title: Factors contributing to hospital readmission in a Hong Kong regional hospital: a case-controlled study.
abstract: BACKGROUND
  As many as 50% of total hospital admissions are readmissions. Because the factors contributing to hospital readmission are multiple, and research findings are not conclusive, it is important for clinicians to gain an understanding of the key factors that contribute to readmission.
  
  
  OBJECTIVE
  This study explores the factors contributing to hospital readmission and derives an explanatory model that can best identify characteristics of patients at high risk for hospital readmission.
  
  
  METHODS
  This research was a case-controlled study with readmitted patients (n = 168) as the readmitted group and non-readmitted patients (n = 98) as the control group. The variables included demographic data, health assessment data, medical diagnosis, frequency of admissions, severity of illness, intensity of service and improvement of condition. The study sample was also interviewed to explore the patients' views on their repeated hospitalization.
  
  
  RESULTS
  In the bivariate analysis significant differences between the study and control groups were multiple and generally consistent with findings in other studies. Using multiple logistic regression, however, the final model shows that only three factors best predict readmissions: frequency (3-4 times) of readmissions (OR = 9.96, p < .0001) and frequency (more than 5 times) of readmissions (OR = 15.73, p < .0001), financial assistance (OR = 5.03, p < .001), and severity of illness (OR = 3.12, p < .01). Our interview data suggest that the readmitted patients required assistance to accomplish daily living activities upon discharge and often returned to the hospital for the same health reason.
  
  
  CONCLUSIONS
  The study findings suggest that patients who are frequently readmitted to the hospital are severely ill; are on public assistance; and may need special attention when discharged in order to attenuate repeated hospital readmission.
authors.affiliation: Department of Nursing and Health Sciences, The Hong Kong Polytechnic University, Hunghom, China. hsfwong@polyu.edu.hk
authors.forename: FrancesKamYuet
authors.initials: F
authors.lastname: Wong
authors.forename: May
authors.initials: M
authors.lastname: Ho
authors.forename: Iry
authors.initials: I
authors.lastname: Chiu
authors.forename: Wai Kong
authors.initials: WK
authors.lastname: Lui
authors.forename: Cecilia
authors.initials: C
authors.lastname: Chan
authors.forename: Kit Ming
authors.initials: KM
authors.lastname: Lee
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D016022:Case-Control Studies; D005260:Female; D006723:Hong Kong / Q000453:epidemiology; D006786:Hospitals, Urban / Q000706:statistics & numerical data*; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D010347:Patient Care Planning; D010351:Patient Discharge; D010359:Patient Readmission / Q000706:statistics & numerical data*; D012307:Risk Factors