particularly with the adoption of more, and more complex, technology.
This presents a difficult situation. If scarce resources are allocated to yearly safety and
performance testing, perhaps for mandatory or accreditation reasons, then the repair backlog
may increase to a level where clinical service delivery becomes affected. Also, if the
repair backlog increases, then maintenance activity will reduce, thus compounding the
problem.
In order to operate with limited resources, various techniques have been adopted to justify
reduced safety and performance testing frequencies and to define maintenance
requirements more precisely (Fennigkoh and Smith, 1989; Fennigkoh and Lagerman,
1997; Gullikson, David and Blair, 1997). These techniques have included classifying the
maintenance needs of items or protocols for justifying the extension of safety and performance
testing intervals. These techniques rely either on some measure of device “criticality”
risk analysis or on sound statistical reliability data. Usually, insufficient data are
available for valid statistical analysis, and these techniques then must be based on riskmanagement
techniques. Risk management typically involves developing a “matrix” with
the probability of failure along one axis and the consequence of failure (from minor to
major) along another. Devices can be placed in the matrix according to where they sit on
each axis and ranked, allowing resources to be targeted at the highest risk items (i.e., those
where both the probability and consequence of failure are highest). The rationale behind
any technique adopted should always be documented. (See also Chapter 56.)