Simulating wait time in healthcare: Accounting for transition process variability using survival analyses

Levin, Scott R.; Garifullin, Maxim

doi:10.1109/wsc.2015.7408250

Cited by 4 publications

References 12 publications

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Operations Research, Simulation

Sharkey¹

2016

Wiley StatsRef: Statistics Reference Online

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Simulation models have been indispensable tools for decision makers in many different public and private environments. Simulation models are created in order to provide valuable insight to decision makers by replicating real‐life decision scenarios and exploring more complete information about the relative uncertainties and their impacts in those environments. This article discusses the methodology of developing a simulation model that involves the abstraction of a real‐life system into a symbolic model format. The multiple stages required in a Monte Carlo simulation study include the (i) problem statement definition; (ii) information gathering and data preparation; (iii) model conceptualization; (iv) model implementation; (v) analysis and interpretation; (vi) verification and validation; and (vii) implementation and documentation. Once a model has been verified and validated as accurately representing the real‐world environment, many “What if” questions about the system can be posed. Illustrative examples are presented.

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Operations Research, Simulation

Sharkey¹

2016

Wiley StatsRef: Statistics Reference Online

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A study on the management of a discrete event simulation project in a manufacturing company with PMBOK®

Montevechi¹,

Pereira²,

Paes³

et al. 2016

2016 Winter Simulation Conference (WSC)

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A systematic literature review of simulation models for non-technical skill training in healthcare logistics

et al. 2018

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BackgroundResource allocation in patient care relies heavily on individual judgements of healthcare professionals. Such professionals perform coordinating functions by managing the timing and execution of a multitude of care processes for multiple patients. Based on advances in simulation, new technologies that could be used for establishing realistic representations have been developed. These simulations can be used to facilitate understanding of various situations, coordination training and education in logistics, decision-making processes, and design aspects of the healthcare system. However, no study in the literature has synthesized the types of simulations models available for non-technical skills training and coordination of care.MethodsA systematic literature review, following the PRISMA guidelines, was performed to identify simulation models that could be used for training individuals in operative logistical coordination that occurs on a daily basis. This article reviewed papers of simulation in healthcare logistics presented in the Web of Science Core Collections, ACM digital library, and JSTOR databases. We conducted a screening process to gather relevant papers as the knowledge foundation of our literature study. The screening process involved a query-based identification of papers and an assessment of relevance and quality.ResultsTwo hundred ninety-four papers met the inclusion criteria. The review showed that different types of simulation models can be used for constructing scenarios for addressing different types of problems, primarily for training and education sessions. The papers identified were classified according to their utilized paradigm and focus areas. (1) Discrete-event simulation in single-category and single-unit scenarios formed the most dominant approach to developing healthcare simulations and dominated all other categories by a large margin. (2) As we approached a systems perspective (cross-departmental and cross-institutional), discrete-event simulation became less popular and is complemented by system dynamics or hybrid modeling. (3) Agent-based simulations and participatory simulations have increased in absolute terms, but the share of these modeling techniques among all simulations in this field remains low.ConclusionsAn extensive study analyzing the literature on simulation in healthcare logistics indicates a growth in the number of examples demonstrating how simulation can be used in healthcare settings. Results show that the majority of studies create situations in which non-technical skills of managers, coordinators, and decision makers can be trained. However, more system-level and complex system-based approaches are limited and use methods other than discrete-event simulation.

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Simulating wait time in healthcare: Accounting for transition process variability using survival analyses

Cited by 4 publications

References 12 publications

Operations Research, Simulation

Operations Research, Simulation

A study on the management of a discrete event simulation project in a manufacturing company with PMBOK®

A systematic literature review of simulation models for non-technical skill training in healthcare logistics

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