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J Trauma. 2011 Jan;70(1):130-4; discussion 134-5. doi: 10.1097/TA.0b013e3182032b34.

The impact of insurance status on actuarial survival in hospitalized trauma patients: when do they die?

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  • 1Department of Surgery, Howard University College of Medicine, Washington, District of Columbia, USA.

Erratum in

  • J Trauma. 2011 Feb;70(2):525. Cornwell, Edward E 3rd [added].



Previous work has suggested that insurance status, gender, and ethnicity all have an independent association with mortality after trauma. The purpose of this study is to investigate whether these factors exerted survival impact that could be observed throughout the hospital stay.


Using the National Trauma Data Bank (version 7.0), a Cox proportional hazards survival analysis was performed on young (19-30 years old) trauma patients to mitigate the impact of comorbid confounders. Variables included in the model were age, gender, ethnicity, Injury Severity Score, presence of shock at presentation, mechanism of injury, insurance status, year of admission, teaching status of the hospital, diagnosis of substance abuse or psychotic disorders, and complications after admission. Rate ratios (RRs) comparing the slopes of the adjusted survival curves were calculated using the Mantel-Cox method.


A total of 192,488 young trauma patients were identified with complete data. Increased hazard of death was seen in patients who were uninsured (hazard ratio [HR]=1.69, 95% confidence interval [CI]=1.59-1.80, p<0.001), of a minority ethnicity (HR=1.08, 95% CI=1.01-1.15, p=0.025) or men (HR=1.14, 95% CI=1.04-1.23, p=0.004). RRs were significantly larger between insurance status (RR=1.75, 95% CI=1.58-1.94, p<0.001) than between race (RR=1.23, 95% CI=1.10-1.37, p<0.001) or between gender (RR=1.16, 95% CI=1.01-1.32, p=0.030).


Risk of death on the first hospital day after injury differs by insurance status, and this disparity becomes more pronounced throughout the hospital stay. Further study is necessary to determine whether this is a result of additional unmeasured patient covariates with insurance status or a difference in provider behavior in response to patient insurance status.

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