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In our previous work we proposed a phase type survival tree method for clustering patients into clinically meaningful patient groups. We also discussed its extension which uses the survival tree based analysis for patient pathway prognostication and to examine the relationship between length of stay in hospital and destination on discharge. The current paper illustrates how phase type survival tree...
Survival tree based analysis is a powerful method of prognostication and determining clinically meaningful patient groups from a given dataset of patients' length of stay. In our previous work [1, 2] we proposed a phase type survival tree method for clustering patients into homogeneous groups with respect to their length of stay where partitioning is based on covariates representing patient characteristics...
Stroke is the major cause of disability in the UK, costing the economy ??7 billion per annum. Prolonged length of stay (LOS) in hospital is considered to be an inefficient use of resources and is in part due to bed blocking. We present results of survival analyses utilising LOS and destination as outcome measures, based on data from the Belfast City Hospital. On the basis of these results we have...
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