Title: Analysis of patient flows in elective surgery: modelling and optimisation of the hospitalisation process

Authors: Dario Antonelli; Giulia Bruno; Teresa Taurino

Addresses: Department of Management and Production Engineering, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino, Italy ' Department of Management and Production Engineering, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino, Italy ' Department of Management and Production Engineering, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino, Italy

Abstract: Rationalising costs while guaranteeing a good quality of service is a challenge that healthcare systems are currently facing. In elective surgery departments, as operations can be scheduled in advance, the goal is usually to maximise the utilisation index of the operating theatre. Nevertheless, the optimisation of a single stage of the process is pointless without an efficient management of the entire routing from income to dismissal. The paper presents discrete events simulation of the actual patient flows in elective surgery exploiting the recovery logs of a hospital department. A UML activity diagram of the surgery process together with the collected hospital data have been used to build a stochastic model of queuing network, identify its parameters and conduct different simulated experiments in order to select the solution that best optimises the performances of the system. The simulation results have shown that there is a large variation in waiting times in correspondence to small variations of the average value of the inter-arrival times. Therefore, solutions that optimise utilisation indexes of both beds and operating theatres should consider a concurrent effort to reduce the variance of admittance processes, otherwise the waiting times will lengthen beyond acceptable limits.

Keywords: healthcare systems; elective surgery; simulation; patient flow; unified modelling language; UML.

DOI: 10.1504/IJSOM.2018.096171

International Journal of Services and Operations Management, 2018 Vol.31 No.4, pp.513 - 529

Received: 16 May 2016
Accepted: 22 Dec 2016
Published online: 15 Nov 2018 *

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