Binseng Wang, ScD, CCE, FAIMBE, FACCE

Binseng Wang, ScD, CCE, FAIMBE, FACCE

Brian Poplin, DHA, FACHE, CBET

Brian Poplin, DHA, FACHE, CBET

The Joint Commission has officially confirmed that the Centers for Medicare and Medicaid Services has agreed to accept alternatives to manufacturers’ maintenance recommendations. So clinical engineering (CE) professionals are now reassured that they can continue to use the “risk-based criteria” for maintenance planning. However, one important detail that has not been discussed thoroughly is whether we are using risk or, more accurately, severity in our planning.

Most dictionaries define risk as “the possibility of loss or injury,” implying that it is something that is not certain to but could happen. A definition relevant to clinical engineering is offered by the International Organization for Standardization and the International Electrotechnical Commission. They define risk as “[t]he combination of the probability of occurrence of harm and the severity of that harm.” To better appreciate this definition, let us examine two types of accidents: commercial airline and automobile. The severity of airline accidents is much higher than that of automobile accidents, considering casualties and property losses. However, the probability of the former is much lower than that of the latter due to the stringent controls mandated by government and practiced by industry. Therefore, the risk of someone being harmed by an airline accident is much lower than someone being harmed by an automobile accident.

The Probability of Harm

Analogously, medical equipment offers a wide range of severity, spanning from little or no harm to severe injury or death, as well as very different harm probabilities. The challenge for health care organizations and professionals is essentially to understand and reduce the probability of harm caused by equipment failure, as it is difficult to reduce severity. Many implementations of the “risk-based criteria” have focused on severity instead of risk. One example concerns therapeutic equipment. It often receives higher priority on scheduled maintenance (SM) than diagnostic imaging and laboratory equipment, even though the latter could be mission critical. This emphasis would be justified if SM can reduce failures. Analyses conducted at several institutions have shown that SM has limited impact on failure reduction. Furthermore, these studies and reviews of sentinel events and FDA MedWatch reports have concluded that use errors (communications, human factors, etc) account for the majority of patient incidents related to medical equipment, instead of the lack of or improper maintenance.

The challenge of managing risks is further increased by the fact that harm probability does not depend solely on the equipment’s failure probability. An equipment failure can only result in patient harm if all other protective measures (built-in alarms, fail-safe mechanisms, etc) also failed. This concept is well illustrated by the “Swiss-cheese model” of accidents [an organizational model used to analyze the causes of systematic failures or accidents] proposed by James Reason [of the University of Manchester, England]. Similar conclusions were found in the commercial airline and automobile accident analyses.

In theory, it is possible to estimate harm probability if you analyze each equipment type in detail. First, discernment is required as to which kinds of failure are serious enough to cause patient harm, if other protective measures are absent. For example, excessive leakage current on a ventilator is not likely to cause harm, but a defective audible apnea alarm could.

Next, one needs to look into the safety features built into the equipment by the manufacturer. The next line of defense is typically contingent on clinicians becoming aware of the crisis and taking proper actions in time.

Finally, it is necessary to determine the probability of the patient not being able to react to the crisis on his/her own accord. This is extremely difficult as the knowledge of normal human physiology is incomplete and very sketchy in pathological conditions.

Search the 24×7 online archive to find past articles by Binseng Wang on this topic.

While it is very challenging to estimate the probability of harm, CE professionals should not simply continue to use severity solely in determining SM strategies. For SM planning purposes, CE professionals should use probability estimated from their own SM and repair data to weigh the severity scores to determine which groups of equipment deserve more attention. Next, they need to look beyond maintenance and work more closely with clinicians and administration to address issues related to use errors, environmental issues, and better selection of equipment in future purchases. Insisting on scheduling maintenance based solely on severity and ignoring user challenges would be missing the forest for the trees.

Binseng Wang, ScD, CCE, FAIMBE, FACCE, is vice president, performance management and regulatory compliance, ARAMARK Healthcare Clinical Technology Services, Charlotte, NC, and Brian Poplin, DHA, FACHE, CBET, is president, ARAMARK Healthcare Clinical Technology Services, Charlotte, NC. For more information, contact .

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