| Consider how injury severity, mechanism of injury, age, and lifetime TBI history could influence chronic outcomes. |
Develop taxonomy of TBI based on biological impact, disease mechanism, and/or longitudinal course, rather than on injury severity. Consider how population characteristics affect the etiology of the course and outcome of TBI.
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| Consider how epidemiological factors contribute to patient diagnosis and heterogeneity. |
Identify putative areas of interventional investigation around the presence of comorbid conditions, which suggests the potential for a shared underlying biology. Consider the opportunities and challenges of patients who present with multiple health conditions in future clinical trials’ inclusion and exclusion criteria. Develop longitudinal studies in diverse populations (e.g., pediatric, military, sports, and elderly) and identify outcome trajectories and differences in the mechanisms of injury.
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| Leverage new approaches for data collection. |
Identify new approaches for data collection in clinical care settings, including the type of care received, use of wearable devices, and methods (e.g., machine learning, artificial intelligence) to analyze the complex data and understand persons at risk for phenotypes representing poor outcomes.
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| Build a national TBI registry to enable monitoring of trends in health, resources, allocation, and priority setting; ensure better data collection; and establish best practices for intervention timeliness, monitoring, and evaluation. |
Develop a database or registry (similar to TBI Model Systems) that follows persons over time. Ensure that the registry follows all severities of TBI, how patients were enrolled, and tools to track those with mild injuries or those who did not receive rehabilitation services.
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