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Complex adaptive systems: concept analysis.

Abstract

AIM: The aim of this paper is to explicate the concept of complex adaptive systems through an analysis that provides a description, antecedents, consequences, and a model case from the nursing and health care literature. BACKGROUND: Life is more than atoms and molecules--it is patterns of organization. Complexity science is the latest generation of systems thinking that investigates patterns and has emerged from the exploration of the subatomic world and quantum physics. A key component of complexity science is the concept of complex adaptive systems, and active research is found in many disciplines--from biology to economics to health care. However, the research and literature related to these appealing topics have generated confusion. A thorough explication of complex adaptive systems is needed. METHODS: A modified application of the methods recommended by Walker and Avant for concept analysis was used. FINDINGS: A complex adaptive system is a collection of individual agents with freedom to act in ways that are not always totally predictable and whose actions are interconnected. Examples include a colony of termites, the financial market, and a surgical team. It is often referred to as chaos theory, but the two are not the same. Chaos theory is actually a subset of complexity science. Complexity science offers a powerful new approach--beyond merely looking at clinical processes and the skills of healthcare professionals. CONCLUSION: The use of complex adaptive systems as a framework is increasing for a wide range of scientific applications, including nursing and healthcare management research. When nursing and other healthcare managers focus on increasing connections, diversity, and interactions they increase information flow and promote creative adaptation referred to as self-organization. Complexity science builds on the rich tradition in nursing that views patients and nursing care from a systems perspective.

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BibTeXRIS

Lela M Holden. 2005. Complex adaptive systems: concept analysis.. https://doi.org/10.1111/j.1365-2648.2005.03638.x

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