Reply: Letter to the Editor: About the advantages and disadvantages of discrete-event simulation for health economic analyses

2016 ◽  
Vol 16 (6) ◽  
pp. 653-653
Author(s):  
J. Jaime Caro ◽  
Jörgen Möller
Keyword(s):  
Health Economic ◽  
Discrete Event Simulation ◽  
Discrete Event ◽  
Event Simulation ◽  
Advantages And Disadvantages ◽  
Letter To The Editor ◽  
Economic Analyses

scholarly journals How to Address Uncertainty in Health Economic Discrete-Event Simulation Models: An Illustration for Chronic Obstructive Pulmonary Disease

2020 ◽  
Vol 40 (5) ◽  
pp. 619-632
Author(s):  
Isaac Corro Ramos ◽  
Martine Hoogendoorn ◽  
Maureen P. M. H. Rutten-van Mölken
Keyword(s):  
Chronic Obstructive Pulmonary Disease ◽  
Health Economic ◽  
Pulmonary Disease ◽  
Discrete Event Simulation ◽  
Discrete Event ◽  
Chronic Obstructive ◽  
Obstructive Pulmonary Disease ◽  
Modeling Uncertainty ◽  
Event Simulation

Background. Evaluation of personalized treatment options requires health economic models that include multiple patient characteristics. Patient-level discrete-event simulation (DES) models are deemed appropriate because of their ability to simulate a variety of characteristics and treatment pathways. However, DES models are scarce in the literature, and details about their methods are often missing. Methods. We describe 4 challenges associated with modeling heterogeneity and structural, stochastic, and parameter uncertainty that can be encountered during the development of DES models. We explain why these are important and how to correctly implement them. To illustrate the impact of the modeling choices discussed, we use (results of) a model for chronic obstructive pulmonary disease (COPD) as a case study. Results. The results from the case study showed that, under a correct implementation of the uncertainty in the model, a hypothetical intervention can be deemed as cost-effective. The consequences of incorrect modeling uncertainty included an increase in the incremental cost-effectiveness ratio ranging from 50% to almost a factor of 14, an extended life expectancy of approximately 1.4 years, and an enormously increased uncertainty around the model outcomes. Thus, modeling uncertainty incorrectly can have substantial implications for decision making. Conclusions. This article provides guidance on the implementation of uncertainty in DES models and improves the transparency of reporting uncertainty methods. The COPD case study illustrates the issues described in the article and helps understanding them better. The model R code shows how the uncertainty was implemented. For readers not familiar with R, the model’s pseudo-code can be used to understand how the model works. By doing this, we can help other developers, who are likely to face similar challenges to those described here.

scholarly journals Discrete-Event Simulation versus Constrained Graphic Modelling of Construction Processes

2014 ◽  
Vol 2 (1) ◽  
pp. 13
Author(s):  
Ian Flood ◽  
Valeh Nowrouzian
Keyword(s):  
Discrete Event Simulation ◽  
Critical Path ◽  
Discrete Event ◽  
Project Planning ◽  
Construction Simulation ◽  
Qualitative Comparison ◽  
Event Simulation ◽  
Advantages And Disadvantages ◽  
Planning And Control ◽  
Linear Scheduling

Effective construction project planning and control requires the development of a model of the project’s construction processes.  The Critical Path Method (CPM) is the most popular project modelling method in construction since it is relatively simple to use and reasonably versatile in terms of the range of processes it can represent.  Several other modelling techniques have been developed over the years, each with their own advantages and disadvantages.  Linear scheduling, for example, has been designed to provide highly insightful visual representations of a construction process, but unfortunately is largely incapable of representing non-repetitive construction work.  Discrete-event simulation is generally agreed to be the most versatile of all modelling methods, but it lacks the simplicity in use of CPM and so has not been widely adopted in construction.  A new graphical constraint-based method of modelling construction processes, Foresight, has been developed with the goal of offering the simplicity in use of CPM, the visual insight of linear scheduling, and the versatility of simulation.  Earlier work has demonstrated the modelling versatility of Foresight.  As part of a continuing study, this paper focuses on a comparison of the Foresight approach with discrete-event construction simulation methods, specifically Stroboscope (a derivative of CYCLONE). Foresight is shown to outperform Stroboscope in terms of the simplicity of the resultant models for a series of case studies involving a number of variants of an earthmoving operation and of a sewer tunnelling operation.  A qualitative comparison of the two approaches also highlights the superior visual insight provided by Foresight over conventional simulation, an attribute essential to both the effective verification and optimization of a model.

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