The nurse as an integration agent in handoff: A social networks analysis perspective
Author(s) -
Sergio da Silva Antonio,
Aline Bento Ambrósio Avelar,
Carlos Farina Milton
Publication year - 2014
Publication title -
african journal of business management
Language(s) - English
Resource type - Journals
ISSN - 1993-8233
DOI - 10.5897/ajbm2014.7476
Subject(s) - betweenness centrality , closeness , popularity , handover , centrality , social network analysis , quality (philosophy) , socialization , social network (sociolinguistics) , business , psychology , public relations , computer science , social psychology , social media , world wide web , political science , computer network , mathematics , combinatorics , epistemology , philosophy , mathematical analysis
The growing interest in social networks, in health services, follows international pressure by improving quality and reducing costs in this sector. Identifying the most important actors in a social network is one of the applications of graph theory in social network analysis (SNA). Socialization among health professionals (actors) and their structural positions, in social networks, are important factors to be considered in developing strategies, which include information dissemination and influence. This research applied SNA to identify the actors with the greatest influence during handoff in a hospital. Data were collected in the second half of 2012, in the city of Sao Paulo. Semi-structured interviews have been conducted with actors in six handoffs. A seventh handoff has been created, as ideal hypothetical model, to compare the distinguishing features among the handoffs. The nurse in the unit of origin emerges as the actor with greater popularity (degree, eigenvector), greater influence or control (betweenness) and better access to information on the handoff (closeness, actor information centrality). A nurse is, possibly, an important categorical role to facilitate actions of integration during a handoff. Key words: Handoffs, information dissemination, social networking analysis, healthcare.
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