Please use this identifier to cite or link to this item:
Title: Modelling stroke patient pathways using survival analysis and simulation modelling
Authors: Barton, Maria
McClean, Sally
Garg, Lalit
Fullerton, Ken
Keywords: Medical care
Cerebrovascular disease -- Patients
Hospital utilization -- Length of stay
Issue Date: 2009
Publisher: ASMDA
Citation: Barton, M., McClean, S. I., Garg, L., & Fullerton, K. (2009). Modelling stroke patient pathways using survival analysis and simulation modelling. XIII International Conference on Applied Stochastic Models and Data Analysis, Vilnius. 370-373.
Abstract: Stroke disease is the third leading cause of death in the UK, placing a heavy burden on society at a cost of 7 billion pounds per year. Prolonged length of stay in hospital is considered to be an inefficient use of hospital resources. In this paper we present results of survival analysis that utilise length of stay and destination as outcome measures, based on data from the Belfast City Hospital. Survival probabilities were determined using Kaplan-Meier survival curves and log rank tests. Multivariate Cox proportional hazards models were also fitted to identify independent predictors of length of stay including age, gender and diagnosis. Elderly patients showed a decreased hazard ratio of discharge. However, gender was not a significant hazard risk for length of stay in hospital. Those patients with a diagnosis of cerebral haemorrhage showed an increased hazard ratio and hence were most likely to have a shorter length of stay and to die in hospital. Those who were eventually discharged to a Private Nursing Home had the lowest probability of early discharge. On the basis of these results we have created several groups, stratified by age, gender diagnosis and destination. These groups are then used to form the basis of a simulation model where each group is a patient pathway within the simulation. Various scenarios are explored with a particular focus on the potential efficiency gains if length of stay in hospital, prior to discharge to a Private Nursing Home, can be reduced.
ISBN: 9789955-284635
Appears in Collections:Scholarly Works - FacICTCIS

Files in This Item:
File Description SizeFormat 
Modelling_Stroke_Patient_Pathways_using.pdf337.92 kBAdobe PDFView/Open

Items in OAR@UM are protected by copyright, with all rights reserved, unless otherwise indicated.