Seyedeh Maedeh Shafiei; Adel Azar; Reza Esmaielpour
Volume 20, Issue 10 , October 2018, , Pages 1-9
Abstract
Background: Nurses frequently work as part of teams. High-quality care can only be delivered through effective communication among team members. Social network analysis (SNA) seeks to discover the connections. In a hospital, connection between nurses working in different departments is critical. In the ...
Read More
Background: Nurses frequently work as part of teams. High-quality care can only be delivered through effective communication among team members. Social network analysis (SNA) seeks to discover the connections. In a hospital, connection between nurses working in different departments is critical. In the same vein, groups of nurses and their social relationships in hospital settings are highly important. Networks play a significant role in work settings such as hospitals. The power of clusters (i.e. groups or teams of nurses) could be regarded as net capacity. If the power of a cluster increases, strength and quality of offered services will rise too. The social network analysis is intended to discover the associations and represent them graphically (i.e. qualitative representation). This means social connections are represented in a quantitative and mathematical language. Objectives: The present study aims to examine the relationships between nurses working in Razi Hospital (Rasht, Iran), analyze therelationships through social network analysis, categorize as well as cluster the network of nurses at Razi Hospital, and represent the resulting data of social network analysis as network graphs. Patients and Methods: This study employs soft system operation research as a qualitative research strategy to deal with the net- work of nurses working at Razi Hospital during 2016 in Iran as a case study. In terms of its area, Razi is the largest hospital of the Gilan Province of Iran. In this regard, 64 nurses engaged in the study through deep interviews with from 6 various departments of the hospital according to SNA procedure. The gathered qualitative data was analyzed using the Gephi software; ultimately, findingsare depicted as network graphs in section 5. Results: Nurses network of Razi Hospital (Rasht, Iran) includes 64 nodes/nurses and 168 edges/links, which are non-directional and weighted. After implementation of different steps in social network analysis, it can be state that, nurse network of the hospital includes 9 clusters out of which, 6 clusters belonged to studied departments. Due to the network low density, which is 0.083, the network has low coherence. This means that only 8.3% of the total potential and potential relationships in the network have been activated. Results concluded that, unfortunately, only members of different departments interact with each other and in the section,they work in. Conclusions: In Razi Hospital, network of nurses is characterized by weak connections between different departments. However, the relationship between members (i.e. relationship between nurses in a department) is strong and this signifies that nurses of a cluster or department are related to each other. The findings suggest that members of a certain department as well as between de- partments should closely associate with each other. In addition, there is a significant association between those departments of the hospital in which nurses are working. We can use significant association in health care aspects that require organizational and or- ganizational decision making. Nurses play an important and critical role in planning the main functions of hospital management.
