The influence of clinical, treatment, and healthcare system characteristics on psychiatric readmission of adolescents

Am J Orthopsychiatry. 2008 Apr;78(2):187-98. doi: 10.1037/a0012557.


This study examined predictors of readmission for a sample of 522 adolescents enrolled in Medicaid and admitted to three inpatient psychiatric hospitals in Maryland. Comprehensive data on clinical, treatment, and health care system characteristics were collected from archival sources (medical records, Medicaid claims, and the Area Resource File). Predictors of readmission were examined with bivariate (Kaplan Meier) and multivariate (Cox Regression) survival techniques. One-year readmission rates were 38% with the majority occurring within 3 months after discharge. Adolescent demographic (age and gender), clinical (severity of symptoms, comorbidity, suicidality) and family characteristics (level of family risk) were associated with readmission. However, treatment factors including type of aftercare, postdischarge living environment, medication noncompliance, and hospital provider were among the strongest predictors of readmission. Study findings underscore the importance of careful discharge planning and linkage to appropriate aftercare. The differing rates of readmission across hospitals also suggest that organizational level factors may play a vital role in determining treatment outcomes.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adolescent
  • Aftercare
  • Delivery of Health Care / classification
  • Delivery of Health Care / methods
  • Delivery of Health Care / statistics & numerical data*
  • Hospitalization / statistics & numerical data
  • Hospitals, Psychiatric / statistics & numerical data*
  • Humans
  • Length of Stay
  • Medicaid
  • Mental Disorders / diagnosis
  • Mental Disorders / psychology
  • Mental Disorders / therapy*
  • Patient Admission
  • Patient Compliance
  • Patient Discharge
  • Patient Readmission*
  • Probability
  • Proportional Hazards Models
  • United States