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Primary author: Adam Mahomed_
Edward Lorenz is credited with the discovery of chaos theory. In 1961 while running an experiment on a weather machine, he noticed something very interesting. The machine tracked weather patterns over time. He was interested in examining one sequence at greater length. But, he did not want to start from the beginning of the sequence with the original initial condition; instead he entered the numbers into the computer from the middle of the sequence of interest (Gleick, 1987). The second run of data should have produced duplicate data when compared to the original data. Lorenz noticed that the data was drifting farther and farther apart from the original (Gleick, 1987). He realized that the problem was with the rounding of the numbers entered into the computer for the second run (Gleick, 1987). The original number was, .506127 and the second number entered was, .506 (Gleick, 1987). He thought the rounding of the numbers would have no consequence on the data set, but he was wrong. Initial conditions have a profound effect on the end result of data. This was how Chaos Theory was born.
Health care today is unpredictable and is evolving at a pace that needs a system in place to meet the needs of patients. Plsek and Greenhalph, stated that throughout the world healthcare systems are becoming more complex. In the past public health research and theory have produced a linear health care system (Resnicow and Page, 2008). With the changing paradigm of health care the linear system may be inadequate to deal with the unpredictable and evolving characteristics of health care today. Health care today may be better understood by means of nonlinear systems.
A nonlinear system is where the inputs are not directly proportional to the outputs. Kiel and Elliot (1996) have explained that nonlinear systems can reveal behavior of variables and the unstable. In the context of social science and public health, Kiel and Elliot believe that the changes in the relationships can be subject to positive feedback. The positive feedback is then amplified and a new behavior can be born that creates an unexpected outcome, a new behavior. Public health is a nonlinear system with many complex variables that cannot be controlled. But, chaos theory recognizes that within the complex nonlinear system there are patterns that can be understood and in the context of public health may help create a behavior change.
Tan et al. explain that the term chaos implies unpredictability. This does not mean that chaos reveals randomness but in fact that chaos reveals complex patterns in data sets (Tan et al., 2005). Tan et al state that, “chaos systems operate in a unstable combination of randomness and order, it continuously changes and evolves: as such, it appears to be an appropriate model for today’s complex health care systems.” One continuum that Tan et al. explore is through three different stages of a complex system: static, edge of chaos, and chaos. In the static stage, the system will experience a period of order. In the edge of chaos stage, the system is constantly shifting between static and chaos. In the last stage, called chaos, an unstable system is observed. The last stage could be a result of the system being created at a pace that does not let the system develop adequately, leading to self-destruction of the system. He explains the stage of chaos is where health care catastrophes occur. The SARS epidemic across China is a good example that shows the rapid, unpredictable change with no apparent pattern that the chaos stage exemplifies (Tan et al., 2005). Although the chaos stage might seem very unpredictable and random there are only certain and limited numbers of behaviors that a chaotic system can experience. It is important to think about the initial conditions that will affect the end result of the system that is trying to be achieved.
Health care systems need to let go of the idea of controlling their own long-term future. It is difficult to plan for long-term goals in a system that is always changing. The chaos theory can be applied to future health care systems planning. Studying nonlinear systems is a good way to understand the health care system and public health. Tan et al. conclude that the systems that are the future of health care need to be, “able to adapt to new environments, improve the balance between having high degrees of order and stability to become obsolete, and must evolve so rapidly and in such diverse ways as to become self-destructive.” They must focus on short-term goals and forecast long-term goals. Adaptability is the most important characteristic that health care systems need to understand. Keeping in mind that the purpose of the health care system is to provide the best outcomes for
Gleick, J. (1987) Chaos: Making a New Science. New York, New York: Penguin Group.
Kiel, D.L., Elliot, E. (1996). Chaos Theory in the Social Sciences: Foundation and Applications. Ann Arbor, Michigan: The University Of Michigan Press.
Plsek, P.E., Greenhalgh, T. (2001). The challenge of complexity in health care.
323, pp. 625- 628.
Resnicow, K., Page, S.E. (2008). Embracing Chaos and Complexity: A Quantum Change for Public Health.
American Journal of Public Health.
98(8), pp 1382- 1389.
Tan, J., Wen, H.J., & Awad, N. (2005). Health Care and Services Delivery Systems as Complex Adaptive Systems: Examining chaos theory in action.
Communications of the ACM
. 48(5), pp. 36-44.
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