Identifying patient readmission subtypes from unplanned readmissions to hospitals in Hong Kong: a cluster analysis.
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.
Chan
Moon-fai
MF
Alice Lee Centre for Nursing Studies, National University of Singapore, Singapore.
Wong
Frances K Y
FK
Chang
Katherine
K
Chow
Susan
S
Chung
Loretta
L
Lee
Wai-man
WM
Lee
Rance
R
D000203:Activities of Daily Living; D000328:Adult; D000367:Age Factors; D000368:Aged; D000704:Analysis of Variance; D002908:Chronic Disease / Q000628:therapy*; D016000:Cluster Analysis; D005260:Female; D015438:Health Behavior; D019538:Health Care Surveys; D006304:Health Status; D006723:Hong Kong; D006769:Hospitals, General / Q000706:statistics & numerical data; D006801:Humans; D015994:Incidence; D008297:Male; D008875:Middle Aged; D017063:Outcome Assessment, Health Care; D010359:Patient Readmission / Q000706:statistics & numerical data*; D011336:Probability; D018570:Risk Assessment; D012720:Severity of Illness Index; D012737:Sex Factors