Improving the Resilience of Military Hospitals Through Self-Adaptation of Hospital Systems Using Organic Computing

Background and Aim: Among the failures of a disaster, the disruption of the critical infrastructure of the community causes the most damage to society. Therefore, the ability of critical infrastructure such as hospitals to anticipate, absorb, adapt or rapidly recover from a devastating event is essential. The purpose of this study is to design a self-adaptive model for resilient hospital systems to improve the quality of services in military hospitals. Methods: In this paper, first the vital systems of resilient hospital were identified using library studies. Then, in the selected systems, aspects of self-adaptive appropriate to each system were selected, and by applying the organic computing method, these systems were self-adapted. agent-based modeling has been used to evaluate the model of Resilient Hospital self-adaptive systems. Necessary data were obtained in the field from a military hospital. Results: According to the simulation results, the self-adaptive model of resilient hospital systems in the support and resource management system has been able to reduce the average backlog of demand by 34.24% and the average waiting time to receive demand by 38.89%. This model has reduced the number of units’ failures in the hospital safety system by 37.53%. In the emergency and disaster management system, the self-adaptive model has been able to reduce the evacuation time of the hospital by 42.11%. The self-adaptive model has improved the performance of the emergency medical care system by 13%. Conclusion: Due to their ability to change behavior in time, self-adapting systems have the ability to improve the resilience of military hospitals in any crisis and make them more successful in their missions.