The people-to-people relationships where knowledge work actually gets performed in organizations are called social networks, and they may be in complete contradiction to the information flows expected, based on looking at the organizational chart of formal roles or titles. These informal or social networks are playing an increasingly important role in the healthcare industry, as medical and clinical knowledge needs to be shared effectively between people within and among healthcare organizations. Social network analysis (SNA) is a research methodology to analyze networks between people, groups, organizations, and systems within and across organizations (Wasserman & Faust, 1994). The results of the analysis inform the researcher of both the structure of the network, as well as the positions of nodes or people in the network. This article provides a description of how SNA can be applied in a healthcare setting.
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There has been a dramatic rise recently in social network research in the management field (Borgatti & Foster, 2003). Network research has grown as a result of the importance of connections between people, groups, organizations, and IT systems. Network research has been used to study leadership (Brass & Krackhardt, 1999), entrepreneurship (Baron & Markman, 2003), knowledge management (Parise, Cross, & Davenport, 2006), individual performance (Mehra, Kilduff, & Brass, 2001), and team performance (Hansen, 1999). Social network analysis (SNA) is a structured methodology to analyze networks within and across organizations. The results of the analysis inform the researcher of both the structure of the network as well as people’s positions within the network. Based on these findings, organizations can then develop interventions to produce the desired network effects. There has been limited research in the healthcare setting, using SNA as a methodology. SNA has been used to study the interaction patterns in primary care practices (Scott, Tallia, Crosson, Orzano, Stroebel, DiCicco-Bloom, O’Malley, Shaw, & Crabtree, 2005), identify influential individuals who are critical to the successful implementation of medical informatics applications (Anderson, 2005), and study the relationship between communication density and the use of an electronic medical record system by nurse practitioners and physicians’ assistants (Tallia, Stange, McDaniel, Aita, Miller, & Crabtree, 2003).