Discrete-Event Simulation Modeling in Healthcare: A Comprehensive Review

被引:54
作者
Isaac Vazquez-Serrano, Jesus [1 ]
Peimbert-Garcia, Rodrigo E. [1 ,2 ]
Eduardo Cardenas-Barron, Leopoldo [1 ]
机构
[1] Tecnol Monterrey, Sch Engn & Sci, Monterrey 64849, Northeast Nuevo, Mexico
[2] Macquarie Univ, Sch Engn, Sydney, NSW 2109, Australia
关键词
discrete-event; simulation; modeling; healthcare; hospital; review; literature; LENGTH-OF-STAY; PATIENT WAITING TIME; EMERGENCY-DEPARTMENT; COST-EFFECTIVENESS; RESOURCE-ALLOCATION; COMPUTER-SIMULATION; ECONOMIC-EVALUATION; IMPROVE EFFICIENCY; DECISION-SUPPORT; SYSTEM DYNAMICS;
D O I
10.3390/ijerph182212262
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Discrete-event simulation (DES) is a stochastic modeling approach widely used to address dynamic and complex systems, such as healthcare. In this review, academic databases were systematically searched to identify 231 papers focused on DES modeling in healthcare. These studies were sorted by year, approach, healthcare setting, outcome, provenance, and software use. Among the surveys, conceptual/theoretical studies, reviews, and case studies, it was found that almost two-thirds of the theoretical articles discuss models that include DES along with other analytical techniques, such as optimization and lean/six sigma, and one-third of the applications were carried out in more than one healthcare setting, with emergency departments being the most popular. Moreover, half of the applications seek to improve time- and efficiency-related metrics, and one-third of all papers use hybrid models. Finally, the most popular DES software is Arena and Simul8. Overall, there is an increasing trend towards using DES in healthcare to address issues at an operational level, yet less than 10% of DES applications present actual implementations following the modeling stage. Thus, future research should focus on the implementation of the models to assess their impact on healthcare processes, patients, and, possibly, their clinical value. Other areas are DES studies that emphasize their methodological formulation, as well as the development of frameworks for hybrid models.
引用
收藏
页数:20
相关论文
共 50 条
  • [1] Discrete-Event Simulation in Healthcare Settings: A Review
    Forbus, John J.
    Berleant, Daniel
    MODELLING, 2022, 3 (04): : 417 - 433
  • [2] MODELING PARADIGMS FOR DISCRETE-EVENT SIMULATION
    SCHRUBEN, L
    YUCESAN, E
    OPERATIONS RESEARCH LETTERS, 1993, 13 (05) : 265 - 275
  • [3] Computer model and code sharing practices in healthcare discrete-event simulation: a systematic scoping review
    Monks, Thomas
    Harper, Alison
    JOURNAL OF SIMULATION, 2025, 19 (01) : 108 - 123
  • [4] Discrete-Event Simulation of an Intrahospital Transportation Service
    Painchaud, Maxime
    Belanger, Valerie
    Ruiz, Angel
    HEALTH CARE SYSTEMS ENGINEERING, 2017, 210 : 233 - 244
  • [5] Comprehensive review and future research agenda on discrete-event simulation and agent-based simulation of emergency departments
    Ouda, Eman
    Sleptchenko, Andrei
    Simsekler, Mecit Can Emre
    SIMULATION MODELLING PRACTICE AND THEORY, 2023, 129
  • [6] VERIFICATION METHOD FOR DISCRETE-EVENT SIMULATION BASED ON DISCRETE-EVENT SYSTEM FORMALISM
    Jang, Sooyoung
    Choi, Changbeom
    INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING-THEORY APPLICATIONS AND PRACTICE, 2023, 30 (05): : 1313 - 1327
  • [7] Advantages and disadvantages of discrete-event simulation for health economic analyses
    Caro, J. Jaime
    Moller, Jorgen
    EXPERT REVIEW OF PHARMACOECONOMICS & OUTCOMES RESEARCH, 2016, 16 (03) : 327 - 329
  • [8] Discrete-event computer simulation methods in the optimisation of a physiotherapy clinic
    Villamizar, J. R.
    Coelli, F. C.
    Pereira, W. C. A.
    Almeida, R. M. V. R.
    PHYSIOTHERAPY, 2011, 97 (01) : 71 - 77
  • [9] Modeling and analyzing a physician clinic environment using discrete-event (visual) simulation
    Swisher, JR
    Jacobson, SH
    Jun, JB
    Balci, O
    COMPUTERS & OPERATIONS RESEARCH, 2001, 28 (02) : 105 - 125
  • [10] Discrete-Event Simulation Model Generation based on Activity Metrics
    Capocchi L.
    Santucci J.F.
    Pawletta T.
    Folkerts H.
    Zeigler B.P.
    Simulation Modelling Practice and Theory, 2020, 103