Integrated patient and resource allocation response to a pandemic influenza outbreak

Amina Lyazidi, Purdue University

Abstract

The purpose of this thesis is to develop an integrated response planning in the case of a pandemic influenza outbreak. The planning scheme covers the needs of patients from the time they are infected until they leave the hospital at the end of their treatment period. This planning is divided into two broad planning phases. In the first phase, demand is estimated by FluSurge 2.0, a spreadsheet software developed by the Centers for Disease Control and Prevention (CDC). Then a bi-objective, mixed-integer linear programming model is chosen to allocate patients to hospitals while minimizing the total and maximum travelled distances. After that, this model is implemented in a case study with AIMMS optimization software. The second phase consists of using an optimization-simulation approach to a resource allocation problem in one of the hospitals from the case study. A simulation model using AnyLogic software is first developed to describe the course of patients at the hospital from check-in to check-out. Based on the parameters of the simulation study, a weighted goal programming model is developed next with as objectives, the minimization of patients' total waiting time and the number of extra physicians, nurses, beds and ICU beds needed. This model is solved with OptQuest, an add-in in AnyLogic. Afterwards, the results are used to run the simulation again. This novel method is compared to the traditional simulation approach. The optimization-simulation is proven to give better results, although this advantage is more manifest in later periods of the epidemic, when hospitals are congested and every resource is critical. A final conclusion is that more integrated and detailed planning responses are always better.

Degree

M.S.I.E.

Advisors

Lee, Purdue University.

Subject Area

Industrial engineering|Health care management|Operations research

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