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Open Access Research article

Network analysis of team communication in a busy emergency department

P Daniel Patterson1*, Anthony J Pfeiffer1, Matthew D Weaver1, David Krackhardt2, Robert M Arnold3, Donald M Yealy1 and Judith R Lave4

Author affiliations

1 Department of Emergency Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, USA

2 Heinz School of Public Policy and Management, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA

3 Department of Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, USA

4 Department of Health Policy and Management, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania, USA

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Citation and License

BMC Health Services Research 2013, 13:109  doi:10.1186/1472-6963-13-109

Published: 22 March 2013

Abstract

Background

The Emergency Department (ED) is consistently described as a high-risk environment for patients and clinicians that demands colleagues quickly work together as a cohesive group. Communication between nurses, physicians, and other ED clinicians is complex and difficult to track. A clear understanding of communications in the ED is lacking, which has a potentially negative impact on the design and effectiveness of interventions to improve communications. We sought to use Social Network Analysis (SNA) to characterize communication between clinicians in the ED.

Methods

Over three-months, we surveyed to solicit the communication relationships between clinicians at one urban academic ED across all shifts. We abstracted survey responses into matrices, calculated three standard SNA measures (network density, network centralization, and in-degree centrality), and presented findings stratified by night/day shift and over time.

Results

We received surveys from 82% of eligible participants and identified wide variation in the magnitude of communication cohesion (density) and concentration of communication between clinicians (centralization) by day/night shift and over time. We also identified variation in in-degree centrality (a measure of power/influence) by day/night shift and over time.

Conclusions

We show that SNA measurement techniques provide a comprehensive view of ED communication patterns. Our use of SNA revealed that frequency of communication as a measure of interdependencies between ED clinicians varies by day/night shift and over time.

Keywords:
Teamwork; Communication; Social network analysis; Emergency medicine