Pediatric Trauma Assessment and Management Database: Leveraging Existing Data Systems to Predict Mortality and Functional Status after Pediatric Injury.

Abstract

Efforts to improve pediatric trauma outcomes need detailed data, optimally collected at lowest cost, to assess processes of care. We developed a novel database by merging 2 national data systems for 5 pediatric trauma centers to provide benchmarking metrics for mortality and non-mortality outcomes and to assess care provided throughout the care continuum. Trauma registry and Virtual Pediatric Systems, LLC (VPS) from 5 pediatric trauma centers were merged for children younger than 18 years discharged in 2013 from a pediatric ICU after traumatic injury. For inpatient mortality, we compared risk-adjusted models for trauma registry only, VPS only, and a combination of trauma registry and VPS variables (trauma registry+VPS). To estimate risk-adjusted functional status, we created a prediction model de novo through purposeful covariate selection using dichotomized Pediatric Overall Performance Category scale. Of 688 children included, 77.3% were discharged from the ICU with good performance or mild overall disability and 17.6% with moderate or severe overall disability or coma. Inpatient mortality was 5.1%. The combined dataset provided the best-performing risk-adjusted model for predicting mortality, as measured by the C-statistic, pseudo-R², and Akaike Information Criterion, when compared with the trauma registry-only model. The final Pediatric Overall Performance Category model demonstrated adequate discrimination (C-statistic = 0.896) and calibration (Hosmer-Lemeshow goodness-of-fit p = 0.65). The probability of poor outcomes varied significantly by site (p < 0.0001). Merging 2 data systems allowed for improved risk-adjusted modeling for mortality and functional status. The merged database allowed for patient evaluation throughout the care continuum on a multi-institutional level. Merging existing data is feasible, innovative, and has potential to impact care with minimal new resources.