title: Insurance type, not race, predicts mortality after pediatric trauma.
abstract: BACKGROUND
  In adult trauma, mortality varies with race and insurance status. In the elderly, insurance type has little impact on mortality after trauma and the influence of race is reduced. How race and insurance affect pediatric trauma requires further attention. We hypothesized that mortality after pediatric trauma is influenced by insurance type and not race.
  
  
  METHODS
  We reviewed all cases of blunt trauma in children ≤13 y requiring admission, using the National Trauma Data Bank Research Data Sets for 2007 and 2008. Exclusions included an Abbreviated Injury Score of 6 for any body region, dead on arrival, and missing data. Our primary outcome measure was in-hospital mortality.
  
  
  RESULTS
  We identified 831 Asian (1.2%), 10,592 black (15.5%), 45,173 white (66.2%), and 8498 Hispanic (12.5%) children, and 3161 children (4.6%) classified as other race. Mean age was 7.4 ± 4.5 y, 11.9% were uninsured, and overall in-hospital mortality was 1.4%. Multivariable modeling indicated that race was not associated with increased mortality (Asian versus white, adjusted odds ratio [AOR] 1.05, P = 0.88; black versus white, AOR 0.92, P = 0.42; Hispanic versus white, AOR 0.87, P = 0.26; and other race versus white, AOR 1.01, P = 0.96). In contrast, insurance status (any insurance versus no insurance, AOR 0.6, P < 0.01) and insurance type (private insurance versus no insurance, AOR 0.47, P < 0.01; Medicaid versus no insurance, 0.67, P < 0.01) predicted reduced mortality.
  
  
  CONCLUSIONS
  Insurance status and insurance type are important predictors of mortality after pediatric trauma while, in contrast, race is not.
authors.affiliation: Division of Trauma and Critical Care, Department of Surgery, Cedars-Sinai Medical Center, Los Angeles, California 90048, USA.
authors.forename: Scott S
authors.initials: SS
authors.lastname: Short
authors.forename: Douglas Z
authors.initials: DZ
authors.lastname: Liou
authors.forename: Matthew B
authors.initials: MB
authors.lastname: Singer
authors.forename: Matthew B
authors.initials: MB
authors.lastname: Bloom
authors.forename: Daniel R
authors.initials: DR
authors.lastname: Margulies
authors.forename: Marko
authors.initials: M
authors.lastname: Bukur
authors.forename: Ali
authors.initials: A
authors.lastname: Salim
authors.forename: Eric J
authors.initials: EJ
authors.lastname: Ley
mesh_terms: D001213:Asian / Q000706:statistics & numerical data; D044383:Black People / Q000706:statistics & numerical data; D002648:Child; D002675:Child, Preschool; D016208:Databases, Factual / Q000706:statistics & numerical data; D005260:Female; D006630:Hispanic or Latino / Q000706:statistics & numerical data; D017052:Hospital Mortality; D006801:Humans; D007348:Insurance, Health / Q000706:statistics & numerical data*; D008297:Male; D008484:Medicaid / Q000706:statistics & numerical data*; D015999:Multivariate Analysis; D011237:Predictive Value of Tests; D044469:Racial Groups / Q000706:statistics & numerical data*; D012189:Retrospective Studies; D014481:United States / Q000453:epidemiology; D044465:White People / Q000706:statistics & numerical data; D014947:Wounds and Injuries / Q000208:ethnology* / Q000401:mortality*; D001741:Black or African American
keywords: Insurance status; Insurance type; Mortality; Pediatric; Race; Trauma