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Using Phase-Type Models to Cost Stroke Patient Care Across Health, Social and Community Services

McClean, Sally I, Gillespie, Jennifer, Garg, Lalit, Barton, Maria, Scotney, Bryan and Fullerton, Ken (2014) Using Phase-Type Models to Cost Stroke Patient Care Across Health, Social and Community Services. European Journal of Operational Research190- (2014), 236 (1). pp. 190-199. [Journal article]

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URL: http://www.sciencedirect.com/science/article/pii/S0377221714001027

DOI: 10.1016/j.ejor.2014.01.063

Abstract

Stroke disease places a heavy burden on society, incurring long periods of time in hospital and community care, and associated costs. Also stroke is a highly complex disease with diverse outcomes and multiple strategies for therapy and care. Previously a modeling framework has been developed which clusters patients into classes with respect to their length of stay (LOS) in hospital. Phase-type models were then used to describe patient flows for each cluster. Also multiple outcomes, such as discharge to normal residence, nursing home, or death can be permitted. We here add costs to this model and obtain the Moment Generating Function for the total cost of a system consisting of multiple transient phase-type classes with multiple absorbing states. This system represents different classes of patients in different hospital and community services states. Based on stroke patients’ data from the Belfast City Hospital, various scenarios are explored with a focus on comparing the cost of thrombolysis treatment under different regimes. The overall modeling framework characterizes the behavior of stroke patient populations, with a focus on integrated system-wide costing and planning, encompassing hospital and community services. Within this general framework we have developed models which take account of patient heterogeneity and multiple care options. Such complex strategies depend crucially on developing a deep engagement with the health care professionals and underpinning the models with detailed patient-specific data.

Item Type:Journal article
Faculties and Schools:Faculty of Computing & Engineering
Faculty of Computing & Engineering > School of Computing and Information Engineering
Research Institutes and Groups:Computer Science Research Institute
Computer Science Research Institute > Information and Communication Engineering
ID Code:30876
Deposited By: Professor Sally McClean
Deposited On:21 Jan 2015 11:03
Last Modified:04 Mar 2015 16:17

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