About

Traumatic brain injury (TBI) is a major medical problem for both military and civilian populations. There are many critical gaps in our knowledge regarding how to diagnose and treat people who sustain a TBI. High priority gaps include the need for an objective diagnosis for mild TBI, biomarkers to track recovery or progression of injury, a biologically-based classification system, and comparative effectiveness research to determine which treatments are effective and for whom. To address these gaps, as well as other important questions on how to improve outcomes, the National Institutes of Health (NIH), in partnership with the Department of Defense (DoD), is building a secure, centralized informatics system (database) for TBI research. It will serve as a central repository for new data, link to current databases and allow valid comparison of results across studies. The database builds upon an effort to create common data elements for the study of TBI - which are essentially definitions and guidelines about the kinds of data that should be collected, and how to collect these data in clinical studies.

Mission

The Federal Interagency Traumatic Brain Injury Research (FITBIR) Informatics System is a central repository that was developed by the National Institutes of Health (NIH), in collaboration of the Department of Defense (DOD), to promote collaboration, accelerate research, and advance knowledge on the characterization, prevention, diagnosis, and treatment of traumatic brain injury (TBI). FITBIR’s mission is to provide researchers access to a common platform for digital object collection, retrieval, sharing, and preservation. Sharing data, methodologies, and associated tools, rather than summaries or interpretations of this information, can accelerate research progress by allowing re-analysis of data, as well as re-aggregation, integration, and rigorous comparison with other data, tools, and methods. This community-wide sharing requires common data definitions and standards, as well as comprehensive and coherent informatics approaches.