Risk of Adverse Outcomes Among Veterans Who Screen Positive for Traumatic Brain Injury in the Veterans Health Administration But Do Not Complete a Comprehensive Evaluation: A LIMBIC-CENC Study

Abstract: Objective: To examine whether post-9/11 veterans who screened positive for mild traumatic brain injury (mTBI) but did not complete a Comprehensive TBI Evaluation (CTBIE) were at higher risk of subsequent adverse events compared with veterans who screened positive and completed a CTBIE. Upon CTBIE completion, information assessed by a trained TBI clinician indicates whether there is mTBI history (mTBI+) or not (mTBI-). Setting: Veterans Health Administration (VHA) outpatient services. Participants: A total of 52 700 post-9/11 veterans who screened positive for TBI were included. The follow-up review period was between fiscal years 2008 and 2019. The 3 groups studied based on CTBIE completion and mTBI status were: (1) mTBI+ (48.6%), (2) mTBI- (17.8%), and (3) no CTBIE (33.7%). Design: This was a retrospective cohort study. Log binomial and Poisson regression models adjusting for demographic, military, pre-TBI screening health, and VHA covariates examined risk ratios of incident outcomes based on CTBIE completion and mTBI status. Main measures: Incident substance use disorders (SUDs), alcohol use disorder (AUD), opioid use disorder (OUD), overdose, and homelessness documented in VHA administrative records, and mortality as documented in the National Death Index, 3 years post-TBI screen. VHA outpatient utilization was also examined. Results: Compared with the no CTBIE group, the mTBI+ group had 1.28 to 1.31 times the risk of incident SUD, AUD, and overdose, but 0.73 times the risk of death 3 years following TBI screening. The mTBI- group had 0.70 times the risk of OUD compared with the no CTBIE group within the same period. The no CTBIE group also had the lowest VHA utilization. Conclusions: There were mixed findings on risk of adverse events for the no CTBIE group relative to the mTBI+ and mTBI- groups. Future research is needed to explore the observed differences, including health conditions and healthcare utilization, documented outside VHA among veterans who screen positive for TBI.

Read the full article
Report a problem with this article

Related articles

  • More for Researchers

    Identifying opioid relapse during COVID-19 using natural language processing of nationwide Veterans Health Administration electronic medical record data

    Abstract: Novel and automated means of opioid use and relapse risk detection are needed. Unstructured electronic medical record data, including written progress notes, can be mined for clinically relevant information, including the presence of substance use and relapse-critical markers of risk and recovery from opioid use disorder (OUD). In this study, we used natural language processing (NLP) to automate the extraction of opioid relapses, and the timing of these occurrences, from veteran patients' electronic medical record. We then demonstrated the utility of our NLP tool via analysis of pre-/post-COVID-19 opioid relapse trends among veterans with OUD. For this demonstration, we analyzed data from 107,606 veterans OUD enrolled in Veterans Health Administration, comparing a pandemic-exposed cohort (n = 53,803; January 2019-March 2021) to a matched prepandemic cohort (n = 53,803; October 2017-December 2019). The recall of our NLP tool was 75% and our precision was 94%, demonstrating moderate sensitivity and excellent specificity. Using the NLP tool, we found that the odds of opioid relapse postpandemic onset were proportionally higher compared to prepandemic trends, despite patients having fewer mental health encounters from which to derive instances of relapse postpandemic onset. In this research application of the tool, and as hypothesized, we found that opioid relapse risk was elevated postpandemic. The application of NLP Methods: to identify and monitor relapse risk holds promise for future surveillance, risk prevention, and clinical outcome research.