Abstract
Data standards are available for spinal cord injury (SCI). The International SCI Data Sets were created in 2002 and there are currently 27 freely available. In 2015 the National Institute of Neurological Disorders and Stroke developed clinical common data elements to promote clinical data sharing in SCI. The objective of this paper is to provide an overview of SCI data standards, describe learnings from the traumatic brain injury (TBI) field using data to enhance research and care, and discuss future opportunities in SCI. Given the complexity of SCI, frameworks such as a systems medicine approach and Big Data perspective have been advanced. Implementation of these frameworks require multi-modal data and a shift towards open science and principles such as requiring data to be FAIR (Findable, Accessible, Interoperable and Reusable). Advanced analytics such as artificial intelligence require data to be interoperable so data can be exchanged among different technology systems and software applications. The TBI field has multiple ongoing initiatives to promote sharing and data reuse for both pre-clinical and clinical studies, which is an opportunity for the SCI field given these injuries can often occur concomitantly. The adoption of interoperable standards, data sharing, open science, and the use of advanced analytics in SCI is needed to facilitate translation in research and care. It is critical that people with lived experience are engaged to ensure data are relevant and enhances quality of life.
•Data elements and standards are available for spinal cord injury (SCI).•Given the complexity of SCI, frameworks such as a systems medicine approach and Big Data perspective have been proposed.•Opportunities exist to learn from the traumatic brain injury field which has experience with pre-clinical and clinical data standards, and data sharing.•Engagement of people living with SCI is critical to ensure data collected is meaningful and improves quality of life.•The adoption of interoperable standards, data sharing, open science and the use of advanced analytics will facilitate translation in SCI research and care.