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research article

Assessing the Impact of Stochasticity for Operating Theater Sizing

Tancrez, J.-S.
•
Roland, B.
•
Cordier, J.-P.
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2013
Decision Support Systems

Over the last few decades, rational health care management and, in particular, operating theater planning, has attracted increased attention from practitioners and from the scientific community. However, although the operating theater environment is clearly stochastic, the impact of this randomness has often been ignored. In practice, simple rules based largely on past experience (such as keeping a safety margin), are most frequently used when making plans for the operating theater. In this paper, we propose an approach to help rationalize, at a strategic decision-making level, the way in which stochasticity can be taken into account in operating theater management, to help in the sizing and in the allocation of capacity. The three main sources of randomness are considered: durations of operations, unexpected emergencies and blocking because of a full recovery unit. Based on the Markov theory, our tool enables several performance measures to be estimated. An operating theater manager can use our approach to make informed decisions and assess, for example, the disruption of the planning by emergencies, the waiting times for emergency patients, the impact of the recovery unit, or the distribution of the working time. In particular, our approach helps determine the number of operations that should be planned in order to keep expected overtime limited. The tool is described in detail, discussed, and applied to the illustrative case of a Belgian hospital. (C) 2012 Elsevier B.V. All rights reserved.

  • Details
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Type
research article
DOI
10.1016/j.dss.2012.10.021
Web of Science ID

WOS:000320687700018

Author(s)
Tancrez, J.-S.
Roland, B.
Cordier, J.-P.
Riane, F.
Date Issued

2013

Publisher

Elsevier

Published in
Decision Support Systems
Volume

55

Issue

2

Start page

616

End page

628

Subjects

Healthcare management

•

Operating theater

•

Stochastic modeling

•

Markov process

•

Sizing

•

Emergencies

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
TOM  
Available on Infoscience
July 26, 2013
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/93545
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