Identifying patient readmission subtypes from unplanned readmissions to hospitals in Hong Kong: A cluster analysis

Moon Fai Chan, Kam Yuet Wong, Ka Pik Katherine Chang, Susan Chow, Loretta Chung, Wai Man Lee, Rance Lee

Research output: Journal article publicationJournal articleAcademic researchpeer-review

7 Citations (Scopus)

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.
Original languageEnglish
Pages (from-to)37-44
Number of pages8
JournalNursing and Health Sciences
Volume11
Issue number1
DOIs
Publication statusPublished - 26 Mar 2009

Keywords

  • Cluster analysis
  • Unplanned readmission

ASJC Scopus subject areas

  • Nursing(all)

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