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BMC Bioinformatics

, 13:S4

First Online: 07 September 2012

Abstract

BackgroundHospitals 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.

MethodGiven 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.

ResultsA 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.

ConclusionsICPA 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.

Xian Yang, Rui Han, Jeremy Bradley, Benita Cox, Robert Dickinson and Richard Kitney contributed equally to this work.

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Autor: Xian Yang - Rui Han - Yike Guo - Jeremy Bradley - Benita Cox - Robert Dickinson - Richard Kitney

Fuente: https://link.springer.com/







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