An Intelligent Scheduling of Non-Critical Patients Admission for Emergency Department
The combination of the progressive growth of an aging population, increased life expectancy and a greater number of chronic diseases all contribute significantly to the growing demand for emergency medical care, and thus, causing saturation in Emergency Departments (EDs). This saturation is usually...
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doaj-fe3200b09b2b483d8b20c4b1eebf05bc2021-03-30T01:18:50ZengIEEEIEEE Access2169-35362020-01-0189209922010.1109/ACCESS.2019.29630498945359An Intelligent Scheduling of Non-Critical Patients Admission for Emergency DepartmentEva Bruballa0https://orcid.org/0000-0002-5094-3563Alvaro Wong1https://orcid.org/0000-0002-8394-9478Dolores Rexachs2https://orcid.org/0000-0001-5500-850XEmilio Luque3https://orcid.org/0000-0002-2884-3232Escoles Universitaries Gimbernat (EUG), Computer Science School, Universitat Autonoma de Barcelona, Barcelona, SpainComputer Architecture and Operating Systems Department, Universitat Autonoma de Barcelona Campus Bellaterra, Barcelona, SpainComputer Architecture and Operating Systems Department, Universitat Autonoma de Barcelona Campus Bellaterra, Barcelona, SpainComputer Architecture and Operating Systems Department, Universitat Autonoma de Barcelona Campus Bellaterra, Barcelona, SpainThe combination of the progressive growth of an aging population, increased life expectancy and a greater number of chronic diseases all contribute significantly to the growing demand for emergency medical care, and thus, causing saturation in Emergency Departments (EDs). This saturation is usually due to the admission of non-urgent patients, who constitute a high percentage of patients in an ED. The Agent-based Model (ABM) is one of the most important tools that helps to study complex systems and explores the emergent behavior of this type of department. Its simulation more accurately reflects the complexity of the operation of real systems. Our proposal is the design of an ABM to schedule the access of these non-critical patients into an ED, which can be useful for the service management dealing with the actual growing demand for emergency care. We suppose that a relocation of these non-critical patients within the expected input pattern, provided initially by historical records, enables a reduction in waiting time for all patients, and therefore, it will lead to an improvement in the quality of service. It would also allow us to avoid long waiting times. This research offers the availability of relevant knowledge for Emergency Department managers in order to help them make decisions to improve the quality of the service, in anticipation of the expected growing demand of the service in the very near future.https://ieeexplore.ieee.org/document/8945359/Agent-based modeling and simulation (ABMS)Emergency Department (ED)response capacitydecision support systems (SDS)length of stay (LoS) |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Eva Bruballa Alvaro Wong Dolores Rexachs Emilio Luque |
spellingShingle |
Eva Bruballa Alvaro Wong Dolores Rexachs Emilio Luque An Intelligent Scheduling of Non-Critical Patients Admission for Emergency Department IEEE Access Agent-based modeling and simulation (ABMS) Emergency Department (ED) response capacity decision support systems (SDS) length of stay (LoS) |
author_facet |
Eva Bruballa Alvaro Wong Dolores Rexachs Emilio Luque |
author_sort |
Eva Bruballa |
title |
An Intelligent Scheduling of Non-Critical Patients Admission for Emergency Department |
title_short |
An Intelligent Scheduling of Non-Critical Patients Admission for Emergency Department |
title_full |
An Intelligent Scheduling of Non-Critical Patients Admission for Emergency Department |
title_fullStr |
An Intelligent Scheduling of Non-Critical Patients Admission for Emergency Department |
title_full_unstemmed |
An Intelligent Scheduling of Non-Critical Patients Admission for Emergency Department |
title_sort |
intelligent scheduling of non-critical patients admission for emergency department |
publisher |
IEEE |
series |
IEEE Access |
issn |
2169-3536 |
publishDate |
2020-01-01 |
description |
The combination of the progressive growth of an aging population, increased life expectancy and a greater number of chronic diseases all contribute significantly to the growing demand for emergency medical care, and thus, causing saturation in Emergency Departments (EDs). This saturation is usually due to the admission of non-urgent patients, who constitute a high percentage of patients in an ED. The Agent-based Model (ABM) is one of the most important tools that helps to study complex systems and explores the emergent behavior of this type of department. Its simulation more accurately reflects the complexity of the operation of real systems. Our proposal is the design of an ABM to schedule the access of these non-critical patients into an ED, which can be useful for the service management dealing with the actual growing demand for emergency care. We suppose that a relocation of these non-critical patients within the expected input pattern, provided initially by historical records, enables a reduction in waiting time for all patients, and therefore, it will lead to an improvement in the quality of service. It would also allow us to avoid long waiting times. This research offers the availability of relevant knowledge for Emergency Department managers in order to help them make decisions to improve the quality of the service, in anticipation of the expected growing demand of the service in the very near future. |
topic |
Agent-based modeling and simulation (ABMS) Emergency Department (ED) response capacity decision support systems (SDS) length of stay (LoS) |
url |
https://ieeexplore.ieee.org/document/8945359/ |
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