Modeling using Discrete Event Simulation: A Report of the ISPOR-SMDM Modeling Good Research Practices Task Force-4

Karnon, Jonathan; Stahl, James E.; Brennan, Alan; Jaime, J.; Mar, Javier; Möller, Jörgen

doi:10.1016/j.jval.2012.04.013

Cited by 268 publications

(315 citation statements)

References 36 publications

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“…Los conceptos principales de DES son entidades, atributos, variables, eventos, recursos, colas y tiempo (Karnon et al, 2012;Kelton, Sadowski y Sturrock, 2006). …”

Section: Simulación De Eventos Discretosunclassified

Una comparación cualitativa de la dinámica de sistemas, la simulación de eventos discretos y la simulación basada en agentes

Sarmiento-Vásquez

López-Sandoval

2017

Ing. ind. (Lima)

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Resumen: La dinámica de sistemas, la simulación de eventos discretos y la simulación basada en agentes son tres formas de modelamiento ampliamente usadas para la toma de decisiones empresariales. Estos paradigmas están enfocados en representar el comportamiento de los sistemas en el tiempo, aunque con perspectivas distintas. En este artículo se presenta una comparación de los tres paradigmas en 10 aspectos, comparación que puede servir como referente para elegir la técnica más apropiada para un problema requerido. Palabras clave: teoría de sistemas / métodos de simulación / modelos matemáticosA qualitative comparison of system dynamics, discrete event simulation, and agent-based simulation AbstRAct: Systems dynamics, discrete event simulation, and agent-based simulation are three widely used forms of modeling for business decision making. These paradigms are focused on representing the behavior of systems over time, although in different perspectives. This paper compares the three paradigms in 10 aspects and it can serve as an indicator to choose the most appropriate technique to a required problem.

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“…Los conceptos principales de DES son entidades, atributos, variables, eventos, recursos, colas y tiempo (Karnon et al, 2012;Kelton, Sadowski y Sturrock, 2006). …”

Section: Simulación De Eventos Discretosunclassified

Una comparación cualitativa de la dinámica de sistemas, la simulación de eventos discretos y la simulación basada en agentes

Sarmiento-Vásquez

López-Sandoval

2017

Ing. ind. (Lima)

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“…DES was developed in the 1960s, but its application to economic evaluations started to emerge only in the last decade [40][41][42]. DES is based on the concepts of entities (analogous to agents in ABMs), attributes, queues and resources.…”

Section: Agent-based Models Versus Discrete-event Simulation Modelsmentioning

confidence: 99%

Economic Evaluations with Agent-Based Modelling: An Introduction

Chhatwal

2015

PharmacoEconomics

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Agent-based modelling (ABM) is a relatively new technique, which overcomes some of the limitations of other methods commonly used for economic evaluations. These limitations include linearity, homogeneity and stationarity. Agents in ABMs are autonomous entities, who interact with each other and with the environment. ABMs provide an inductive or 'bottom-up' approach, i.e. individual-level behaviours define system-level components. ABMs have a unique property to capture emergence phenomena that otherwise cannot be predicted by the combination of individual-level interactions. In this tutorial, we discuss the basic concepts and important features of ABMs. We present a case study of an application of a simple ABM to evaluate the cost effectiveness of screening of an infectious disease. We also provide our model, which was developed using an open-source software program, NetLogo. We discuss software, resources, challenges and future research opportunities of ABMs for economic evaluations. Key Points for Decision MakersAgent-based modelling (ABM) is more flexible than other modelling methods commonly used for economic evaluations, and can provide insights into dynamic interactions among real-world phenomena.ABMs can be more challenging to construct than other modelling methods.The need for ABMs is expected to increase as decision-making becomes more complex and as data availability increases.

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“…In particular, DES models allow explicit incorporation of resource constraints (which may result in delays if the resources are not available). It should be noted that both these techniques are being increasingly used for health technology assessment [19][20][21].…”

Section: Examples Of Resource Modelling At Individual Organisationalmentioning

confidence: 99%

Resource Modelling: The Missing Piece of the HTA Jigsaw?

Thokala

Dixon

Jahn³

2014

PharmacoEconomics

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AcknowledgementsThe authors would like to acknowledge the feedback from the reviewers. There are no conflicts of interest for any of the authors. SD wrote the initial drafts for sections 1, 2 and 6. PT and BJ wrote the initial drafts for sections 3, 4 and 5. All authors contributed to the finalising the paper and revising the paper based on reviewers' comments. PT is the overall guarantor for the paper. 2 Abstract:Within health technology assessment (HTA), cost-effectiveness analysis and budget impact analyses have been broadly accepted as important components of decision making. However, whilst they address efficiency and affordability, the issue of implementation and feasibility has been largely ignored. HTA commonly takes place within a deliberative framework that captures issues of implementation and feasibility in a qualitative manner.We argue that only through a formal, quantitative assessment of resource constraints can these issues be fully addressed. This paper argues the need for resource modelling to be considered explicitly in health technology assessment (HTA). First, economic evaluation and budget impact models are described along with their limitations in evaluating feasibility. Next, resource modelling is defined and its usefulness is described along with examples of resource modelling from the literature. Then, the important issues that need to be considered when undertaking resource modelling are described before setting out recommendations for the use of resource modelling in HTA. Key Points for Decision Makers• Economic analyses typically ignore the short term constraints (e.g. beds, availability of CT scanners, nurses, etc) which might lead to low levels of uptake.• A quantitative assessment of technology diffusion, its related resource requirements and capacity constraints is required for uptake to be formally considered by decision makers • Resource modelling is especially useful if there are significant changes in the amount or type of resources needed within the pathway by implementing the new technology • Modelling techniques exist that can capture these resource implications and these analyses can be performed at a national level or at an organisational level 3

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Modeling using Discrete Event Simulation: A Report of the ISPOR-SMDM Modeling Good Research Practices Task Force-4

Cited by 268 publications

References 36 publications

Una comparación cualitativa de la dinámica de sistemas, la simulación de eventos discretos y la simulación basada en agentes

Una comparación cualitativa de la dinámica de sistemas, la simulación de eventos discretos y la simulación basada en agentes

Economic Evaluations with Agent-Based Modelling: An Introduction

Resource Modelling: The Missing Piece of the HTA Jigsaw?

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