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Applied Health Economics and Health Policy

, Volume 14, Issue 6, pp 623–634 | Cite as

Review of Economic Submissions to NICE Medical Technologies Evaluation Programme

  • Abualbishr AlshreefEmail author
  • Michelle Jenks
  • William Green
  • Simon Dixon
Review Article

Abstract

The economic evaluation of medical devices is increasingly used to inform decision making on adopting new or novel technologies; however, challenges are inevitable due to the unique characteristics of devices. Cost-consequence analyses are recommended and employed by the English National Institute for Health and Care Excellence (NICE) Medical Technologies Evaluation Programme (MTEP) to help address these challenges. The aim of this work was to review the critiques raised for previous MTEP submissions and explore if there were common problems across submissions. We reviewed a sample of 12 economic submissions to MTEP representing 50 % of 24 sets of guidance issued to July 2015. For each submission, we reviewed the External Assessment Centre’s (EAC) report and the guidance document produced by NICE. We identified the main problems raised by the EAC’s assessments and the committee’s considerations for each submission, and explored strategies for improvement. We found that the identification and measurement of costs and consequences are the main shortcomings within economic submissions to MTEP. Together, these shortcomings accounted for 42 % of criticisms by the EACs among the reviewed submissions. In certain circumstances problems with these shortcomings may be unavoidable, for example, if there is a limited evidence base for the device being appraised. Nevertheless, strategies can often be adopted to improve submissions, including the use of more appropriate time horizons, whilst cost and resource use information should be taken, where possible, from nationally representative sources.

Keywords

National Health Service Medical Device External Assessment Centre Medical Technology Advisory Committee Evidence Identification 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Author contributions

The manuscript was prepared by AA, MJ, WG and SD and the review of the EAC reports and guidance documents was undertaken by AA, MJ and WG with advice from SD. AA, MJ and SD were involved in conceptualisation and design of the work.

Compliance with Ethical Standards

Funding

This work was funded by Yorkshire and Humber Academic Health Sciences Network (YHAHSN), though the views expressed in this article are the authors’ own views.

Potential conflict of interest

Two of the authors (MJ and WG) are employees of York Health Economics Consortium (YHEC). The YHEC is funded by NICE to act as an External Assessment Centre for the Medical Technologies Evaluation Programme. This work was not funded by NICE. All other authors (AA and SD) declared no conflict of interest.

Supplementary material

40258_2016_262_MOESM1_ESM.docx (38 kb)
Supplementary material 1 (DOCX 38 kb)

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Health Economics and Decision Science, School of Health and Related ResearchUniversity of SheffieldSheffieldUK
  2. 2.York Health Economics ConsortiumUniversity of YorkYorkUK

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