The sciences of the artificial (3rd ed.)
The sciences of the artificial (3rd ed.)
Accumulating and Coordinating: Occasions for Information Technologies in Medical Work
Computer Supported Cooperative Work
Thinking in Complexity, 3e
Workflow modeling in critical care: Piecing together your own puzzle
Journal of Biomedical Informatics
Activity-based computing for medical work in hospitals
ACM Transactions on Computer-Human Interaction (TOCHI)
Artificial Intelligence in Medicine
Bridging gaps in handoffs: A continuity of care based approach
Journal of Biomedical Informatics
Envisioning complexity in healthcare systems through social networks
Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
Measuring performance & interrelatedness in social networks of knowledge workers
Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
Mining Deviations from Patient Care Pathways via Electronic Medical Record System Audits
ACM Transactions on Management Information Systems (TMIS) - Special Issue on Informatics for Smart Health and Wellbeing
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A recent trend in the literature has been to characterize healthcare activities in terms of complex systems theory. Complexity has often been loosely and variously defined, with meanings ranging from ''not simple'' to ''complicated'' to ''intractable.'' In this paper, we consider various aspects of complexity and how they relate to modern healthcare practice, with the aim of developing research approaches for studying complex healthcare environments. We propose a theoretical lens for understanding and studying complexity in healthcare systems based on degrees of interrelatedness of system components. We also describe, with relevant caveats, how complex healthcare systems are generally decomposable, rendering them more tractable for further study. The ideas of interrelatedness among the components of a system as a measure of complexity and functional decomposition as a mechanism for studying meaningful subcomponents of a complex system can be used as a framework for understanding complex healthcare systems. Using examples drawn from current literature and our own research, we explain the feasibility of this approach for understanding, studying, and managing complex healthcare systems.