and risk-adjusted net present value (rNPV) analysis for exploring the value of an example technology; a biosensor-integrated self-reporting arteriovenous graft (subsequently referred to as smart AVG). Currently in preclinical development, the device will use impedance spectroscopy to detect graft stenosis (surveillance use case) and electrically induce apoptosis to treat stenosis (interventional use case). Both functions have been demonstrated in-vitro but the value proposition is yet to be established.

METHODS: This study comprised: a qualitative stakeholder engagement exploring the value of the smart AVG through semi-structured interviews with clinical experts; a cost-effectiveness analysis conducted from a US Medicare perspective; and an investment model estimating rNPVs to determine commercial viability. These stages were interconnected with findings from one stage informing the subsequent stage.

RESULTS: The stakeholder engagement suggested that it would be difficult to establish the current value of the surveillance use case due to the lack of well-established interventions for preclinical stenosis. Based on this, the cost-effectiveness analysis focused on the interventional use case and estimated threshold prices at assumed levels of effectiveness. Using these prices, rNPVs were estimated in the final stage. From the analyses, for a smart AVG to be deemed cost-effective and commercially viable, an effectiveness level of at least 41% (in graft failure reduction) and a unit price of $14,749 were required.

CONCLUSIONS: This multi-stage approach expansively assesses the value of a new technology by identifying the combination of conditions (such as clinical study success, potential market size and product penetration, and assumptions associated with cost-effectiveness modelling and reimbursement) under which investment in R&D may be regarded as commercially attractive.