title: Reduction in mortality after inappropriate early discharge from intensive care unit: logistic regression triage model.
abstract: OBJECTIVE
  To develop a predictive model to triage patients for discharge from intensive care units to reduce mortality after discharge.
  
  
  METHODS
  Logistic regression analyses and modelling of data from patients who were discharged from intensive care units.
  
  
  METHODS
  Guy's hospital intensive care unit and 19 other UK intensive care units from 1989 to 1998.
  
  
  METHODS
  5475 patients for the development of the model and 8449 for validation.
  
  
  METHODS
  Mortality after discharge and power of triage model.
  
  
  RESULTS
  Mortality after discharge from intensive care was up to 12.4%. The triage model identified patients at risk from death on the ward with a sensitivity of 65.5% and specificity of 87.6%, and an area under the receiver operating curve of 0.86. Variables in the model were age, end stage disease, length of stay in unit, cardiothoracic surgery, and physiology. In the validation dataset the 34% of the patients identified as at risk had a discharge mortality of 25% compared with a 4% mortality among those not at risk.
  
  
  CONCLUSIONS
  The discharge mortality of at risk patients may be reduced by 39% if they remain in intensive care units for another 48 hours. The discharge triage model to identify patients at risk from too early and inappropriate discharge from intensive care may help doctors to make the difficult clinical decision of whom to discharge to make room for a patient requiring urgent admission to the unit. If confirmed, this study has implications on the provision of resources.
authors.affiliation: St Thomas's Hospital, London SE1 7EH.
authors.forename: K
authors.initials: K
authors.lastname: Daly
authors.forename: R
authors.initials: R
authors.lastname: Beale
authors.forename: R W
authors.initials: RW
authors.lastname: Chang
mesh_terms: D018806:APACHE; D016009:Chi-Square Distribution; D003422:Critical Care / Q000145:classification*; D017052:Hospital Mortality; D006801:Humans; D007362:Intensive Care Units / Q000592:standards / Q000706:statistics & numerical data*; D007902:Length of Stay; D016015:Logistic Models; D010351:Patient Discharge / Q000592:standards; D010360:Patient Transfer / Q000592:standards*; D010362:Patients' Rooms; D018570:Risk Assessment; D014218:Triage / Q000379:methods*; D006113:United Kingdom / Q000453:epidemiology