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Open Access Research article

Development of modelling method selection tool for health services management: From problem structuring methods to modelling and simulation methods

Gyuchan T Jun12, Zoe Morris2, Tillal Eldabi3*, Paul Harper4, Aisha Naseer3, Brijesh Patel5 and John P Clarkson2

Author Affiliations

1 Loughborough Design School, Loughborough University, Loughborough, LE11 3TU, UK

2 Engineering Department, University of Cambridge, Trumpington Street, Cambridge CB2 1PZ, UK

3 Business School, Brunel University, Uxbridge, Middlesex UB8 3PH, UK

4 School of Mathematics, Cardiff University, Senghennydd Road, Cardiff CF24 4AG, UK

5 School of Management, University of Southampton, Southampton SO17 1BJ, UK

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BMC Health Services Research 2011, 11:108  doi:10.1186/1472-6963-11-108

Published: 19 May 2011

Abstract

Background

There is an increasing recognition that modelling and simulation can assist in the process of designing health care policies, strategies and operations. However, the current use is limited and answers to questions such as what methods to use and when remain somewhat underdeveloped.

Aim

The aim of this study is to provide a mechanism for decision makers in health services planning and management to compare a broad range of modelling and simulation methods so that they can better select and use them or better commission relevant modelling and simulation work.

Methods

This paper proposes a modelling and simulation method comparison and selection tool developed from a comprehensive literature review, the research team's extensive expertise and inputs from potential users. Twenty-eight different methods were identified, characterised by their relevance to different application areas, project life cycle stages, types of output and levels of insight, and four input resources required (time, money, knowledge and data).

Results

The characterisation is presented in matrix forms to allow quick comparison and selection. This paper also highlights significant knowledge gaps in the existing literature when assessing the applicability of particular approaches to health services management, where modelling and simulation skills are scarce let alone money and time.

Conclusions

A modelling and simulation method comparison and selection tool is developed to assist with the selection of methods appropriate to supporting specific decision making processes. In particular it addresses the issue of which method is most appropriate to which specific health services management problem, what the user might expect to be obtained from the method, and what is required to use the method. In summary, we believe the tool adds value to the scarce existing literature on methods comparison and selection.