The International Neuromodulation Registry: An Informatics Framework Supporting Cohort Discovery and Analysis - Hedges, David M.; Hegman, John C.; Brown, Jefferson R.; Wilburn, Jack T.; Chapman, Brian E.; Butson, Christopher R. (Frontiers in Neuroinformatics, 2020)
Background: Neuromodulation therapies, such as deep brain stimulation (DBS) or transcranial magnetic stimulation (TMS), are used in extreme cases of neuropsychiatric illness when conventional therapies fail to have an effect. While generally effective, seemingly parallel and similar cases often have different results. Academic medical centers are conducting research into determining predictive factors, but many of these studies are chronically statistically underpowered. Objective: In order to increase sample size to allow for more predictive power in neuromodulation studies, we have created an informatics platform called the International Neuromodulation Registry (INR). The INR platform has a data flow process that will allow researchers to pool data and draw conclusions based on data from multiple studies. Methods: This custom informatics platform has a Neo4j graph database and includes a harmonization process that allows data from different studies to be compared. Users of the INR can download deidentified patient imaging, patient demographic data, as well as stimulation settings and medical rating scales. The INR supports complex network analysis and patient timeline visualization. Results: The INR currently houses imaging and medical data from more than 200 patients. Conclusions: Ultimately, we believe that widespread use of the INR platform will allow for more complete analyses and help reduce data redundancy.