Secondary Analysis of Existing Databases in Traumatic Brain Injury to Explore Outcomes Relevant to Medical Rehabilitation

University Of Utah, Salt Lake City UT

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Abstract

Pain is one of the most common comorbidities among individuals with mild traumatic brain injuries (mTBI), yet little has been done to understand the longitudinal course of pain or treatment in this population. Despite the ubiquitous use of pain scores as the fifth vital sign in clinical care, there have been few attempts to capitalize on commonly gathered pain data and to actually define the meaning of these scores over time or in conjunction with treatment trajectories. As a result, a growing number of individuals with mTBI and pain suffer functional disability, increased healthcare utilization, challenges to family functioning, and delayed return to work. Given the high prevalence of mTBI in Iraq and Afghanistan war Veterans (IAV), and the availability of clinically focused administrative data from the Department of Veterans Affairs (VA), IAV with mTBI are a unique population to examine these important issues. Our transdisciplinary team will compile data from a previously funded project to: Identify patterns (trajectories) of pain scores and pain treatment during the first five years of VA care in an IAV cohort with mTBI, and identify the relationships among pain and treatment trajectories, and adverse outcomes including suicidal ideation/attempt, overdose, accidents, and development of substance use disorder. We will use the latent growth mixture modeling technique to identify distinct trajectories associated with pain scores and latent class models to identify unique trajectories of pain treatment over the 5-year period after entering VA care. We will then determine if the incidence of adverse events during the 2-year window following the 5-year trajectory development period differs by pain score and treatment trajectory classes. We will use Cox regression models to determine the independent effects of pain and treatment trajectories and adverse outcomes, controlling for age, gender, race/ethnicity, and other comorbid conditions. Results will provide data that can be used to inform best practices by identifying more effective and suboptimal treatment approaches for individuals who experience comorbid mTBI and pain. More importantly, this will be one of the first studies to fulfill the promise of clinical benefit for the pain vital sign. Given the increasing availability of administrative data developed in the course of clinical care, methods used in this project can be translated for use in other clinical settings. Moreover, the proposed project provides the foundation for more focused studies that can examine the longitudinal experience and treatment of pain from the patient's perspective. The resulting data will also lead to the development of predictive models that can be used to identify effective and suboptimal treatment approaches for mTBI patients with specific pain phenotypes across different settings of care beyond the VA, establishing evidence to advance existing clinical practice guidelines for treating pain in individuals with mTBI.