. "Appendix B: Redesigning Health Care with Insights from the Science of Complex Adaptive Systems." Crossing the Quality Chasm: A New Health System for the 21st Century. Washington, DC: The National Academies Press, 2001.
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Crossing the Quality Chasm: A New Health System for the 21st Century
fundamentally, they are not. When the human parts do not act as expected or hoped for, we say that people are being “unreasonable” or “resistant to change,” their behavior is “wrong” or “inappropriate.” The system designer’s reaction typically is to specify behavior in even more detail via laws, regulations, structures, rules, guidelines, and so on. The unstated goal seems to be to make the human parts act more mechanical.
RECONCILING MECHANICAL AND ADAPTIVE SYSTEMS THINKING
This apparently misguided thinking arises from traditional science. In the Renaissance, Galileo, Newton, and others gave us the image of the clockwork universe (Capra, 1996). The paradigm of science for the last several hundred years has been one of reductionism; that is, further study of the parts of systems will lead to deeper understanding and predictability. Indeed, this tradition has led to great advances in knowledge.
Reductionist thinking has also been applied to organizations. Taylor (1911) introduced “scientific management” a century ago and changed our view of systems of work. Taylorism resulted in huge gains in productivity through the introduction of scientific study of time and motion in work. Taylor believed that if workers would do their work in the “one best way,” everyone would benefit (Kanigel, 1997). These ideas form a continuing and deeply held paradigm today (Morgan, 1997; Zimmerman et al., 1998; Brown and Eisenhardt, 1998).
Mechanical systems thinking does work in many situations when applied to human systems, and it has led to great progress in the past century. It is precisely because mechanical systems thinking works in many situations that it has become such a strongly held paradigm.
Organizational theorist Ralph Stacey (1996) provides a way to think about this seeming paradox (Figure B-1). Zimmerman et al. (1998) further describe this concept and provides several examples of its application in health care. In the lower left portion of the diagram are issues in which there is a high degree of certainty (as to outcomes from actions) and a high degree of agreement (among the people involved in taking the actions). Here, mechanical systems thinking with detailed plans and controls is appropriate. An example in health care is a surgical team doing routine gall bladder surgery. Through experience and the accumulation of knowledge, there is a high degree of certainty about the surgical procedures that lead to successful outcomes. The members of the surgical team agree on the way they will operate. In a good surgical team, everyone’s actions need to be relatively predictable and somewhat mechanical. Someone who behaved unpredictably would be expelled from the team. In this area it is important to fully specify behavior and reduce variation, and there are many such issues at both the micro- and macrosystem level in health care.