Eman Ouda, Andrei Sleptchenko, Mecit Can Emre Simsekler
{"title":"你的急诊科对资金流入激增的适应能力如何?弹性增强的一个新的多维框架","authors":"Eman Ouda, Andrei Sleptchenko, Mecit Can Emre Simsekler","doi":"10.1016/j.simpat.2025.103105","DOIUrl":null,"url":null,"abstract":"<div><div>Emergency Departments (EDs) encounter numerous operational challenges, uncertainties, and sudden surges in patient arrivals, often resulting in overcrowding. This overcrowding can impact patient outcomes, staff satisfaction, and the overall functionality of the system. Therefore, it is crucial to strengthen the resilience of these departments in the face of such uncertainties. In this study, we aim to identify the key factors contributing to ED overcrowding and develop a comprehensive hierarchical multidimensional resilience model. This model categorizes the components of three crowding assessment tools: NEDOCS, EDWIN, and READI, into two main categories, recoverability and resistance. The proposed approach demonstrates promising results as we apply it to examine three case studies using Discrete Event Simulation (DES). The subsequent phase involves providing strategic recommendations to improve the ED’s performance and serves as a valuable tool for proactive system failure prevention. These recommendations encompass augmenting available resources and optimizing patient pathways, all aimed at enhancing the ED’s ability to operate effectively. Our findings underscore the accuracy of the DES model in predicting the ED system’s performance under various conditions, ranging from normal patient influx scenarios to high patient influx scenarios. This generalizable hierarchical resilience model aids decision-makers in comprehending system factors for better resource allocation and management decisions.</div></div>","PeriodicalId":49518,"journal":{"name":"Simulation Modelling Practice and Theory","volume":"142 ","pages":"Article 103105"},"PeriodicalIF":3.5000,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"How resilient is your emergency department to inflow surges? A novel multidimensional framework for resilience enhancement\",\"authors\":\"Eman Ouda, Andrei Sleptchenko, Mecit Can Emre Simsekler\",\"doi\":\"10.1016/j.simpat.2025.103105\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Emergency Departments (EDs) encounter numerous operational challenges, uncertainties, and sudden surges in patient arrivals, often resulting in overcrowding. This overcrowding can impact patient outcomes, staff satisfaction, and the overall functionality of the system. Therefore, it is crucial to strengthen the resilience of these departments in the face of such uncertainties. In this study, we aim to identify the key factors contributing to ED overcrowding and develop a comprehensive hierarchical multidimensional resilience model. This model categorizes the components of three crowding assessment tools: NEDOCS, EDWIN, and READI, into two main categories, recoverability and resistance. The proposed approach demonstrates promising results as we apply it to examine three case studies using Discrete Event Simulation (DES). The subsequent phase involves providing strategic recommendations to improve the ED’s performance and serves as a valuable tool for proactive system failure prevention. These recommendations encompass augmenting available resources and optimizing patient pathways, all aimed at enhancing the ED’s ability to operate effectively. Our findings underscore the accuracy of the DES model in predicting the ED system’s performance under various conditions, ranging from normal patient influx scenarios to high patient influx scenarios. This generalizable hierarchical resilience model aids decision-makers in comprehending system factors for better resource allocation and management decisions.</div></div>\",\"PeriodicalId\":49518,\"journal\":{\"name\":\"Simulation Modelling Practice and Theory\",\"volume\":\"142 \",\"pages\":\"Article 103105\"},\"PeriodicalIF\":3.5000,\"publicationDate\":\"2025-03-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Simulation Modelling Practice and Theory\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1569190X25000401\",\"RegionNum\":2,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Simulation Modelling Practice and Theory","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1569190X25000401","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
How resilient is your emergency department to inflow surges? A novel multidimensional framework for resilience enhancement
Emergency Departments (EDs) encounter numerous operational challenges, uncertainties, and sudden surges in patient arrivals, often resulting in overcrowding. This overcrowding can impact patient outcomes, staff satisfaction, and the overall functionality of the system. Therefore, it is crucial to strengthen the resilience of these departments in the face of such uncertainties. In this study, we aim to identify the key factors contributing to ED overcrowding and develop a comprehensive hierarchical multidimensional resilience model. This model categorizes the components of three crowding assessment tools: NEDOCS, EDWIN, and READI, into two main categories, recoverability and resistance. The proposed approach demonstrates promising results as we apply it to examine three case studies using Discrete Event Simulation (DES). The subsequent phase involves providing strategic recommendations to improve the ED’s performance and serves as a valuable tool for proactive system failure prevention. These recommendations encompass augmenting available resources and optimizing patient pathways, all aimed at enhancing the ED’s ability to operate effectively. Our findings underscore the accuracy of the DES model in predicting the ED system’s performance under various conditions, ranging from normal patient influx scenarios to high patient influx scenarios. This generalizable hierarchical resilience model aids decision-makers in comprehending system factors for better resource allocation and management decisions.
期刊介绍:
The journal Simulation Modelling Practice and Theory provides a forum for original, high-quality papers dealing with any aspect of systems simulation and modelling.
The journal aims at being a reference and a powerful tool to all those professionally active and/or interested in the methods and applications of simulation. Submitted papers will be peer reviewed and must significantly contribute to modelling and simulation in general or use modelling and simulation in application areas.
Paper submission is solicited on:
• theoretical aspects of modelling and simulation including formal modelling, model-checking, random number generators, sensitivity analysis, variance reduction techniques, experimental design, meta-modelling, methods and algorithms for validation and verification, selection and comparison procedures etc.;
• methodology and application of modelling and simulation in any area, including computer systems, networks, real-time and embedded systems, mobile and intelligent agents, manufacturing and transportation systems, management, engineering, biomedical engineering, economics, ecology and environment, education, transaction handling, etc.;
• simulation languages and environments including those, specific to distributed computing, grid computing, high performance computers or computer networks, etc.;
• distributed and real-time simulation, simulation interoperability;
• tools for high performance computing simulation, including dedicated architectures and parallel computing.