Discrete-event simulation to reduce waiting time in accident and emergency departments: a case study in a district general clinic

Waiting time is a crucial performance metric in A&E departments. In this regard, longer waiting times are related to low patient satisfaction, high mortality rates and more severe physical health complications. To analyze patient flow in these departments, discrete-event simulation (DES) has bee...

Full description

Autores:
Nuñez Perez, Nixon De Jesus
Ortiz Barrios, Miguel Angel
McClean, S. I.
Salas Navarro, Katherinne Paola
Jimenez, Genett
Tipo de recurso:
http://purl.org/coar/resource_type/c_f744
Fecha de publicación:
2017
Institución:
Corporación Universidad de la Costa
Repositorio:
REDICUC - Repositorio CUC
Idioma:
eng
OAI Identifier:
oai:repositorio.cuc.edu.co:11323/2006
Acceso en línea:
https://hdl.handle.net/11323/2006
https://repositorio.cuc.edu.co/
Palabra clave:
Accident and emergency (A&E)
Discrete event simulation (DES)
Emergency departments (EDs)
Healthcare
Rights
openAccess
License
Atribución – No comercial – Compartir igual
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dc.title.spa.fl_str_mv Discrete-event simulation to reduce waiting time in accident and emergency departments: a case study in a district general clinic
title Discrete-event simulation to reduce waiting time in accident and emergency departments: a case study in a district general clinic
spellingShingle Discrete-event simulation to reduce waiting time in accident and emergency departments: a case study in a district general clinic
Accident and emergency (A&E)
Discrete event simulation (DES)
Emergency departments (EDs)
Healthcare
title_short Discrete-event simulation to reduce waiting time in accident and emergency departments: a case study in a district general clinic
title_full Discrete-event simulation to reduce waiting time in accident and emergency departments: a case study in a district general clinic
title_fullStr Discrete-event simulation to reduce waiting time in accident and emergency departments: a case study in a district general clinic
title_full_unstemmed Discrete-event simulation to reduce waiting time in accident and emergency departments: a case study in a district general clinic
title_sort Discrete-event simulation to reduce waiting time in accident and emergency departments: a case study in a district general clinic
dc.creator.fl_str_mv Nuñez Perez, Nixon De Jesus
Ortiz Barrios, Miguel Angel
McClean, S. I.
Salas Navarro, Katherinne Paola
Jimenez, Genett
dc.contributor.author.spa.fl_str_mv Nuñez Perez, Nixon De Jesus
Ortiz Barrios, Miguel Angel
McClean, S. I.
Salas Navarro, Katherinne Paola
Jimenez, Genett
dc.subject.spa.fl_str_mv Accident and emergency (A&E)
Discrete event simulation (DES)
Emergency departments (EDs)
Healthcare
topic Accident and emergency (A&E)
Discrete event simulation (DES)
Emergency departments (EDs)
Healthcare
description Waiting time is a crucial performance metric in A&E departments. In this regard, longer waiting times are related to low patient satisfaction, high mortality rates and more severe physical health complications. To analyze patient flow in these departments, discrete-event simulation (DES) has been used; however, its application has not been extended to evaluate the impact of improvement strategies. Therefore, this paper aims to design and pretest operational strategies for better ED care delivery using DES. First, input data analysis is carried out. Afterward, the DES model is developed and validated to establish whether it is statistically comparable with the real-world. Then, performance indicators of the current system are computed and analyzed. Finally, improvement strategies are proposed and evaluated by simulation modelling and statistical tests. A case study of an A&E department from a district general clinic is presented to validate the proposed framework. In particular, we will validate the effectiveness of introducing a triage system (Scenario 3), a strategy that is not currently adopted by the clinic. Results demonstrate that waiting times could be meaningfully diminished based on the proposed approaches within this paper.
publishDate 2017
dc.date.issued.none.fl_str_mv 2017
dc.date.accessioned.none.fl_str_mv 2019-01-18T16:10:25Z
dc.date.available.none.fl_str_mv 2019-01-18T16:10:25Z
dc.type.spa.fl_str_mv Documento de Conferencia
dc.type.coar.fl_str_mv http://purl.org/coar/resource_type/c_c94f
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dc.identifier.isbn.spa.fl_str_mv 978-331967584-8
dc.identifier.issn.spa.fl_str_mv 03029743
dc.identifier.uri.spa.fl_str_mv https://hdl.handle.net/11323/2006
dc.identifier.instname.spa.fl_str_mv Corporación Universidad de la Costa
dc.identifier.reponame.spa.fl_str_mv REDICUC - Repositorio CUC
dc.identifier.repourl.spa.fl_str_mv https://repositorio.cuc.edu.co/
identifier_str_mv 978-331967584-8
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Corporación Universidad de la Costa
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dc.language.iso.none.fl_str_mv eng
language eng
dc.relation.ispartof.spa.fl_str_mv 10.1007/978-3-319-67585-5_37
dc.rights.spa.fl_str_mv Atribución – No comercial – Compartir igual
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rights_invalid_str_mv Atribución – No comercial – Compartir igual
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eu_rights_str_mv openAccess
dc.publisher.spa.fl_str_mv Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
institution Corporación Universidad de la Costa
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spelling Nuñez Perez, Nixon De JesusOrtiz Barrios, Miguel AngelMcClean, S. I.Salas Navarro, Katherinne PaolaJimenez, Genett2019-01-18T16:10:25Z2019-01-18T16:10:25Z2017978-331967584-803029743https://hdl.handle.net/11323/2006Corporación Universidad de la CostaREDICUC - Repositorio CUChttps://repositorio.cuc.edu.co/Waiting time is a crucial performance metric in A&E departments. In this regard, longer waiting times are related to low patient satisfaction, high mortality rates and more severe physical health complications. To analyze patient flow in these departments, discrete-event simulation (DES) has been used; however, its application has not been extended to evaluate the impact of improvement strategies. Therefore, this paper aims to design and pretest operational strategies for better ED care delivery using DES. First, input data analysis is carried out. Afterward, the DES model is developed and validated to establish whether it is statistically comparable with the real-world. Then, performance indicators of the current system are computed and analyzed. Finally, improvement strategies are proposed and evaluated by simulation modelling and statistical tests. A case study of an A&E department from a district general clinic is presented to validate the proposed framework. In particular, we will validate the effectiveness of introducing a triage system (Scenario 3), a strategy that is not currently adopted by the clinic. Results demonstrate that waiting times could be meaningfully diminished based on the proposed approaches within this paper.Nuñez Perez, Nixon De Jesus-831eced6-e8dc-4b33-9ab3-2ae6321fe39d-0Ortiz Barrios, Miguel Angel-0000-0001-6890-7547-600McClean, S. 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