title: The impact of injury coding schemes on predicting hospital mortality after pediatric injury.
abstract: OBJECTIVE
  Accurate adjustment for injury severity is needed to evaluate the effectiveness of trauma management. While the choice of injury coding scheme used for modeling affects performance, the impact of combining coding schemes on performance has not been evaluated. The purpose of this study was to use Bayesian logistic regression to develop models predicting hospital mortality in injured children and to compare the performance of models developed using different injury coding schemes.
  
  
  METHODS
  Records of children (age < 15 years) admitted after injury were obtained from the National Trauma Data Bank (NTDB) and the National Pediatric Trauma Registry (NPTR) and used to train Bayesian logistic regression models predicting mortality using three injury coding schemes (International Classification of Disease-9th revision [ICD-9] injury codes, the Abbreviated Injury Scale [AIS] severity scores, and the Barell matrix) and their combinations. Model performance was evaluated using independent data from the NTDB and the Kids' Inpatient Database 2003 (KID).
  
  
  RESULTS
  Discrimination was optimal when modeling both ICD-9 and AIS severity codes (area under the receiver operating curve [AUC] = 0.921 [NTDB] and 0.967 [KID], Hosmer-Lemeshow [HL] h-statistic = 115 [NTDB] and 147 [KID]), while calibration was optimal when modeling coding based on the Barell matrix (AUC = 0.882 [NTDB] and 0.936 [KID], HL h-statistic = 19 [NTDB] and 69 [KID]). When compared to models based on ICD-9 codes alone, models that also included AIS severity scores and coding from the Barell matrix showed improved discrimination and calibration.
  
  
  CONCLUSIONS
  Mortality models that incorporate additional injury coding schemes perform better than those based on ICD-9 codes alone in the setting of pediatric trauma. Combining injury coding schemes may be an effective approach for improving the predictive performance of empirically derived estimates of injury mortality.
authors: Division of Trauma and Burns, Children's National Medical Center, Washington, DC, USA. rburd@cnmc.org
authors: Randall S
authors: RS
authors: Burd
authors: David
authors: D
authors: Madigan
mesh_terms: D000293:Adolescent; D019540:Area Under Curve; D001499:Bayes Theorem; D002648:Child; D002675:Child, Preschool; D005260:Female; D017052:Hospital Mortality; D006801:Humans; D007223:Infant; D007231:Infant, Newborn; D038801:International Classification of Diseases; D016015:Logistic Models; D008297:Male; D011237:Predictive Value of Tests; D012042:Registries; D012189:Retrospective Studies; D015599:Trauma Severity Indices; D014947:Wounds and Injuries / Q000401:mortality*