Social Networking in Health System for Knowledge Translation

Interaction among health system sections is one of the main contributing factors for progress of biomedical fields. Such interaction requires sharing the knowledge in properly designed networks of researchers and clinicians where experience meets expertise to create new knowledge. As an infrastructure for approaching this idea, there is a need for development of integrated databases for identification, classification, and discovery of the knowledge about researchers and clinicians to analyze their links in a network. In this case, Social Network Analysis (SNA) works as a society-oriented prototype to explore the structural patterns of social connections;1 hence it renders both visual and statistical representations of interpersonal relations.2 SNA, a subset of ‘sociometry’ coined by J. L. Moreno3, presents the methodology to analyze social relations. It is composed of nodes (individuals), the smallest unit in a network, and lines (relations), a tie between two nodes. Likewise, ego-networks are kinds of social networks that focus on certain nodes and are called egos.1 They also propose highly remarkable information in order to comprehend the structure and nature of relationships, and interaction within a scientific community.1 Here, we propose the development of a database benefiting SNA to get the required inputs for a social interface involving various groups of health system. Integration of health system groups by means of new methodologies and technologies could provide valuable outputs for knowledge flow among these groups. SNA has also been suggested as a pragmatic methodology to delineate interaction models in healthcare settings.4-8 Furthermore, we aim to present a proposal to integrate the health system groups through the SNA methodology as well as social media technology.