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Article type: Research Article
Authors: Cocchi, D.a; * | Ciagli, E.a | Ancora, A.a | Tortoli, P.a | Carpini, C.b | Cirone, D.b | Rossi, E.c | Frosini, F.c | Vezzosi, S.c
Affiliations: [a] Department of Information Engineering, University of Florence, Florence, Italy | [b] General Management Staff, Careggi University Hospital, Florence, Italy | [c] Innovation Control and Quality Area, Careggi University Hospital, Florence, Italy
Correspondence: [*] Corresponding author: D. Cocchi, Department of Information Engineering, University of Florence, Florence, Italy. Tel.: +39 3404985391; Fax: +39 574583773; E-mail: duccio.cocchi@unifi.it.
Abstract: BACKGROUND: Today, hospital rankings are based not only on basic clinical indicators, but even on quality service indicators such as patient waiting times. Improving these indicators is a very important issue for hospital management, so finding a solution to achieve it in a simple and effective way is one of the greatest goals. OBJECTIVES: The aim of this article is to evaluate the use of a discrete event simulation model to improve healthcare processes and reduce waiting time of patients and hospital costs. METHODS: The case study proposed in this paper is the reorganization of non-clinical front office operation for the patients (i.e. booking of exams, delivering medical reports, etc.) of the Careggi University Hospital of Florence, to optimize the utilization of the human resources and to improve performances of the process. RESULTS: The development and validation of the model was made according to an analysis of real processes and data, pre and post implementation of model outcomes. The new organization shows a decrease of waiting times from an average value of 10 minutes and 37 seconds to 5 minutes and 57 seconds (-44%). CONCLUSIONS: This paper shows that discrete event simulation could be a precise, cost-limited tool to optimize hospital processes and performance.
Keywords: Discrete event simulation, healthcare, optimization, front office, lean thinking
DOI: 10.3233/THC-191813
Journal: Technology and Health Care, vol. 28, no. 5, pp. 487-494, 2020
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