Title: A scenario-based approach for master surgery scheduling under uncertainty

Authors: F. Hooshmand; S.A. MirHassani; A. Akhavein

Addresses: Faculty of Mathematics and Computer Science, Amirkabir University of Technology, Tehran, Iran ' Faculty of Mathematics and Computer Science, Amirkabir University of Technology, Tehran, Iran ' Islamic Azad University, Tehran Medical Branch, Tehran, Iran

Abstract: This study develops a cyclic allocation table in which operating room blocks are allocated to surgeons under the assumption that the hospital authority has already chosen the share of operating room time to be made available for each surgeon. The aim is to minimise the expected bed shortage in the intensive care unit and wards where the number of patients operated by each surgeon, the length of stay of patients, and the number of available beds in hospitalisation units are uncertain. Thus, a scenario-based, two-stage, stochastic model on a large scenario space is proposed. Then, the sample average approximation method is employed to solve the model for a set of randomly sampled scenarios. Numerical experiments demonstrate that by using a moderate sample size, solutions obtained by this method converge to a real optimum in a reasonable time. Moreover, the proposed method outperforms other methods such as expected value approach.

Keywords: master surgery schedule; MSS; bed shortage in hospitalisation units; scenario-based stochastic problem; scenario generation; sample average approximation; SAA.

DOI: 10.1504/IJHTM.2017.10009743

International Journal of Healthcare Technology and Management, 2017 Vol.16 No.3/4, pp.177 - 203

Received: 23 Jun 2016
Accepted: 15 Feb 2017

Published online: 21 Dec 2017 *

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