Garg, Lalit, McClean, Sally, Meenan, Brian and Millard, Peter (2011) Phase-Type Survival Trees and Mixed Distribution Survival Trees for Clustering Patients' Hospital Length of Stay. Informatica, 22 (1). pp. 57-72. [Journal article]
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Clinical investigators, health professionals and managers are often interested in developing criteria for clustering patients into clinically meaningful groups according to their expected length of stay. In this paper, we propose two novel types of survival trees; phase-type survival trees and mixed distribution survival trees, which extend previous work on exponential survival trees. The trees are used to cluster the patients with respect to length of stay where partitioning is based on covariates such as gender, age at the time of admission and primary diagnosis code. Likelihood ratio tests are used to determine optimal partitions. The approach is illustrated using nationwide data available from the English Hospital Episode Statistics (HES) database on stroke-related patients, aged 65 years and over, who were discharged from English hospitals over a 1-year period.
|Item Type:||Journal article|
|Keywords:||decision support, clinical databases, phases of care, estimating group, service time|
|Faculties and Schools:||Faculty of Computing & Engineering|
Faculty of Computing & Engineering > School of Computing and Information Engineering
Faculty of Computing & Engineering > School of Engineering
|Research Institutes and Groups:||Computer Science Research Institute|
Engineering Research Institute
Computer Science Research Institute > Information and Communication Engineering
Engineering Research Institute > Nanotechnology & Integrated BioEngineering Centre (NIBEC)
|Deposited By:||Professor Sally McClean|
|Deposited On:||15 Jul 2011 10:04|
|Last Modified:||15 Jul 2011 10:04|
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- Phase-Type Survival Trees and Mixed Distribution Survival Trees for Clustering Patients' Hospital Length of Stay. (deposited UNSPECIFIED)
- Phase-Type Survival Trees and Mixed Distribution Survival Trees for Clustering Patients' Hospital Length of Stay. (deposited 15 Jul 2011 10:04) [Currently Displayed]
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