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Social Network Analysis to Assess the Impact of the CTSA on Biomedical Research Grant Collaboration

Success of the Clinical Translational Science Award (CTSA) program implicitly demands team science efforts and well‐orchestrated collaboration across the translational silos (T1–T4). Networks have proven to be useful abstractions of research collaborations. Networks provide novel system‐level insights and exhibit marked changes in response to external interventions, making them potential evaluation tools that complement more traditional approaches. This study is part of our ongoing efforts to assess the impact of the CTSA on Biomedical Research Grant Collaboration (BRGC). Collaborative research grants are a complex undertaking and an outcome of sustained interaction among researchers. In this report, BRGC networks representing collaborations among CTSA‐affiliated investigators constructed from grants management system data at the University of Kentucky across a period of six years (2007–2012) corresponding to pre‐ and post‐CTSA are investigated. Overlapping community structure detection algorithms, in conjunction with surrogate testing, revealed the presence of intricate research communities rejecting random graphs as generative mechanisms. The deviation from randomness was especially pronounced post‐CTSA, reflecting an increasing trend in collaborations and team‐science efforts potentially as a result of CTSA. Intercommunity cross talk was especially pronounced post‐CTSA.