A Fuzzy Logic Model for Medical Equipment Risk Classification

In Brief In developing countries, hospitals often suffer from insufficient funds and the lack of qualified technical personnel. This leads to a number of problems, among which is the improper and irregular maintenance of medical equipment. This situation calls for an effective approach to prioritize maintenance jobs based on certain importance criteria to make the best use of the available budget. In this article, we adopt the notion that medical equipment maintenance should be prioritized based on their risk level. Existing risk classification models express risk in terms of equipment function, maintenance requirements, and physical risk. They overlook other important factors such as the operational conditions of equipment. Other models have failed to classify critical devices as high risk because they did not incorporate the criticality of equipment as part of the global mission of the hospital. We argue that because hospitals in developing countries rarely implement coherent management standards, same level-of-care hospitals are not technologically equal. This research proposes a new risk assessment model based on fuzzy logic. Because fuzzy logic is closer to the human way of thinking, it is expected to improve the way devices are prioritized. The proposed model was tested on 136 different medical devices in 4 hospitals. Results show that, in certain cases, the same equipment type may have different risk scores depending on the operating conditions within the hospital. Meanwhile, some mission-critical equipment such as steam sterilizers, electrosurgical units, and hematology analyzers attain higher risk levels than obtained by existing models. We attribute this improvement to the fact that risk scores are now dynamic rather than static. This research proposes a new risk assessment model based on fuzzy logic. Since fuzzy logic is closer to the human way of thinking, it is expected to improve the way devices are prioritized.