Applying Social Network Analysis in a Healthcare Setting

Applying Social Network Analysis in a Healthcare Setting

Salvatore Parise (Babson College, USA)
Copyright: © 2008 |Pages: 9
DOI: 10.4018/978-1-59904-889-5.ch013
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Abstract

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.

Key Terms in this Chapter

Social Network Analysis: A research methodology to analyze networks between people, groups, organizations, and systems within and across organizations.

Information Network: Information networks map who people turn to for information regarding work-related activities.

Degree Centrality: Refers to the number of links going into (“in-degree”) or coming out of (“out-degree”) a node in a network.

Social Network: The people-to-people relationships in organizations where knowledge work actually gets performed. The social network may be in complete contradiction to the information flows expected, based on the organizational chart of formal roles or titles.

Network Fragmentation: In the context of SNA, network fragmentation occurs where silos exist in the network and information is not being transferred across functional, hierarchical, cultural, or geographic boundaries.

Broker: In the context of SNA, brokers are used to describe nodes in the network that connect different subgroups.

Tacit Knowledge: Knowledge that is difficult to codify, and often resides in the key experts of the organization.

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