Accelerators: Sparking Innovation and Transdisciplinary Team Science in Disparities Research
- PMID: 28241508
- PMCID: PMC5369061
- DOI: 10.3390/ijerph14030225
Accelerators: Sparking Innovation and Transdisciplinary Team Science in Disparities Research
Abstract
Development and implementation of effective, sustainable, and scalable interventions that advance equity could be propelled by innovative and inclusive partnerships. Readied catalytic frameworks that foster communication, collaboration, a shared vision, and transformative translational research across scientific and non-scientific divides are needed to foster rapid generation of novel solutions to address and ultimately eliminate disparities. To achieve this, we transformed and expanded a community-academic board into a translational science board with members from public, academic and private sectors. Rooted in team science, diverse board experts formed topic-specific "accelerators", tasked with collaborating to rapidly generate new ideas, questions, approaches, and projects comprising patients, advocates, clinicians, researchers, funders, public health and industry leaders. We began with four accelerators-digital health, big data, genomics and environmental health-and were rapidly able to respond to funding opportunities, transform new ideas into clinical and community programs, generate new, accessible, actionable data, and more efficiently and effectively conduct research. This innovative model has the power to maximize research quality and efficiency, improve patient care and engagement, optimize data democratization and dissemination among target populations, contribute to policy, and lead to systems changes needed to address the root causes of disparities.
Keywords: accelerator; big data; community engagement; digital health; disparities; environmental health; genomics; team science; translational research.
Conflict of interest statement
The authors declare no conflict of interest and the funding sponsors had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, and in the decision to publish the results.
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