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This article is part of the supplement: Research from the Eleventh International Workshop on Network Tools and Applications in Biology (NETTAB 2011)

Open Access Open Badges Research

Modelling and performance analysis of clinical pathways using the stochastic process algebra PEPA

Xian Yang1, Rui Han1, Yike Guo1*, Jeremy Bradley1, Benita Cox2, Robert Dickinson3 and Richard Kitney3

  • * Corresponding author: Yike Guo

  • † Equal contributors

Author Affiliations

1 Department of Computing, Imperial College London, London, SW7 2AZ, UK

2 Business School, Imperial College London, London, SW7 2AZ, UK

3 Department of Bioengineering, Imperial College London, London, SW7 2AZ, UK

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BMC Bioinformatics 2012, 13(Suppl 14):S4  doi:10.1186/1471-2105-13-S14-S4

Published: 7 September 2012



Hospitals nowadays have to serve numerous patients with limited medical staff and equipment while maintaining healthcare quality. Clinical pathway informatics is regarded as an efficient way to solve a series of hospital challenges. To date, conventional research lacks a mathematical model to describe clinical pathways. Existing vague descriptions cannot fully capture the complexities accurately in clinical pathways and hinders the effective management and further optimization of clinical pathways.


Given this motivation, this paper presents a clinical pathway management platform, the Imperial Clinical Pathway Analyzer (ICPA). By extending the stochastic model performance evaluation process algebra (PEPA), ICPA introduces a clinical-pathway-specific model: clinical pathway PEPA (CPP). ICPA can simulate stochastic behaviours of a clinical pathway by extracting information from public clinical databases and other related documents using CPP. Thus, the performance of this clinical pathway, including its throughput, resource utilisation and passage time can be quantitatively analysed.


A typical clinical pathway on stroke extracted from a UK hospital is used to illustrate the effectiveness of ICPA. Three application scenarios are tested using ICPA: 1) redundant resources are identified and removed, thus the number of patients being served is maintained with less cost; 2) the patient passage time is estimated, providing the likelihood that patients can leave hospital within a specific period; 3) the maximum number of input patients are found, helping hospitals to decide whether they can serve more patients with the existing resource allocation.


ICPA is an effective platform for clinical pathway management: 1) ICPA can describe a variety of components (state, activity, resource and constraints) in a clinical pathway, thus facilitating the proper understanding of complexities involved in it; 2) ICPA supports the performance analysis of clinical pathway, thereby assisting hospitals to effectively manage time and resources in clinical pathway.