Please use this identifier to cite or link to this item:
|Title:||Identifying patient readmission subtypes from unplanned readmissions to hospitals in Hong Kong: A cluster analysis|
|Authors:||Chan, M.-F. |
|Citation:||Chan, M.-F., Wong, F.K.Y., Chang, K., Chow, S., Chung, L., Lee, W.-M., Lee, R. (2009). Identifying patient readmission subtypes from unplanned readmissions to hospitals in Hong Kong: A cluster analysis. Nursing and Health Sciences 11 (1) : 37-44. ScholarBank@NUS Repository. https://doi.org/10.1111/j.1442-2018.2009.00427.x|
|Abstract:||It has been conjectured with regard to patient readmission patterns that there might be significant differences in patient characteristics, need factors, enabling resources, and health behavior. The aim of this study was to identify the profiles of readmitted patients in Hong Kong (n = 120) based on their predisposing characteristics, needs, health behavior, and enabling resources. All the readmitted patients were recruited to the study in three hospitals from 2003 to 2005. A cluster analysis yielded three clusters: Clusters 1, 2, and 3 constituted 27.5% (n = 33), 27.5% (n = 33), and 45.0% (n = 54) of the total sample, respectively. The study results show that community nurse services do affect the rate at which patients are admitted to hospital for a second time. The findings might help by providing important information that will enable health-care policy-makers to identify strategies to target a specific group of patients in the hope of reducing its readmission rate. © 2009 The Authors Journal compilation © 2009 Blackwell Publishing Asia Pty Ltd.|
|Source Title:||Nursing and Health Sciences|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on Nov 14, 2018
WEB OF SCIENCETM
checked on Nov 6, 2018
checked on Oct 26, 2018
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.