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Harnessing Multiteam Systems in the Development of a Multifaceted Data Repository for Emergency Public Health
Brandy L Farlow1, Keriayn N Smith, Aubrie Weyhmiller
1Author Affiliations: Renaissance Computing Institute (RENCI), University of North Carolina at Chapel Hill, Chapel Hill, North Carolina (Farlow, Smith, Weyhmiller, Hubal, Suber, and Krishnamurthy); Booz Allen Hamilton Inc., McLean, Virginia (Keller); and Stanford Center for Biomedical Informatics Research, Stanford University, Palo Alto, California (Musen).
Abstract:
The NIH launched the Rapid Acceleration of Diagnostics (RADx) Initiative to facilitate timely, accurate, and accessible COVID-19 testing, research, and data sharing. The RADx Data Hub (hereafter referred to as Data Hub) is a centralized repository developed to enable secure access and secondary analysis of curated, de-identified data across RADx Initiative programs. Implementing this Data Hub required extensive nested multiteam system collaboration and alignment. Here, we describe the nested multiteam system framework that effectuated data access within a global crisis as a model for future public health challenges. Our work highlights how structured team science methods can enhance the speed and efficacy of data assembly and distribution to accelerate response during public health crises.
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