title: Specifications for calculation of risk-adjusted odds of death using trauma registry data.
abstract: BACKGROUND
  Logistic regression models, with coefficients developed from normative populations, can be applied to a trauma registry cohort to predict the risk-adjusted frequency of death. Quality of care is judged based on differences between predicted and observed mortality frequency. The goal of these analyses was to determine if decedents who died in the emergency department had independent variables associated with risk of death identical to those who died after hospital admission.
  
  
  METHODS
  This case-control study is based upon decedents in a trauma registry matched to survivors. Backward stepwise linear logistic regression models contained independent variables selected to reflect patients' status before treatment.
  
  
  RESULTS
  Beta coefficients and independent variables selected for models of expired emergency department patients were different from those of hospital death patients.
  
  
  CONCLUSIONS
  To achieve a more precise determination of risk-adjusted mortality for injured patients at a trauma center, two separate analyses are appropriate: death in emergency department and death after hospital admission.
authors.affiliation: Department of Surgery, Oregon Health Sciences University, Portland 97201-3098, USA.
authors.forename: R J
authors.initials: RJ
authors.lastname: Mullins
authors.forename: N C
authors.initials: NC
authors.lastname: Mann
authors.forename: D M
authors.initials: DM
authors.lastname: Brand
authors.forename: B S
authors.initials: BS
authors.lastname: Lenfesty
mesh_terms: D000293:Adolescent; D000328:Adult; D000367:Age Factors; D000368:Aged; D016022:Case-Control Studies; D004636:Emergency Service, Hospital; D005260:Female; D017052:Hospital Mortality; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D016017:Odds Ratio; D012044:Regression Analysis; D012307:Risk Factors; D012737:Sex Factors; D014947:Wounds and Injuries / Q000401:mortality*