title: Emergency department orthopedics observation unit as an alternative to admission.
abstract: OBJECTIVE
  Inclusion of select orthopedic problems in the orthopedics observation unit (OOU) may reduce hospital admissions. Our system allows OOU status for 24 hours, but the effect on admissions is unknown. Our primary hypothesis was that we could predict which OOU patients required admission based on the presence of uncontrolled pain.
  
  
  METHODS
  Data were prospectively collected for all OOU patients in this prospective observational study, including data on extremity cellulitis, fractures, and spine injuries awaiting brace placement.The primary outcome variable was admission to the hospital versus discharge home. The a priori hypotheses were that patients with more persistent or worsening pain would require admission more often and that the OOU would result in fewer patients needing a costlier inpatient admission to the hospital. An a priori power analysis showed adequate power of 80% to detect a difference between admitted and discharged patients.
  
  
  RESULTS
  Data were prospectively collected from August 2011 to August 2012 for 199 consecutive OOU patients, 62% of whom were men. Diagnoses included infection (cellulitis or abscess of extremity) in 76%, fracture in 15% and other in 9% of the patients. Sixty-two patients (31%) were admitted and 7 patients (4%) made return visits for the same problem within a 30-day period. No significant relations existed between any of the independent variables and admission on bivariate analysis. Multivariable logistic regression found no significant predictors of hospital admission. Logistic regression was not performed on 30-day returns because of the low event rate (4%).
  
  
  CONCLUSIONS
  An OOU prevented 138 of 199 (69%) patients from being admitted to a hospital. There were no significant predictors of which patients would require admission. Pain was not a predictor of need for admission. The lack of significant predictors is important in suggesting that without the ability to predict which patients require admission, a system using an OOU can reduce admissions by more than two-thirds.
authors.affiliation: From the Department of Emergency Medicine, University of New Mexico, Albuquerque.
authors.forename: Amy A
authors.initials: AA
authors.lastname: Ernst
authors.affiliation: From the Department of Emergency Medicine, University of New Mexico, Albuquerque.
authors.forename: Jaime
authors.initials: J
authors.lastname: Jones
authors.affiliation: From the Department of Emergency Medicine, University of New Mexico, Albuquerque.
authors.forename: Steven J
authors.initials: SJ
authors.lastname: Weiss
authors.affiliation: From the Department of Emergency Medicine, University of New Mexico, Albuquerque.
authors.forename: Otono
authors.initials: O
authors.lastname: Silva
mesh_terms: D000328:Adult; D002481:Cellulitis / Q000150:complications / Q000628:therapy*; D003661:Decision Support Techniques; D004636:Emergency Service, Hospital / Q000458:organization & administration*; D005260:Female; D005500:Follow-Up Studies; D050723:Fractures, Bone / Q000150:complications / Q000628:therapy*; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D009985:Orthopedics / Q000458:organization & administration*; D010146:Pain / Q000209:etiology; D010343:Patient Admission / Q000706:statistics & numerical data*; D011446:Prospective Studies; D013124:Spinal Injuries / Q000150:complications / Q000628:therapy*