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TAXONOMY OF MEDICAL DEVICES IN THE LOGIC OF HEALTH TECHNOLOGY ASSESSMENT

Published online by Cambridge University Press:  29 December 2015

Cornelia Henschke
Affiliation:
Department of Health Care Management, Technische Universität Berlincornelia.henschke.1@tu-berlin.de
Dimitra Panteli
Affiliation:
Department of Health Care Management, Technische Universität Berlin
Matthias Perleth
Affiliation:
Medical Consultancy Department, Federal Joint Committee
Reinhard Busse
Affiliation:
Department of Health Care Management, Technische Universität Berlin

Abstract

Objectives: The suitability of general HTA methodology for medical devices is gaining interest as a topic of scientific discourse. Given the broad range of medical devices, there might be differences between groups of devices that impact both the necessity and the methods of their assessment. Our aim is to develop a taxonomy that provides researchers and policy makers with an orientation tool on how to approach the assessment of different types of medical devices.

Methods: Several classifications for medical devices based on varying rationales for different regulatory and reporting purposes were analyzed in detail to develop a comprehensive taxonomic model.

Results: The taxonomy is based on relevant aspects of existing classification schemes incorporating elements of risk and functionality. Its 9 × 6 matrix distinguishes between the diagnostic or therapeutic nature of devices and considers whether the medical device is directly used by patients, constitutes part of a specific procedure, or can be used for a variety of procedures. We considered the relevance of different device categories in regard to HTA to be considerably variable, ranging from high to low.

Conclusions: Existing medical device classifications cannot be used for HTA as they are based on different underlying logics. The developed taxonomy combines different device classification schemes used for different purposes. It aims at providing decision makers with a tool enabling them to consider device characteristics in detail across more than one dimension. The placement of device groups in the matrix can provide decision support on the necessity of conducting a full HTA.

Type
Methods
Copyright
Copyright © Cambridge University Press 2015 

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