Evidence-based mathematical maintenance model for medical equipment

Today, medical equipment maintenance suffers from the same ailments that traditional medicine was suffering from before. Rapid advance of medical technologies has proven that traditional maintenance is no longer enough to ensure that equipment is getting the best possible maintenance. Medical equipment industry has been following empirical approaches and very little was done on mathematical modelling. Preliminary data collected from some hospitals in USA and analysed show that current maintenance strategies might be effective but there is no clear evidence whether they are efficient. However, incorporating mission-criticality concept with patient risk might produce much higher impact on reduction of risk. Refocusing resources from scheduled maintenance to higher impact tasks, e.g., use error tracking, self-identified failures and repairs, user training and working with facilities and purchasing should lead to a balanced mix between needs and resources. A mathematical model is developed using a mixed integer based approach for maintenance operations schedules for medical equipment. Field data are used to get the parameters of the model by nonlinear least square regression. A greedy algorithm is proposed to give an initial solution for the model.