Academic journal article Emergence: Complexity and Organization

Mutual Empathy, Ambiguity, and the Implementation of Electronic Knowledge Management within the Complex Health System*

Academic journal article Emergence: Complexity and Organization

Mutual Empathy, Ambiguity, and the Implementation of Electronic Knowledge Management within the Complex Health System*

Article excerpt

Healthcare can be characterized as a complex adaptive system. New Zealand is recognized as having one of the highest rates of enmeshed clinical information and communication technology within this complex system. This paper describes the implementation of an integrated series of electronic clinical health knowledge management systems in a large New Zealand District Health Board. In combination with standard project management, the core implementation team utilized an action research reflective learning approach to enhance their capability to cope with emergent issues, and plan for each subsequent project stage. The emergent focus on "process" issues of connectedness, competency, and control were not the "technical" concerns the principal author was initially expecting, but can be understood through an appreciation of individual and group dynamics, system and complexity theories. In particular, mutual empathy for both self and others was identified as a core capability requirement to cope with the inherent ambiguity within complex systems.


Healthcare can be characterized as a complex adaptive system. From the cellular to sociopolitical levels, multiple "agents" and systems interact across shadowy boundaries and contribute to our concepts of health and healthcare. Nonlinear dynamics and sensitivity to initial conditions are inherent; and small changes in one part of the system, or embedded system, can change the context and outcome of another part, leading to significant variability and emergence in health outcomes (Goldberger, 1996; McDaniel et al, 2003; Plesk & Greenhalgh, 2001; Wilson et a?., 2001).

If we accept this complexity conceptualization of healthcare (while recognizing doubters and the risk of fadism: e.g., Price, 2004; Reid & Notcutt, 2002), then we need to appreciate the innate unpredictability of health outcomes. We need to appreciate the limitations of healthcare management that is unduly bounded by the search for increasing data analysis and prediction models that will allow this complexity to be controlled. Rather than focusing investment on increasingly complex and costly "rational" control and decision mechanisms, we should be building the capability to cope with and indeed exploit this inherent variability and emergence (Anderson et al, 2000; Fraser & Greenhalgh, 2001; Kurtz & Snowden, 2003; Lemak & Goodrick, 2003; Plesk & Wilson, 2001).

Globally, information and communication technology (ICT) is increasingly being applied to the health system. Objectives and predicted benefits vary by stakeholder and system, but coordination, integration, safety, and efficiency are common themes (Institute of Medicine, 2000). There may be a range of views on the constituent parts or overall makeup of an ideal health knowledge management system. However, recurrent identified core features or principles that may be independent of place, time, or technology can be encapsulated in the mnemonic C.A.R.E. G.A.P.S. F.I.R.S.T.

The system should enhance every stakeholder's "capacity to C.A.R.E."; that is, perform their integral Clinical, Administrative, Research, and Educational healthcare functions. The system should accommodate the complex and holistic environment in which it is enmeshed, while recognizing, connecting, and enabling all the key stakeholders, primarily General practitioners, Allied health services (including hospitals), Patients and their Supports, as well as being Fast, Intuitive, Robust, Stable, and Trustworthy (Orr, 2004; Standards Australia, 2001; Standards Australia/New Zealand, 2001; Sveiby, 2001; Wyatt, 2001).

Historically, clinician-valued, cost-efficient systems that have sustainably delivered their predicted benefits have proven to be relatively elusive. A failure to recognize complexity, or a focus on trying to control the complexity of healthcare via increasing levels of data collection, analysis, and detailed "decision support" guideline or protocol creation, could explain, at least in part, this relative failure (Ash, 1 997; Ash et al, 2004; Berger & Kichak, 2004; Bryant, 1998; Garg, 2005; Heeks étal, 1999; Southon étal, 1997). …

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