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Envisioning complexity in healthcare systems through social networks
Conference proceeding   Peer reviewed

Envisioning complexity in healthcare systems through social networks

Andrew V. Levula, Kon Shing Kenneth Chung, Jane Young and Kate White
Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, pp.931-936
ACM Conferences
ASONAM '13: Advances in Social Networks Analysis and Mining 2013
25/08/2013

Abstract

Applied computing -- Life and medical sciences -- Health care information systems Human-centered computing -- Human computer interaction (HCI) -- Interaction paradigms -- Web-based interaction Information systems -- Information retrieval -- Document representation
In this study, we develop an Aggregate Complexity Framework (ACF) for envisioning complexity for care coordination. This framework provides an empirical foundation that can be adopted for better understanding and characterizing aggregate complexity in healthcare systems through the use of social network measures. Complexity is defined as the interrelatedness of components within a system. For instance, healthcare systems are characterized as complex adaptive system as they consist of multidisciplinary teams that have strong interdependences as healthcare professionals are required to coordinate effectively and share resources for positive patient outcomes. This aggregate complexity framework can be used to capture the number of components (e.g. professionals, technology, other artifacts etc.) and the degree of interrelatedness between the components (the level of influence the components have on one another) within a system. The contribution that this study makes to the field is 1) better understanding of aggregate complexity and coordination 2) a theoretical model which can be used to further understand the challenges of care coordination in cancer settings and 3) practical implications for aggregate complexity framework for envisioning organizations and healthcare systems.

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