the downtime or turnaround time [Wang et al., 2012]. This explains why downtime is onl y adopted
for major pieces of equipment (e.g., MRI, linear accelerator, CT, automated laboratory chemistry
analyzer, etc.) for which time logging is part of the user routine due to high demand.
For the rest of medical equipment, the more practical approach is to use failure rate as the
primary reliability measure
. While failure rate can be measured for individual pieces of equipment,
it is not practical to deal with it when there are over 5-10,000 pieces of equipment in a hospital
On the other extreme, a single failure rate for all medical equipment (termed “global failure rate
by Wang et al. [2006b]) could be too ambiguous for any decision. Therefore, it is recommended
to start measuring failure rates for the main categories of equipment (i.e., biomedical, imaging,
oncology, and clinical laboratory) and then drill down from there to specific groups by function
(e.g., diagnostic, monitoring, therapeutic, etc.), purpose (e.g., resuscitation, physical therapy, surgery,
intensive care, etc.), and finally down to the brand and model level. At higher levels, accuracy is
sacrificed due to the large variability that is included in the group but less time is needed to acquire
enough measurements for statistical analy ses. As one drills down, the accuracy increases but more
time is needed for data collection. As a rule of thumb, it is best to start at a fairly high level and dive
into smaller groups when there is a need or desire to understand better the underlying causes and
opportunities for improvement.
Table 5.1 shows results of analyses of data collected from hundreds of hospitals that can be
used as a reference for evaluating individual CE departments’ maintenance effectiveness [Wang et al.,
2006b, 2008, 2011].
While the maintenance effectiveness discussed above provides a way to measure the outcome of the
CE Department, it does not measure how efficiently the resources are used to achieve the desired
outcomes. Like any other enterprise, the CE Department has to be both effective and efficient in
order to be of value for the healthcare organization it supports or, to put it more bluntly, to survive
and thrive.
There are two basic ways to measure CE efficiency. The first one is to use the overall cost of
maintaining all the medical equipment within the healthcare organization as a way to determine
how efficiently the financial resources are being used to keep the inventory safe and reliable. The
second is to use the amount of full-time equivalent (FTE) staff deployed by the CE Department as
a way to determine labor productivity. These two measures are discussed below.
One precaution that is needed is to isolate failures that are tr uly due to equipment and not those caused by use errors (also known
as “cannot duplicate”), peripherals, and network issues (see Section 3.4.3 above).
On the other hand, individual failure r ates can be useful for determine the need for equipment replacement, as equipment that
fails often may be reaching its useful life or there are other failure causes that need attention.

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