Levelling the number of required beds at the holding and recovery departments

Bachelor thesis (2017)

Authors

A.M. Babel Electrical Engineering, Mathematics and Computer Science

Contributors

J.T. van Essen (mentor)
K.P. Hart (mentor)
E.M. van Elderen (mentor)
Faculty
Electrical Engineering, Mathematics and Computer Science, Electrical Engineering, Mathematics and Computer Science
Copyright: © 2017 Angelica Babel
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Published Date

25-08-2017

Language

English

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Faculty

Electrical Engineering, Mathematics and Computer Science

Abstract

In this thesis, we consider levelling the number of required beds at the holding and recovery department. Due to the decreased number of available nurses, the workload for the nurses at hospitals has increased. For this reason, it is important to level the number of required beds at the holding and recovery department. By doing so, the workload can be reduced, beds will be available for emergency surgeries, less surgeries will be cancelled due to the lack of beds and less staff will be needed.
The thesis starts with introducing an analytic calculation of the number of required beds at the holding and recovery department. These calculations consider a stochastic length of stay (LOS) distribution for each surgery type. Making use of the analytic calculation and the stochastic length of stay, several solution methods are developed. The first solution method includes a formulation of the problem as an Integer Linear Program (ILP). The exact calculation of the number of required beds is not linear, so the objective function is simplified. The ILP minimises the number of expected beds.
The other solution methods uses the start and end times of each surgery. These start and end times are spread using two algorithms called Fixed Goal Values and Flexible Goal Values.
Data from an Academic Medical Centre in the Netherlands is used to determine the LOS distributions and to find solutions for the ILP and the algorithms. This thesis shows that the number of required bed at the holding and recovery department can be reduced.