LAUSR

A smart hospital can react to emergencies and unexpected events in real time. Emergencies occur frequently in hospitals, and the number of lives saved should be maximized. Because emergency patients disrupt established schedules of hospital operating room, proactive techniques should be employed to save as many lives as possible. In this study, three optimization models were developed for optimizing operating room scheduling during unexpected events and accommodating emergency patient surgeries in the established schedule. The first model (Model I) schedules emergency patients in newly opened rooms, whereas the second model (Model II) aims to assign emergency patients to untapped ranges; the third model (Model III) resequences elective and emergency patients in the room with the greatest free margin. This paper presents a real-life case study for illustration; the three models are adopted and the results are subsequently compared. In conclusion, the proposed models are expected to provide proactive plans for hospitals as well as enhance the performance and efficiency of operating rooms.