Korean J Prev Med.  1999 Sep;32(3):289-296.

A Case-control Study of Unexpected Readmission in a University Hospital

Affiliations
  • 1Department of Health Services Administration, Yuhan College, Korea.
  • 2Department of Preventive Medicine, College of Medicine, Yonsei University, Korea.

Abstract


OBJECTIVES
This study describes the risk factors affecting the unexpected readmission of 261 patients who were discharged from a university hospital in Seoul.
METHODS
This case-control study reviewed medical records of inpatients who had been discharged from a hospital between 1 August 1995 and 31 October 1995 after the treatment for general diseases. The cases were 68 patients who were readmitted unexpectedly within 28 days of discharge from an index stay, and the controls were 193 patients who were discharged without readmission during the study period.
RESULTS
Logistic regression analysis results were as follows; Patients who had no operation during their hospital stay were more likely to be readmitted unexpectedly than patients who had operation. Patients who had 1 or 2 parts of their body being involved in treatment were more likely to be readmitted unexpectedly than patients who hand more than 3 parts of their body being involved in treatment. Patients who had complications after surgery were more likely to be readmitted unexpectedly than patients who had no complications. Insufficient discharge planning caused unexpected readmissions.
CONCLUSIONS
Discharge planning education should be extended to health care providers. And the assessment of discharge planning should be evaluated. Readmission is often necessary for the treatment of related problems originating from initial hospitalization, which causes cost problems. Unexpected readmission is preventable and the models for readmission can serve as a valuable clinical tool for high risk patients.

Keyword

Unexpected readmission; Quality of care

MeSH Terms

Case-Control Studies*
Education
Hand
Health Personnel
Hospitalization
Humans
Inpatients
Length of Stay
Logistic Models
Medical Records
Patient Discharge
Risk Factors
Seoul
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