Abstract
The market success of a medical product depends on its commercial viability, yet this may be hard to predict during the development process of medical devices. This paper aims to determine if applying the Headroom method combined with return on investment (ROI) analysis allows for estimation of the potential commercial viability of one therapeutic and five diagnostic devices. The devices were targeted at different disease areas. Information regarding the maximum additional health benefit that could be obtained with the new device, the estimated production price and expected sales volume was gathered from literature and expert opinions. A willingness-to-pay threshold for one additional Quality-Adjusted Life Years of €30,000 was assumed for Headroom calculation. The analysis showed that the device with the highest estimated headroom per unit was RAPAI: a computed tomography photo-acoustic instrument for imaging inter-phalangeal joints (€1,645,120), followed by CBPM: continuous blood pressure measurement device (€922,440), Home Brain Monitoring (HBM) device (€750,000), a portable point-of-care (POC-CKD) device (€36,250), and the IHP: injectable healing plasters (€22,100). The devices with the highest estimated ROI were RAPAI (€14,951,200), and POC-CKD (€14,100,000), followed by HBM (€9,450,000), CBPM (€8,624,400), and IHP (€7,050,000). Overall, RAPAI is expected to have the highest potential commercial viability and HBM and IHP the lowest. The presented combined method is feasible, useful, and informative to help assess the potential commercial viability of medical devices under development. It might be an answer to the growing need of performing value-based pricing of devices replacing currently dominating cost-plus pricing approach.
Original language | English |
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Pages (from-to) | 338-346 |
Number of pages | 9 |
Journal | Technological Forecasting and Social Change |
Volume | 112 |
DOIs | |
Publication status | Published - Nov 2016 |
Externally published | Yes |
Bibliographical note
Funding Information:This research was committed under a grant assigned by Province Overijssel and EU for NIRION Project within GO EFRO 2007–2013, and within High Tech Health Farm Program granted by Overijsselse Centra voor Research & Innovatie.
Publisher Copyright:
© 2016 Elsevier Inc.