Applying social network analysis to evaluate implementation of a multisector population health collaborative that uses a bridging hub organization

Aaron L. Leppin, Janet M. Okamoto, Paige W. Organick, Anjali D. Thota, Francisco J. Barrera-Flores, Mark L. Wieland, Rozalina G. McCoy, Robert P. Bonacci, Victor M. Montori

Research output: Contribution to journalArticlepeer-review

5 Scopus citations


Background: Multisector collaboratives are increasingly popular strategies for improving population health. To be comprehensive, collaboratives must coordinate the activities of many organizations across a geographic region. Many policy-relevant models encourage creation and use of centralized hub organizations to do this work, yet there is little guidance on how to evaluate implementation of such hubs and track their network reach. We sought to demonstrate how social network analysis (SNA) could be used for this purpose. Methods: Through formative research, we defined and conceptualized key characteristics of a bridging hub network and identified a set of candidate measures-(1) network membership, (2) network interaction, (3) role and reach of the bridging hub, and (4) network collaboration-to evaluate its implementation within a pre-determined geographic region of Southeast Minnesota, USA. We then developed and administered a survey to assess outcomes as part of a SNA. We commented on the feasibility and usefulness of the methods. Results: The initial surveyed network consisted of 50 healthcare organizational sites and 50 community organizations representing sectors of public health, education, research, health promotion, social services, and long-term care and supports. Fifty-three of these organizations responded to the survey. The network's level of collaboration was "Cooperation" (level 2 of 5) and reported levels of collaboration varied by organization. Thirty-eight additional, unsurveyed organizations were identified as collaborators by respondents, pushing the theoretical network denominator up to 138 organizations. These additional organizations included grocery stores, ambulance services, and smaller, independent healthcare and community-based services focused on meeting the needs of underserved populations. The bridging hub organization had the highest betweenness centrality and was in good position to bridge healthcare and the community, although its organizational reach was estimated at only 51%. The SNA methods were feasible and useful for identifying opportunities and guiding implementation. Conclusions: Bridging hub organizations are not likely to link-or even be aware of-all relevant organizations in a geographic region at initial implementation. SNA may be a useful method for evaluating the value and reach of a bridging hub organization and guiding ongoing implementation efforts. Trial registration:; #NCT03046498.

Original languageEnglish (US)
Article number315
JournalFrontiers in Public Health
Issue numberNOV
StatePublished - Nov 2 2018


  • Community based programs
  • Health promotion
  • Partnerships
  • Population health
  • Social network analysis

ASJC Scopus subject areas

  • Public Health, Environmental and Occupational Health


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