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Lean thinking by integrating with discrete event simulation and design of experiments: an emergency department expansion
BACKGROUND: Many management tools, such as Discrete Event Simulation (DES) and Lean Healthcare, are efficient to support and assist health care quality. In this sense, the study aims at using Lean Thinking (LT) principles combined with DES to plan a Canadian emergency department (ED) expansion and a...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7924453/ https://www.ncbi.nlm.nih.gov/pubmed/33816935 http://dx.doi.org/10.7717/peerj-cs.284 |
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author | Gabriel, Gustavo Teodoro Campos, Afonso Teberga Magacho, Aline de Lima Segismondi, Lucas Cavallieri Vilela, Flávio Fraga de Queiroz, José Antonio Montevechi, José Arnaldo Barra |
author_facet | Gabriel, Gustavo Teodoro Campos, Afonso Teberga Magacho, Aline de Lima Segismondi, Lucas Cavallieri Vilela, Flávio Fraga de Queiroz, José Antonio Montevechi, José Arnaldo Barra |
author_sort | Gabriel, Gustavo Teodoro |
collection | PubMed |
description | BACKGROUND: Many management tools, such as Discrete Event Simulation (DES) and Lean Healthcare, are efficient to support and assist health care quality. In this sense, the study aims at using Lean Thinking (LT) principles combined with DES to plan a Canadian emergency department (ED) expansion and at meeting the demand that comes from small care centers closed. The project‘s purpose is reducing the patients’ Length of Stay (LOS) in the ED. Additionally, they must be assisted as soon as possible after the triage process. Furthermore, the study aims at determining the ideal number of beds in the Short Stay Unit (SSU). The patients must not wait more than 180 min to be transferred. METHODS: For this purpose, the hospital decision-makers have suggested planning the expansion, and it was carried out by the simulation and modeling method. The emergency department was simulated by the software FlexSim Healthcare(®), and, with the Design of Experiments (DoE), the optimal number of beds, seats, and resources for each shift was determined. Data collection and modeling were executed based on historical data (patients’ arrival) and from some databases that are in use by the hospital, from April 1st, 2017 to March 31st, 2018. The experiments were carried out by running 30 replicates for each scenario. RESULTS: The results show that the emergency department cannot meet expected demand in the initial planning scenario. Only 17.2% of the patients were completed treated, and LOS was 2213.7 (average), with a confidence interval of (2131.8–2295.6) min. However, after changing decision variables and applying LT techniques, the treated patients’ number increased to 95.7% (approximately 600%). Average LOS decreased to 461.2, with a confidence interval of (453.7–468.7) min, about 79.0%. The time to be attended after the triage decrease from 404.3 min to 20.8 (19.8–21.8) min, around 95.0%, while the time to be transferred from bed to the SSU decreased by 60.0%. Moreover, the ED reduced human resources downtime, according to Lean Thinking principles. |
format | Online Article Text |
id | pubmed-7924453 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | PeerJ Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-79244532021-04-02 Lean thinking by integrating with discrete event simulation and design of experiments: an emergency department expansion Gabriel, Gustavo Teodoro Campos, Afonso Teberga Magacho, Aline de Lima Segismondi, Lucas Cavallieri Vilela, Flávio Fraga de Queiroz, José Antonio Montevechi, José Arnaldo Barra PeerJ Comput Sci Human-Computer Interaction BACKGROUND: Many management tools, such as Discrete Event Simulation (DES) and Lean Healthcare, are efficient to support and assist health care quality. In this sense, the study aims at using Lean Thinking (LT) principles combined with DES to plan a Canadian emergency department (ED) expansion and at meeting the demand that comes from small care centers closed. The project‘s purpose is reducing the patients’ Length of Stay (LOS) in the ED. Additionally, they must be assisted as soon as possible after the triage process. Furthermore, the study aims at determining the ideal number of beds in the Short Stay Unit (SSU). The patients must not wait more than 180 min to be transferred. METHODS: For this purpose, the hospital decision-makers have suggested planning the expansion, and it was carried out by the simulation and modeling method. The emergency department was simulated by the software FlexSim Healthcare(®), and, with the Design of Experiments (DoE), the optimal number of beds, seats, and resources for each shift was determined. Data collection and modeling were executed based on historical data (patients’ arrival) and from some databases that are in use by the hospital, from April 1st, 2017 to March 31st, 2018. The experiments were carried out by running 30 replicates for each scenario. RESULTS: The results show that the emergency department cannot meet expected demand in the initial planning scenario. Only 17.2% of the patients were completed treated, and LOS was 2213.7 (average), with a confidence interval of (2131.8–2295.6) min. However, after changing decision variables and applying LT techniques, the treated patients’ number increased to 95.7% (approximately 600%). Average LOS decreased to 461.2, with a confidence interval of (453.7–468.7) min, about 79.0%. The time to be attended after the triage decrease from 404.3 min to 20.8 (19.8–21.8) min, around 95.0%, while the time to be transferred from bed to the SSU decreased by 60.0%. Moreover, the ED reduced human resources downtime, according to Lean Thinking principles. PeerJ Inc. 2020-08-10 /pmc/articles/PMC7924453/ /pubmed/33816935 http://dx.doi.org/10.7717/peerj-cs.284 Text en ©2020 Gabriel et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Computer Science) and either DOI or URL of the article must be cited. |
spellingShingle | Human-Computer Interaction Gabriel, Gustavo Teodoro Campos, Afonso Teberga Magacho, Aline de Lima Segismondi, Lucas Cavallieri Vilela, Flávio Fraga de Queiroz, José Antonio Montevechi, José Arnaldo Barra Lean thinking by integrating with discrete event simulation and design of experiments: an emergency department expansion |
title | Lean thinking by integrating with discrete event simulation and design of experiments: an emergency department expansion |
title_full | Lean thinking by integrating with discrete event simulation and design of experiments: an emergency department expansion |
title_fullStr | Lean thinking by integrating with discrete event simulation and design of experiments: an emergency department expansion |
title_full_unstemmed | Lean thinking by integrating with discrete event simulation and design of experiments: an emergency department expansion |
title_short | Lean thinking by integrating with discrete event simulation and design of experiments: an emergency department expansion |
title_sort | lean thinking by integrating with discrete event simulation and design of experiments: an emergency department expansion |
topic | Human-Computer Interaction |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7924453/ https://www.ncbi.nlm.nih.gov/pubmed/33816935 http://dx.doi.org/10.7717/peerj-cs.284 |
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