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Pediatric Trauma Assessment and Management Database: Leveraging Existing Data Systems to Predict Mortality and Functional Status after Pediatric Injury. J Am Coll Surg 2017 May;224(5):933-944.e5

Date

02/27/2017

Pubmed ID

28235647

Pubmed Central ID

PMC6475528

DOI

10.1016/j.jamcollsurg.2017.01.061

Scopus ID

2-s2.0-85016070243   6 Citations

Abstract

BACKGROUND: 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.

STUDY DESIGN: 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.

RESULTS: 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).

CONCLUSIONS: 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.

Author List

Flynn-O'Brien KT, Fallat ME, Rice TB, Gall CM, Nance ML, Upperman JS, Gourlay DM, Crow JP, Rivara FP

Authors

Katherine T. Flynn-O'Brien MD, MPH Assistant Professor in the Surgery department at Medical College of Wisconsin
David M. Gourlay MD Chief, Professor in the Surgery department at Medical College of Wisconsin




MESH terms used to index this publication - Major topics in bold

Child
Child, Preschool
Databases, Factual
Female
Hospital Mortality
Humans
Infant
Intensive Care Units, Pediatric
Male
Predictive Value of Tests
Recovery of Function
Risk Assessment
Trauma Centers
Treatment Outcome
United States
Wounds and Injuries