Emerging methods in economic modeling of imaging costs and outcomes: A short report on discrete event simulation

被引:17
|
作者
Hollingworth, William
Spackman, D. Eldon
机构
[1] Univ Washington, Dept Radiol, Seattle, WA 98104 USA
[2] Univ Washington, Dept Pharm, Seattle, WA 98104 USA
关键词
models; economic; Markov chains; diagnostic imaging; computer simulation;
D O I
10.1016/j.acra.2007.01.007
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Rationale and Objectives. This short report provides a non-technical overview of one emerging modeling technique, discrete event simulation (DES). Methods. A selective review of the literature that has applied DES methods to evaluate imaging technologies. Results. Mathematical models to evaluate the likely costs and outcomes of health technologies have become increasingly accepted. Increasing experience has also brought a mounting awareness of the limitations of conventional modeling techniques such as decision trees and Markov processes. Patient-level simulation, including DES, may provide a more flexible approach to modeling for economic evaluation of health technologies. Conclusions. The strengths of DES suggest that it may have an increasingly important role in the future modeling of annual screening programs, diagnosis, and treatment of chronic recurrent disease and modeling the utilization of imaging equipment.
引用
收藏
页码:406 / 410
页数:5
相关论文
共 10 条
  • [1] Estimated societal costs of stroke in the UK based on a discrete event simulation
    Patel, Anita
    Berdunov, Vladislav
    Quayyum, Zahidul
    King, Derek
    Knapp, Martin
    Wittenberg, Raphael
    AGE AND AGEING, 2020, 49 (02) : 270 - 276
  • [2] Discrete-Event Simulation Modeling in Healthcare: A Comprehensive Review
    Isaac Vazquez-Serrano, Jesus
    Peimbert-Garcia, Rodrigo E.
    Eduardo Cardenas-Barron, Leopoldo
    INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, 2021, 18 (22)
  • [3] 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
  • [4] Modeling Using Discrete Event Simulation: A Report of the ISPOR-SMDM Modeling Good Research Practices Task Force-4
    Karnon, Jonathan
    Stahl, James
    Brennan, Alan
    Caro, J. Jaime
    Mar, Javier
    Moller, Jorgen
    MEDICAL DECISION MAKING, 2012, 32 (05) : 701 - 711
  • [5] Modeling using Discrete Event Simulation: A Report of the ISPOR-SMDM Modeling Good Research Practices Task Force-4
    Karnon, Jonathan
    Stahl, James
    Brennan, Alan
    Caro, J. Jaime
    Mar, Javier
    Moller, Jorgen
    VALUE IN HEALTH, 2012, 15 (06) : 821 - 827
  • [6] Discrete-Event Simulation Modeling Unlocks Value for the Jansen Potash Project
    Bouffard, Sylvie C.
    Boggis, Peter
    Monk, Bryan
    Pereira, Marianela
    Quan, Keith
    Fleming, Sandra
    INTERFACES, 2018, 48 (01) : 45 - 56
  • [7] Discrete-event simulation models in the economic evaluation of health technologies and health products
    Rodriguez Barrios, Jose Manuel
    Serrano, David
    Monleon, Ton
    Caro, Jaime
    GACETA SANITARIA, 2008, 22 (02) : 151 - 161
  • [8] Computer modeling of patient flow in a pediatric emergency department using discrete event simulation
    Hung, Geoffrey R.
    Whitehouse, Sandra R.
    ONeill, Craig
    Gray, Andrew P.
    Kissoon, Niranjan
    PEDIATRIC EMERGENCY CARE, 2007, 23 (01) : 5 - 10
  • [9] Discrete Event Modeling and Simulation-Driven Engineering for the ATLAS Data Acquisition Network
    Bonaventura, Matias
    Foguelman, Daniel
    Castro, Rodrigo
    COMPUTING IN SCIENCE & ENGINEERING, 2016, 18 (03) : 70 - 83
  • [10] Methods for Assessing Longitudinal Biomarkers of Time-to-Event Outcomes in CKD: A Simulation Study
    Liu, Qian
    Smith, Abigail R.
    Mariani, Laura H.
    Nair, Viji
    Zee, Jarcy
    CLINICAL JOURNAL OF THE AMERICAN SOCIETY OF NEPHROLOGY, 2019, 14 (09): : 1315 - 1323