3.8 Article

Application of team science best practices to the project management of a large, multi-site lung cancer screening research consortium

Journal

Publisher

CAMBRIDGE UNIV PRESS
DOI: 10.1017/cts.2023.566

Keywords

Team science; cancer; consortium; project management; data management

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This manuscript describes how the PROSPR-Lung consortium utilized evidence-based SciTS best practices to establish infrastructure and processes for translational research in lung cancer screening. Specific examples are provided for developing a shared mission, transparent leadership, research support systems, efficient data management, interdisciplinary conversations, and a culture of trust. Guidance is offered for managing a multi-site research center and data repository, along with project management tools and processes to drive collaboration, efficiency, and scientific productivity.
Research is increasingly conducted through multi-institutional consortia, and best practices for establishing multi-site research collaborations must be employed to ensure efficient, effective, and productive translational research teams. In this manuscript, we describe how the Population-based Research to Optimize the Screening Process Lung Research Center (PROSPR-Lung) utilized evidence-based Science of Team Science (SciTS) best practices to establish the consortium's infrastructure and processes to promote translational research in lung cancer screening. We provide specific, actionable examples of how we: (1) developed and reinforced a shared mission, vision, and goals; (2) maintained a transparent and representative leadership structure; (3) employed strong research support systems; (4) provided efficient and effective data management; (5) promoted interdisciplinary conversations; and (6) built a culture of trust. We offer guidance for managing a multi-site research center and data repository that may be applied to a variety of settings. Finally, we detail specific project management tools and processes used to drive collaboration, efficiency, and scientific productivity.

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