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Social Network Analysis of a Simulation Community.

Richard H Riley1, Cai Kjaer, A Carol Cheney

  • 1From the University of Western Australia (R.H.R); Department of Health (R.H.R., A.C.C., S.N., B.L.S.), Government of Western Australia, East Perth, WA; and Optimice Pty Ltd (C.K.), Sydney, NSW, Australia.

Simulation in Healthcare : Journal of the Society for Simulation in Healthcare
|November 9, 2018
PubMed
Summary
This summary is machine-generated.

Networking analysis mapped the Western Australian healthcare simulation community, identifying key collaborators and isolated groups. This data can strengthen professional connections and advance simulation-based education.

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Area of Science:

  • Health Professions Education
  • Network Science
  • Community Health

Background:

  • Graphical analysis of networking maps assesses professional community health, connectivity, and vulnerabilities.
  • Healthcare simulation communities benefit from understanding internal and external relationships.
  • Mapping professional networks can reveal opportunities for collaboration and advancement.

Purpose of the Study:

  • To capture and map connections within Western Australia's healthcare simulation community.
  • To identify individuals and organizations involved in healthcare simulation.
  • To foster new collaborative opportunities and advance simulation-based education.

Main Methods:

  • An online survey and proprietary mapping software were utilized.
  • Established simulation practitioners formed the baseline for the survey.
  • Links and interactions between individuals and organizations were mapped.

Main Results:

  • 79 respondents provided 500 relationship pairs for 203 personnel.
  • Two-thirds of respondents were from medical, nursing, and allied health fields.
  • Average collaborators per respondent was 6.6, with identified leaders and isolated groups.

Conclusions:

  • A few simulation educators had extensive internal and external linkages.
  • Isolated groups with limited cross-organizational associations were identified.
  • Data can inform organizations and agencies to strengthen the simulation network.