  End-stage renal disease patients face a complicated sociomedical situation
and rely on various forms of infrastructure for life-sustaining treatment.
Disruption of these infrastructures during disasters poses a major threat to
their lives. To improve patient access to dialysis treatment, there is a need
to assess the potential threat to critical care facilities from hazardous
events. In this study, we propose optimization models to solve critical care
system resilience problems including patient and medical resource allocation.
We use human mobility data in the context of Harris County (Texas) to assess
patient access to critical care facilities, dialysis centers in this study,
under the simulated hazard impacts, and we propose models for patient
re-allocation and temporary medical facility placement to improve critical care
system resilience in an equitable manner. The results show (1) the capability
of the optimization model in efficient patient re-allocation to alleviate
disrupted access to dialysis facilities; (2) the importance of large facilities
in maintaining the functioning of the system. The critical care system,
particularly the network of dialysis centers, is heavily reliant on a few
larger facilities, making it susceptible to targeted disruption. (3) The
consideration of 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 re-allocation model and temporary facilities
placement can serve as a data-driven and analytic-based decision support tool
for public health and emergency management plans to reduce the loss of access
and disrupted access to critical care facilities and would reduce the dire
social costs.
