Prof. Dr. Thierry Chaussalet
University of Westminster
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Academic Career Length
31Years (1996-Present)
(Calculated once Scilit publication data is synced: current year − year of first publication + 1)
Representative Publications
View All Publications1 October 1998 in Health Care Management Science
Journal Article
EEE. El‐Darzi
E. El‐DarziCVC. Vasilakis
C. VasilakisThierry ChaussaletPMP.H. Millard
P.H. Millard
15 December 2004 in Journal of the Royal Statistical Society Series A: Statistics in Society
Journal Article
19 May 2009 in Annals of Operations Research
Journal Article
MAMd Asaduzzaman
Md AsaduzzamanThierry ChaussaletNRNicola J. Robertson
Nicola J. Robertson
The main aim of this paper is to derive a solution to the capacity problem faced by many perinatal networks in the United Kingdom. We propose a queueing model to determine the number of cots at all care units for any desired overflow and rejection probability in a neonatal unit. The model formulation is developed, being motivated by overflow models in telecommunication systems. Exact expressions for the overflow and rejection probabilities are derived. The model is then applied to a neonatal unit of a perinatal network in the UK.
1 February 2013 in Journal of the Operational Research Society
Journal Article
Sally BrailsfordTBT B Bolt
T B Bolt
GBG Bucci
G Bucci
Thierry ChaussaletNCN A Connell
N A Connell
MTM Taylor
M Taylor
+3
This paper addresses a key issue in the health OR literature, namely the apparent failure of OR modelling to become embedded and widely implemented within healthcare organisations. The research presented here is a case study to evaluate the adoption of one particular simulation modelling tool, Scenario Generator (S:G), which was developed by the SIMUL8 Corporation in a PPI partnership with the UK's National Health Service (NHS) Institute for Innovation and Improvement. The study involved semi-structured interviews with employees of 28 Primary Care Trusts who had all been engaged in some way with the initiative, with participants classified as ‘Not Started’, ‘Given Up’ and ‘Actively Using’. This paper presents a brief summary of barriers and facilitators to the successful use of the S:G software, but its main purpose is to focus more broadly on factors influencing the successful adoption of simulation tools in general within healthcare organisations. The insights gained in this study are relevant to improving the uptake of OR modelling in general within the NHS.
5 July 2006 in IEEE Transactions on Information Technology in Biomedicine
Journal Article
Understanding the pattern of length of stay in institutional long-term care has important practical implications in the management of long-term care. Furthermore, residents' attributes are believed to have significant effects on these patterns. In this paper, we present a model-based approach to extract, from a routinely gathered administrative social care dataset, high-level length-of-stay patterns of residents in long-term care. This approach extends previous work by the authors to incorporate residents' features. Two applications using data provided by a local authority in England are presented to demonstrate the potential use of this approach
1 April 2013 in Decision Support Systems
Journal Article
About Me
After receiving a PhD from North Carolina State University (USA) in Probability and Stochastic Processes, Thierry started his career in the UK as a lecturer at the University of Westminster, where he founded in 1998 the Health and Social Care Modelling Group and became Professor in 2007. His research interests are around quantitative modelling of management processes, intelligent data driven methods for informed decision making, resource planning and management.
Thierry serves on the Editorial Board of various healthcare modelling and analytics journals and has edited several special issues of internationally recognised journals. He is member of the NIHR Peer Review panel and was a member of the EPSRC Peer Review College 1996-2016. He was expert evaluator for the EU FP7 ICT programme in 2013 and the EU4H-2023-DGA-MS-IBA-04 in 2024. Keen promoter of the use of data driven modelling and simulation approaches for the management of healthcare, he is also Chair of the Operational Research Society Health and Social Services Special Interest Group, and founding member of MASHnet, the UK network for Modelling And Simulation in Healthcare.