Novel Claims-Based Outcome Phenotypes in Survivors of Pediatric Traumatic Brain Injury.

OBJECTIVE: For children hospitalized with acute traumatic brain injury (TBI), to use postdischarge insurance claims to identify: (1) healthcare utilization patterns representative of functional outcome phenotypes and (2) patient and hospitalization characteristics that predict outcome phenotype.

SETTING: Two pediatric trauma centers and a state-level insurance claim aggregator.

PATIENTS: A total of 289 children, who survived a hospitalization after TBI between 2009 and 2014, were in the hospital trauma registry, and had postdischarge insurance eligibility.

DESIGN: Retrospective cohort study.

MAIN MEASURES: Unsupervised machine learning to identify phenotypes based on postdischarge insurance claims. Regression analyses to identify predictors of phenotype.

RESULTS: Median age 5 years (interquartile range 2-12), 29% (84/289) female. TBI severity: 30% severe, 14% moderate, and 60% mild. We identified 4 functional outcome phenotypes. Phenotypes 3 and 4 were the highest utilizers of resources. Morbidity burden was highest during the first 4 postdischarge months and subsequently decreased in all domains except respiratory. Severity and mechanism of injury, intracranial pressure monitor placement, seizures, and hospital and intensive care unit lengths of stay were phenotype predictors.

CONCLUSIONS: Unsupervised machine learning identified postdischarge phenotypes at high risk for morbidities. Most phenotype predictors are available early in the hospitalization and can be used for prognostic enrichment of clinical trials targeting mitigation or treatment of domain-specific morbidities.