The Impact of Patient Infection Rate on Emergency Department Patient Flow: Hybrid Simulation Study in a Norwegian Case

被引:1
作者
Terning, Gaute [1 ]
El-Thalji, Idriss [2 ]
Brun, Eric Christian [1 ]
机构
[1] Univ Stavanger, Dept Safety Econ & Planning, N-4036 Stavanger, Norway
[2] Univ Stavanger, Dept Mech & Struct Engn & Mat Sci, N-4036 Stavanger, Norway
关键词
healthcare; emergency department; patient flow; patient infection rate; COVID-19; pandemic; agent-based hybrid model; multi-agent hybrid model; pandemic decision support; PERFORMANCE;
D O I
10.3390/healthcare11131904
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
The COVID-19 pandemic put emergency departments all over the world under severe and unprecedented distress. Previous methods of evaluating patient flow impact, such as in-situ simulation, tabletop studies, etc., in a rapidly evolving pandemic are prohibitively impractical, time-consuming, costly, and inflexible. For instance, it is challenging to study the patient flow in the emergency department under different infection rates and get insights using in-situ simulation and tabletop studies. Despite circumventing many of these challenges, the simulation modeling approach and hybrid agent-based modeling stand underutilized. This study investigates the impact of increased patient infection rate on the emergency department patient flow by using a developed hybrid agent-based simulation model. This study reports findings on the patient infection rate in different emergency department patient flow configurations. This study's results quantify and demonstrate that an increase in patient infection rate will lead to an incremental deterioration of the patient flow metrics average length of stay and crowding within the emergency department, especially if the waiting functions are introduced. Along with other findings, it is concluded that waiting functions, including the waiting zone, make the single average length of stay an ineffective measure as it creates a multinomial distribution of several tendencies.
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页数:33
相关论文
共 39 条
[1]  
Albin S., 2001, BUILDING SYSTEM DY 1
[2]   Use of In Situ Simulation to Improve Emergency Department Readiness for the COVID-19 Pandemic [J].
Aljahany, Muna ;
Alassaf, Wajdan ;
Alibrahim, Ahmed A. ;
Kentab, Osama ;
Alotaibi, Abdullah ;
Alresseeni, Abdulaziz ;
Algarni, Abdulaziz ;
Algaeed, Hamad A. ;
Aljaber, Mohammed I. ;
Alruwaili, Badriyah ;
Aljohani, Khalid .
PREHOSPITAL AND DISASTER MEDICINE, 2021, 36 (01) :6-13
[3]   Mutational cascade of SARS-CoV-2 leading to evolution and emergence of omicron variant [J].
Bansal, Kanika ;
Kumar, Sanjeet .
VIRUS RESEARCH, 2022, 315
[4]   Patient flow modelling and performance analysis of healthcare delivery processes in hospitals: A review and reflections [J].
Bhattacharjee, Papiya ;
Ray, Pradip Kumar .
COMPUTERS & INDUSTRIAL ENGINEERING, 2014, 78 :299-312
[5]  
Borshchev A., 2013, The Big Book of Simulation Modeling: Multimethod Modeling with Anylogic 6
[6]   The Exponential Phase of the Covid-19 Pandemic in Central Italy: An Integrated Care Pathway [J].
Capalbo, Carlo ;
Aceti, Antonio ;
Simmaco, Maurizio ;
Bonfini, Rita ;
Rocco, Monica ;
Ricci, Alberto ;
Napoli, Christian ;
Rocco, Matteo ;
Alfonsi, Valeria ;
Teggi, Antonella ;
Orsi, Giovanni Battista ;
Borro, Marina ;
Santino, Iolanda ;
Preissner, Robert ;
Marchetti, Paolo ;
Marcolongo, Adriano ;
Anibaldi, Paolo .
INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, 2020, 17 (11)
[7]  
Castro AJ, 2021, ANAL MATH PHYS, V11, DOI [10.3390/app11020805, 10.1007/s13324-021-00552-x]
[8]  
cdc.gov, PEOPLE CERTAIN MEDIC
[9]   Collateral Effect of the Coronavirus Disease 2019 Pandemic on Emergency Department Visits in Korea [J].
Cho, Yeon-Joo ;
Yeo, In-Hwan ;
Lee, Dong-Eun ;
Kim, Jong-Kun ;
Kim, Yun-Jeong ;
Kim, Chang-Ho ;
Choe, Jae-Young ;
Park, Jung-Bae ;
Seo, Kang-Suk ;
Yu, Byung-Hyuk ;
Lee, Won-Kee .
MEDICINA-LITHUANIA, 2023, 59 (01)
[10]   The COVID-19 pandemic [J].
Ciotti, Marco ;
Ciccozzi, Massimo ;
Terrinoni, Alessandro ;
Jiang, Wen-Can ;
Wang, Cheng-Bin ;
Bernardini, Sergio .
CRITICAL REVIEWS IN CLINICAL LABORATORY SCIENCES, 2020, 57 (06) :365-388