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Open Access Research article

Who are the key players in a new translational research network?

Janet C Long1*, Frances C Cunningham12, Peter Carswell13 and Jeffrey Braithwaite1

Author Affiliations

1 Centre for Clinical Governance Research, Australian Institute of Health Innovation, University of New South Wales, Kensington 2052, Australia

2 Centre for Primary Health Care Systems Research, Menzies School of Health Research, Charles Darwin University, Darwin 0815, Australia

3 School of Population Health, University of Auckland, Auckland 1142, New Zealand

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BMC Health Services Research 2013, 13:338  doi:10.1186/1472-6963-13-338

Published: 30 August 2013

Abstract

Background

Professional networks are used increasingly in health care to bring together members from different sites and professions to work collaboratively. Key players within these networks are known to affect network function through their central or brokerage position and are therefore of interest to those who seek to optimise network efficiency. However, their identity may not be apparent. This study using social network analysis to ask: (1) Who are the key players of a new translational research network (TRN)? (2) Do they have characteristics in common? (3) Are they recognisable as powerful, influential or well connected individuals?

Methods

TRN members were asked to complete an on-line, whole network survey which collected demographic information expected to be associated with key player roles, and social network questions about collaboration in current TRN projects. Three questions asked who they perceived as powerful, influential and well connected. Indegree and betweenness centrality values were used to determine key player status in the actual and perceived networks and tested for association with demographic and descriptive variables using chi square analyses.

Results

Response rate for the online survey was 76.4% (52/68). The TRN director and manager were identified as key players along with six other members. Only two of nine variables were associated with actual key player status; none with perceived. The main finding was the mismatch between actual and perceived brokers. Members correctly identified two of the three central actors (the two mandated key roles director and manager) but there were only three correctly identified actual brokers among the 19 perceived brokers. Possible reasons for the mismatch include overlapping structures and weak knowledge of members.

Conclusions

The importance of correctly identifying these key players is discussed in terms of network interventions to improve efficiency.