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Improving decision making in healthcare services through the use of existing simulation modelling tools and new technologies

Improving decision making in healthcare services through the use of existing simulation modelling... Purpose – The purpose of this paper is to investigate the viability of using distributed simulation to execute large and complex healthcare simulation models which help government take informed decisions. Design/methodology/approach – The paper compares the execution time of a standalone healthcare supply chain simulation with its distributed counterpart. Both the standalone and the distributed models are built using a commercial simulation package (CSP). Findings – The results show that the execution time of the standalone healthcare supply chain simulation increases exponentially as the size and complexity of the system being modelled increases. On the other hand, using distributed simulation approach decreases the run time for large and complex models. Research limitations/implications – The distributed approach of executing different parts of a single simulation model over different computers is only viable when the model: can be divided into logical parts and the exchange of information between these parts occurs at constant simulated time intervals; is sufficiently large and complicated, such that executing the model over a single processor is very time consuming. Practical implications – Based on a feasibility study of the UK National Blood Service we demonstrate the effectiveness of distributed simulation and argue that it is a vital technique in healthcare informatics with respect to supporting decision making in large healthcare systems. Originality/value – To the best of the knowledge, this is the first feasibility study in healthcare which shows the outcome of modelling and executing a distributed simulation using unmodified CSPs and a software/middleware for distributed simulation. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Transforming Government: People, Process and Policy Emerald Publishing

Improving decision making in healthcare services through the use of existing simulation modelling tools and new technologies

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Publisher
Emerald Publishing
Copyright
Copyright © 2010 Emerald Group Publishing Limited. All rights reserved.
ISSN
1750-6166
DOI
10.1108/17506161011047389
Publisher site
See Article on Publisher Site

Abstract

Purpose – The purpose of this paper is to investigate the viability of using distributed simulation to execute large and complex healthcare simulation models which help government take informed decisions. Design/methodology/approach – The paper compares the execution time of a standalone healthcare supply chain simulation with its distributed counterpart. Both the standalone and the distributed models are built using a commercial simulation package (CSP). Findings – The results show that the execution time of the standalone healthcare supply chain simulation increases exponentially as the size and complexity of the system being modelled increases. On the other hand, using distributed simulation approach decreases the run time for large and complex models. Research limitations/implications – The distributed approach of executing different parts of a single simulation model over different computers is only viable when the model: can be divided into logical parts and the exchange of information between these parts occurs at constant simulated time intervals; is sufficiently large and complicated, such that executing the model over a single processor is very time consuming. Practical implications – Based on a feasibility study of the UK National Blood Service we demonstrate the effectiveness of distributed simulation and argue that it is a vital technique in healthcare informatics with respect to supporting decision making in large healthcare systems. Originality/value – To the best of the knowledge, this is the first feasibility study in healthcare which shows the outcome of modelling and executing a distributed simulation using unmodified CSPs and a software/middleware for distributed simulation.

Journal

Transforming Government: People, Process and PolicyEmerald Publishing

Published: Jun 1, 2010

Keywords: Health services; Decision making; Simulation; Modelling; United Kingdom

References