Unmeasured Confounding in Observational Studies with Multiple Treatment Arms: Comparing Emergency Department Mortality of Severe Trauma Patients by Trauma Center Level.

Abstract

Comparing emergency department mortality across different levels of trauma care (nontrauma centers, level I and II centers) is important in evaluating regionalized care. Patient population characteristics differ across different levels of trauma care and it is essential to adjust for baseline covariates to make valid comparisons. Propensity score matching has been established as a more robust method to infer causal relationship in observational studies than conventional regression adjustment. We designed and implemented a three group matching methodology. First, we conducted optimal pair matching between the treatment group (nontrauma centers) and the first control group (level I trauma centers); second, we conducted optimal pair matching between the nontrauma centers and the second control group (level II trauma centers); the final step was to link the two sets of matched pairs by the common treatment subjects to form matched triplets. We then implemented a sensitivity analysis with three treatment arms, Lu's imputation based method, to assess the impact due to potential unmeasured confounding. The results showed that if the most severe adult trauma patients treated in nontrauma centers were to be treated in level I or II trauma centers, the odds of emergency department death would be reduced dramatically (odds ratio [OR] = 0.61 and 0.49). There was no difference between being treated in level I or II trauma centers. The sensitivity analysis revealed that the positive association between being treated at level I or II trauma centers and the reduced odds of mortality would remain present even in the presence of strong unmeasured confounding.