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Presented a Framework of Computational Modeling to Identify the Patient Admission Scheduling Problem in the Healthcare System

Operating room scheduling is a prominent study topic due to its complexity and significance. The increasing number of technical operating room scheduling articles produced each year calls for another evaluation of the literature to enable academics to respond to new trends more quickly. The mathemat...

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Autores principales: Hosseini Rad, Reza, Baniasadi, Sahba, Yousefi, Parisa, Morabbi Heravi, Hakimeh, Shaban Al-Ani, Muzhir, Asghari Ilani, Mohsen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9726263/
https://www.ncbi.nlm.nih.gov/pubmed/36483659
http://dx.doi.org/10.1155/2022/1938719
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author Hosseini Rad, Reza
Baniasadi, Sahba
Yousefi, Parisa
Morabbi Heravi, Hakimeh
Shaban Al-Ani, Muzhir
Asghari Ilani, Mohsen
author_facet Hosseini Rad, Reza
Baniasadi, Sahba
Yousefi, Parisa
Morabbi Heravi, Hakimeh
Shaban Al-Ani, Muzhir
Asghari Ilani, Mohsen
author_sort Hosseini Rad, Reza
collection PubMed
description Operating room scheduling is a prominent study topic due to its complexity and significance. The increasing number of technical operating room scheduling articles produced each year calls for another evaluation of the literature to enable academics to respond to new trends more quickly. The mathematical application of a model for the patient admission scheduling issue with stochastic arrivals and departures is the subject of this study. The approach for applying our model to real-world issues is discussed here. We present a solution technique for efficient computing, a numerical model analysis, and examples to demonstrate the methodology. This study looked at the challenge of assigning procedures to operate rooms in the face of ambiguity regarding surgery length and the arrival of emergency patients based on a flexible policy (capacity reservation). We demonstrate that the proposed methods derived from deterministic models are inadequate compared to the answers produced from our stochastic model using simple numerical examples. We also use heuristics to estimate the objective function to build more complicated numerical examples for large-scale issues, demonstrating that our methodology can be applied quickly to real-world situations that often include big information sets.
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spelling pubmed-97262632022-12-07 Presented a Framework of Computational Modeling to Identify the Patient Admission Scheduling Problem in the Healthcare System Hosseini Rad, Reza Baniasadi, Sahba Yousefi, Parisa Morabbi Heravi, Hakimeh Shaban Al-Ani, Muzhir Asghari Ilani, Mohsen J Healthc Eng Research Article Operating room scheduling is a prominent study topic due to its complexity and significance. The increasing number of technical operating room scheduling articles produced each year calls for another evaluation of the literature to enable academics to respond to new trends more quickly. The mathematical application of a model for the patient admission scheduling issue with stochastic arrivals and departures is the subject of this study. The approach for applying our model to real-world issues is discussed here. We present a solution technique for efficient computing, a numerical model analysis, and examples to demonstrate the methodology. This study looked at the challenge of assigning procedures to operate rooms in the face of ambiguity regarding surgery length and the arrival of emergency patients based on a flexible policy (capacity reservation). We demonstrate that the proposed methods derived from deterministic models are inadequate compared to the answers produced from our stochastic model using simple numerical examples. We also use heuristics to estimate the objective function to build more complicated numerical examples for large-scale issues, demonstrating that our methodology can be applied quickly to real-world situations that often include big information sets. Hindawi 2022-11-29 /pmc/articles/PMC9726263/ /pubmed/36483659 http://dx.doi.org/10.1155/2022/1938719 Text en Copyright © 2022 Reza Hosseini Rad et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Hosseini Rad, Reza
Baniasadi, Sahba
Yousefi, Parisa
Morabbi Heravi, Hakimeh
Shaban Al-Ani, Muzhir
Asghari Ilani, Mohsen
Presented a Framework of Computational Modeling to Identify the Patient Admission Scheduling Problem in the Healthcare System
title Presented a Framework of Computational Modeling to Identify the Patient Admission Scheduling Problem in the Healthcare System
title_full Presented a Framework of Computational Modeling to Identify the Patient Admission Scheduling Problem in the Healthcare System
title_fullStr Presented a Framework of Computational Modeling to Identify the Patient Admission Scheduling Problem in the Healthcare System
title_full_unstemmed Presented a Framework of Computational Modeling to Identify the Patient Admission Scheduling Problem in the Healthcare System
title_short Presented a Framework of Computational Modeling to Identify the Patient Admission Scheduling Problem in the Healthcare System
title_sort presented a framework of computational modeling to identify the patient admission scheduling problem in the healthcare system
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9726263/
https://www.ncbi.nlm.nih.gov/pubmed/36483659
http://dx.doi.org/10.1155/2022/1938719
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