Development and Prospective Validation of Tools to Accurately Identify Neurosurgical and Critical Care Events in Children With Traumatic Brain Injury*

Abstract

Objective To develop and validate case definitions (“computable phenotypes”) to accurately identify neurosurgical and critical care events in children with traumatic brain injury (TBI). Design Prospective observational cohort study, May 2013 – September 2015 Setting Two large U.S. children’s hospitals with level 1 Pediatric Trauma Centers Participants 174 children < 18 years old admitted to an intensive care unit (ICU) after TBI Methods Prospective data were linked to database codes for each patient. The outcomes were prospectively identified acute TBI, intracranial pressure monitor placement, craniotomy or craniectomy, vascular catheter placement, invasive mechanical ventilation, and new gastrostomy tube or tracheostomy placement. Candidate predictors were database codes present in administrative, billing, or trauma registry data. For each clinical event, we developed and validated penalized regression and Boolean classifiers (models to identify clinical events that take database codes as predictors). We externally validated the best model for each clinical event. The primary model performance measure was accuracy, the percent of test patients correctly classified. Results The cohort included 174 children who required ICU admission after TBI. Simple Boolean classifiers were ≥ 94% accurate for 7/9 clinical diagnoses and events. For central venous catheter placement, no classifier achieved 90% accuracy. Classifier accuracy was dependent on available data fields. 5/9 classifiers were acceptably accurate using only administrative data, but three required trauma registry fields and two required billing data. Conclusions In children with TBI, computable phenotypes based on simple Boolean classifiers were highly accurate for most neurosurgical and critical care diagnoses and events. The computable phenotypes we developed and validated can be utilized in any observational study of children with TBI, and can reasonably be applied in studies of these interventions in other patient populations.

Why Everyone Should Care About “Computable Phenotypes”*

“…In this issue of the Journal , Bennett et al(1) report a prospective validation of administrative, billing and trauma registry coding data carried out with the purpose of generating a “computable phenotype” for most neurosurgical and critical care events in children with traumatic brain injury (TBI). This paper is important and potentially transformative for the whole field of pediatric critical care.…”

“…Bennett et al(1) introduce us to the idea of “computable phenotypes”. That is, the ability to first define a condition, disease, patient characteristic or clinical event using only data processed by computer(11).…”

“…This intervention is undoubtedly being used, but how could we harness information about its use in an EHR-based CER study? Certainly not at the moment, but Bennett et al(1) provide us with some of the tools. For example, they have used ICD-9-CM and other administrative database resources to develop and test an algorithm/model that would accurately identify individuals with TBI in the PICU who underwent intracranial pressure monitoring or craniotomy/craniectomy.…”

“…What is evident in both of these examples is that a single ICD-9-CM code was not adequate for purpose. Rather, Bennett et al(1) found that a combination of coding and administrative data sources was required. The fact that no single data source or code was 100% specific and 100% sensitive reflects the prior discussion about the primary purpose of coding, and who does it.…”

“…At the moment, Bennett et al(1) may have tested their models in a number of patients, but our focus should be on the equally important issue of the number of centers used with their respective medical coding and billing administrations (i.e., raters) that generated the data for the sources examined. It was only two, and if multiple hospitals and PICUs are to be used in a future CER study, then each additional center will need to demonstrate consistency of phenotype definition – similar to an operating procedure for “case definition” or inclusions/exclusions of current research network studies.…”