Redefining readmission risk factors for general medicine patients

J Hosp Med. 2011 Feb;6(2):54-60. doi: 10.1002/jhm.805. Epub 2010 Oct 12.


Background: Readmissions are costly both financially for our healthcare system and emotionally for our patients. Identifying factors that increase risk for readmissions may be helpful to focus resources to optimize the discharge process and reduce avoidable readmissions.

Objective: To identify factors associated with readmission within 30 days for general medicine patients.

Methods: We performed a retrospective observational study of an administrative database at an urban 550-bed tertiary care academic medical center. Cohort patients were discharged from the general medicine service over a 2-year period from June 1, 2006, to May 31, 2008. Clinical, operational, and sociodemographic factors were evaluated for association with readmission.

Results: Our cohort included 10,359 consecutive admissions (6805 patients) discharged from the general medicine service. The 30-day readmission rate was 17.0%. In multivariate analysis, factors associated with readmission included black race (odds ratio [OR], 1.43; 95% confidence interval [CI], 1.24-1.65), inpatient use of narcotics (1.33; 1.16-1.53) and corticosteroids (1.24; 1.09-1.42), and the disease states of cancer (with metastasis 1.61; 1.33-1.95; without metastasis 1.95; 1.54-2.47), renal failure (1.19; 1.05-1.36), congestive heart failure (1.30; 1.09-1.56), and weight loss (1.26; 1.09-1.47). Medicaid payer status (1.15; 0.97-1.36) had a trend toward readmission.

Conclusion: Readmission of general medicine patients within 30 days is common and associated with several easily identifiable clinical and nonclinical factors. Identification of these risk factors can allow providers to target interventions to reduce potentially avoidable readmissions.

MeSH terms

  • Academic Medical Centers / statistics & numerical data
  • Continuity of Patient Care / statistics & numerical data*
  • Female
  • Humans
  • Male
  • Middle Aged
  • Multivariate Analysis
  • Patient Discharge / statistics & numerical data*
  • Patient Readmission / statistics & numerical data*
  • Prescription Drugs
  • Primary Health Care / methods*
  • Primary Health Care / statistics & numerical data
  • Retrospective Studies
  • Risk Factors
  • United States
  • Urban Population / statistics & numerical data


  • Prescription Drugs