2019 CSCE Annual Conference - Laval (Greater Montreal)

2019 CSCE Annual Conference - Laval (Greater Montreal) Conference


Title
Robust Reserve Capacity Planning for Post-Disaster Health-care Facilities through Intelligent Planning Units (IPUs)

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Author(s)
Dr. Juyeong Choi, Department of Civil & Environmental Engineering at FAMU-FSU College of Engineering (Presenter)
Ms. Fehintola Sanusi, Florida State University
Dr. Makarand Hastak, Division of Construction Engineering and Management, Purdue University
Abstract

Disasters often challenge the operation of health-care facilities. In particular, the insufficient supply of utility services and medical supplies can significantly compromise the operating capacities of hospitals without proper planning of reserve capacities (e.g., backup generators, bottled water, or a stockpile of emergency resources). This research employs the concept of intelligent planning units (IPUs) to guide health-care facilities on how to plan their reserve capacities in preparation for utility disruptions. The use of the IPUs enables resource planning at a single-patient care level based on the objective of a higher planning unit (e.g., service room level or hospital level). This research develops a mixed integer linear programming model that determines required reserve capacities for a post-disaster hospital to provide the highest level of care for patients (i.e., the objective of a high planning unit) through the optimization of the planning units for single-patient care within budget constraints. To demonstrate the implementation of the model, this study shows how to optimize the reserve capacities of a hypothetical hospital to operate intensive care unit services in two post-disaster scenarios: disruptions of water and power service. The recommended capacity plan based on the optimization model varies depending on a hospital’s budget constraints for planning and target quality of service; the higher the risk awareness and target level of medical services, the more expensive the recommended plan. As such, this model can help hospitals adjust and allocate budgets for mitigation planning depending on their desired level of resilience.