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
