Investigating early readmission as an indicator for quality of care studies

Med Care. 1991 Apr;29(4):377-94. doi: 10.1097/00005650-199104000-00006.


Readmission to a hospital shortly following a previous discharge may be viewed as an adverse outcome of care. Consequently, early readmission represents a potentially useful indicator for monitoring quality. While a number of recent research studies have focused on this issue, several important questions concerning appropriate use of early readmission as a quality of care indicator remain to be addressed. In this article, using data on all discharges for 1 year from 18 hospitals, several of these questions are investigated. Specifically, whether the significant predictors of readmission risk are different for different types of cases (defined using DRGs), whether case severity is an important predictor of readmission risk, whether readmission risks differ systematically with hospital size and other characteristics, whether readmission risk is a function of patients' lengths-of-stay, and whether readmission risk is influenced by whether or not patients are discharged home or into organized care environments are explored. For this study, the focus is on patients who experienced unplanned readmissions to acute care hospitals within 31 days of a prior discharge. The Patient Management Category classification system and ICD-9-CM diagnosis and procedure codes are used to identify, and then exclude from consideration, those readmissions that occurred as part of an appropriately planned sequence of care. In each of 22 sets of related DRGs, analysis of unplanned readmissions indicates that severity/complexity is an important risk factor for early readmission and that clinical and other risk factors differ for different DRG groups. Thus, in future studies of early readmissions, researchers will need to control for both the type (e.g., DRG) and severity/complexity of individual cases. In examining relationships between early readmission and hospital characteristics, no consistent patterns suggestive of quality of care problems were detected.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Age Factors
  • Diagnosis-Related Groups / statistics & numerical data
  • Female
  • Health Services Research / methods
  • Hospitals / standards*
  • Hospitals / statistics & numerical data
  • Humans
  • Logistic Models
  • Male
  • Michigan
  • Patient Readmission / statistics & numerical data*
  • Quality of Health Care / statistics & numerical data*
  • Racial Groups
  • Severity of Illness Index
  • Sex Factors