Model development to improve the predictive maintenance reliability of medical devices

Medical devices are essential in healthcare, and their availability and reliability are critical for quality service. In most Saudi hospitals, maintenance schedules for these devices follow manufacturer recommendations, which often do not account for Saudi Arabia's unique climate and lifestyle. This research introduces a mathematical model to optimize maintenance schedules tailored to Saudi conditions. Three governmental hospitals in Riyadh, Jeddah, and Madinah were selected for a case study. The research developed the Medical Equipment Maintenance Prioritization Factor (MEMPF) model to enhance maintenance schedules. This model uses ten parameters: device function, failure consequence risk, maintenance complexity, device age, utilization rate, failure frequency, maintenance/repair cost, causes of downtime, backup availability, and downtime duration. These parameters were weighted based on their importance. The model was tested on a dataset of 3,640 medical devices from 54 healthcare sections. The outcomes defined maintenance priorities for each device based on the MEMPF value, categorizing them into high, moderate, low, and very low priority. Implementing this model in the case study hospitals could reduce maintenance costs by 36% over ten years.