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PROMISE AND PLAUSIBILITY: HEALTH TECHNOLOGY ADOPTION DECISIONS WITH LIMITED EVIDENCE

Published online by Cambridge University Press:  17 August 2016

Bruce Campbell
Affiliation:
Medical Technologies Advisory Committee, National Institute for Health and Care Excellence
Paul Knox
Affiliation:
Medical Technologies Advisory Committee, National Institute for Health and Care Excellence Department of Eye & Vision Science, Institute of Ageing & Chronic Disease, University of Liverpool pcknox@liv.ac.uk
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Abstract

Background: The adoption of new medical devices and diagnostics is often hampered by lack of published evidence which makes conventional health technology assessment (HTA) difficult. We now have 5 years’ experience of the Medical Technologies Advisory Committee of the National Institute for Health and Care Excellence (NICE) in the United Kingdom, addressing this problem. This committee assesses devices and diagnostics against claims of advantage, to produce guidance on adoption for the health service.

Methods: We have reflected on the practical, technical, and intellectual processes we have used in developing guidance for the health service.

Results: When scientific and clinical evidence is sparse, promise and plausibility play an increased part in decision-making. Drivers of promise include a clear design and mechanism of action, the possibility of radical improvement in care and/or resource use, and improving health outcomes for large numbers of patients. Plausibility relates to judgements about the whether the promise is likely to be delivered in a “real world” setting. Promise and plausibility need to be balanced against the amount of evidence available. We examine the influence they may have on decision-making compared with other factors such as risk and cost.

Conclusions: Decisions about adoption of new devices and diagnostics with little evidence are influenced by judgements of their promise and the plausibility of claims that they will provide benefits in a real-world setting. This kind of decision making needs to be transparent and this article explains how these influences can be balanced against the use of more familiar criteria.

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Copyright © Cambridge University Press 2016 
Figure 0

Figure 1. Illustration of the relationship between (a) Promise, (b) Risk, and (c) Cost and the level of evidence (“Evidence”) likely to be required to support the adoption of a medical device or technology. Note that the orientation of the relationship for promise (a) is opposite that of both risk and cost (b,c). (d) Cost and risk are combined and plotted against promise because, in reality, these three factors influence each other in determining the level of evidence likely to be required to show that a given technology or device should be adopted for use. Thus, a high promise/low cost/low risk device is likely to require less evidence for adoption than a low promise/high cost/high risk one.