Considering Complexity Theory in Understanding Information Management in Health Systems

Document Type

Journal Article


Faculty of Computing, Health and Science


School of Computer and Security Science / eHealth




This article was originally published as: Knight, S. (2011). Considering Complexity Theory in Understanding Information Management in Health Systems. Journal of Information Technology Review, 2(4), 172-182. Original article available here


In 2008, as part of a national agenda of Healthcare reform, the Australian Federal Government commissioned a report into the state of the Australian public health system. The resultant 2009 report by the National Health & Hospitals Reform Commission (NHHRC) described the Australian Health Sector (AHS), and its information and management processes, as ―fragmented‖. Observed in the NHHRCs depiction of the AHS was that the various levels and services offered within healthcare operate largely arbitrarily, and at multiple local system nodes of a whole larger – albeit fragmented – system. Recommended were numerous strategies designed to ‗fix‘ this fragmented complex system. Implied in this depiction and resulting recommendations is the NHHRC‘s pre-supposition that systems need to be (traditionally) ‗ordered‘ and managed to be considered as functioning in their optimal state. This paper argues that an alternative paradigm, informed by the science of complexity – which conceptualises complex organisations and their processes in terms of being Complex Adaptive Systems (CAS) – is able to provide a more appropriate theoretical foundation for both understanding and facilitating information management within highly complex organisational structures. Chaos and Complexity theories offer – for the organisational theorist – an investigative framework better suited to the dynamic and unpredictable characteristics of information and process management within a complex organisation. In this context, traditional information and management science approaches to understanding organisational characteristics such as fragmentation, process and information duplication, redundancy, and system regulation may require a rethink.