An equitable patient reallocation optimization and temporary facility placement model for maximizing critical care system resilience in disasters

Abstract

Medical infrastructure disruptions during disasters pose a major threat to critically ill patients with advanced chronic kidney disease or end-stage renal disease. There is a need to assess the potential threat to critical care facilities from hazardous events to improve patient access to dialysis treatment. We propose optimization models for patient reallocation and temporary medical facility placement to equitably improve critical care system resilience. We leverage human mobility data in Texas to assess patient access to critical care facilities and dialysis centers under the simulated hazard impacts. The optimization model was formulated as an integer programming and solved by COIN-OR Branch-and-Cut (CBC) solver. The results show (1) the capability of the optimization model in efficient patient reallocation to alleviate disrupted access to dialysis facilities; (2) the importance of large facilities in maintaining the system functionality. The critical care system, particularly the network of dialysis centers, is heavily reliant on a few larger facilities, characteristic of scale-free networks, making it susceptible to targeted disruption, such as capacity failures. (3) Considering equity in the optimization model formulation reduces access loss for vulnerable populations in the simulated scenarios. (4) The proposed temporary facilities placement could improve access for the vulnerable population, thereby improving the equity of access to critical care facilities in disaster. The proposed patient reallocation optimization model and temporary facilities placement offer a data-driven and analytics-based decision support tool tailored to the needs of healthcare organizations across private and public sectors to proactively mitigate the potential loss of access to critical care facilities during disasters.