Problem-driven innovation models for emerging technologies
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ORIGINAL PAPER
Problem-driven innovation models for emerging technologies Graphical representation of need-led innovation methodologies in healthcare Erfan Soliman1 · Daniel Mogefors1 · Jeroen H. M. Bergmann1 Received: 1 May 2020 / Accepted: 11 June 2020 © The Author(s) 2020
Abstract As a fundamentally resource-intensive endeavour, healthcare innovation can benefit from a problem-based approach. This kind of methodology needs to define the problem by applying a range of well-established techniques, such as ethnographic research, market analysis, and stakeholder exploration. However, no in-depth investigation has taken place on how these techniques interact and relate to one another. As such, an overarching methodology is needed in order to represent, critically assess, and evolve problem-driven, or need-led, innovation approaches. Graph theory provides a useful way by which this can be done. This paper exemplifies how different elements of a problem-first approach to innovation can be graphically represented within a system, in order to provide insights into the processes that support real-world impact for new technologies. By providing a more refined description of the need-led innovation methodology, it is hoped that these models can drive a more evidence-based and empirical mindset within the field to ultimately drive valuable innovations with increased efficiency. Keywords Innovation · Graph theory · Emerging technologies · System performance · Medical devices
1 Introduction Bringing technological innovations into the market within healthcare can be resource-intensive, due to regulatory requirements and the relatively high upfront costs of research and development [1, 2]. This is further complicated by the complexity of rule interpertation that emerges during the regulatory process [3]. Nonetheless, there is high demand for continued innovation, and the spread of new technologies remains relatively unrestrained in many countries [4]. Advanced emerging technologies, such as three-dimensional bioprinting, which can be used to print large tissue structures, auto-injection devices, which can eliminate the use of needles, or new kind of prosthetics are already reaching a stage of preclinical and clinical research [5,6,19]. These new technologies can impact a Jeroen H. M. Bergmann
[email protected] 1
Natural Interaction Lab, Oxford Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Old Road Campus Research Building, OX3 7DQ, Oxford, UK
range of healthcare problems, and it will be their ‘market pull’, as well as the regulations around them, that are likely to be the key factors defining their potential success going forward [7, 8]. Understanding which problems or needs these technologies address is therefore important for the research community, especially from a perspective of resource efficiency. Methodologies that can reduce the risk connected to healthcare innovation provide value for those interested in creating impact that is economically sustainable.
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