Profiling of medical equipment risk using fuzzy logic

D. Clarkson, Olivier C.L. Haas, Keith Burnham

Research output: Chapter in Book/Report/Conference proceedingChapter

170 Downloads (Pure)

Abstract

Models of risk generally struggle to cope with the complexities of healthcare, and in the context of medical equipment, it is apparent that several categories of ‘risk’ can be identified which are active concurrently. From previous development of a clinical risk simulation model within a Critical Care environment, a specific implementation of fuzzy logic was found to provide a means of developing a ‘risk engine’ which referenced contributing factors and preventative factors of risk in the clinical environment. Components of this ‘risk engine’ model have been applied to the task of classification of risk associated with medical equipment. This in turn allows priorities to be identified in relation to management of a diverse equipment portfolio.
Original languageEnglish
Title of host publicationIPEM Report 110: Quality in Clinical Engineering
PublisherInstitute of Physics and Engineering in Medicine
Pages99-117
ISBN (Print)9781903613580
Publication statusPublished - 2015

Bibliographical note

This chapter is reproduced with permission of the publisher Institute of Physics and Engineering in Medicine From report 110: Quality in Clinical Engineering, ISBN 978 1 903613 58 0. The report is available to non-members of IPEM at £50.00 from http://www.ipem.ac.uk/Publications/IPEMReportSeries/AvailablePublications.aspx .

Keywords

  • risk management
  • medical devices
  • patient safety
  • fuzzy logic

Fingerprint Dive into the research topics of 'Profiling of medical equipment risk using fuzzy logic'. Together they form a unique fingerprint.

  • Cite this

    Clarkson, D., Haas, O. C. L., & Burnham, K. (2015). Profiling of medical equipment risk using fuzzy logic. In IPEM Report 110: Quality in Clinical Engineering (pp. 99-117). Institute of Physics and Engineering in Medicine.