Professional networks are being used increasingly in healthcare to overcome problems of working within a system fragmented by professional “tribes,” and organisational and geographic boundaries. Such networks are thought to encourage the bridging of these boundaries, leading to greater collaboration. Research about how this is achieved does not yet give a comprehensive picture of network processes and the role of key actors. This thesis used a combination of qualitative and quantitative methods, primarily social network analysis, to explore the network structure and the role of key players within a representative network. The network was a new translational research network (TRN) based in Sydney, Australia that sought to drive collaboration between university-based researchers and hospital-based clinicians to translate biomedical research into clinical practice. The thesis asked the following questions: what is the structure of collaborative ties within this network? Who are the key players in this network? Do the formal, mandated leaders of this network recognise the potential held in their network positions? TRN documentation, semi-structured interviews with the 14 governing body members, and a systematic review of brokerage roles in collaborative networks gave context, and informed the design of the social network survey. An on-line, whole network survey was used to collect demographic and relationship data from all 68 members in early 2012 as well as opinions on aspects of the network. Geographic location was a significant factor determining patterns of collaboration. Central actors identified by analysis of network data mostly matched members’ perceptions of powerful and influential players but identified brokers were not perceived as such. Mandated leaders were found to have key network positions and recognised their significance in terms of facilitative activities. The thesis shows empirically the influence of “silos” on collaboration and that the network may increase connectivity between them. Secondly it shows the hidden identity of brokers in the healthcare setting. This confirmed that network interventions based on role support for key players can only be realised if the brokers are accurately identified. Thirdly it shows that mandated leaders in the network understand their roles and activities in a way that reflects their network potential.
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