1. Chapter 6
Complexity
Science and
Complex Adaptive
Systems

2. Introduction
• Complexity science is a new approach based
on the idea that complexity emerges from
simple rules.
• This paradigm allows us to view health care in
the context of complex adaptive systems
(CAS).
• Complexity science and CAS fit well with
nursing, because both promote adaptability
and employ a holistic point of view.

3. Introduction to Complexity Science
• Complexity science is based in physics and
mathematics, and it utilizes simple rules to
explain relationships among variables.
• This approach allows for variations and outcomes
that aren’t fully predictable.
• Complexity represents an attempt to overcome
the limitations of the analytic/ reductionist
approach to understanding nature.

4. Background
• Complexity science is concerned with the
interconnection between “agents,” or units or
components of a larger system.
• Many concepts of complexity science come from
chaos theory, quantum mechanics, and nonlinear
mathematics.
• According to chaos theory, even though the
behaviors with a system may appear random, when
analyzed using nonlinear approaches, they exhibit
dynamic, patterned variation.
• Away from machine metaphor.

5. Roots of Complexity Science (1 of 3)
• Complexity science is rooted in both nonlinear
mathematics and coordination dynamics.
• Nonlinear mathematics focuses on interactions
among variables (rather than the variables
themselves) to explain complex changes over
time and space.
• Nonlinear approaches can be applied when data
do not exhibit a normal distribution or fall close
to the norm.

6. Roots of Complexity Science (2 of 3)
• Major concepts of nonlinear mathematics
include:
– A focus on simple rules
– Coupling: the strength of relationships among
functional units
– The view that system behavior is deterministic
rather than random
– Sensitivity to initial conditions
– Fractals and Self-Similarity
– Scaling
– Emergence

7. Roots of Complexity Science (3 of 3)
• Coordination dynamics is the study of
patterns of coordinated behavior in living
things.
• Major concepts of coordination dynamics
include:
– Pattern dynamics
– Complementary pairs
• Offers a way to address the whole-part
phenomena.

8. Complex Adaptive Systems (1 of 2)
• A complex adaptive system (CAS) is a
collection of individual agents:
– With the freedom to act in ways that aren’t
always predictable
– Whose actions are interconnected so that the
action of one agent changes the context for other
agents
• CAS is a network.

9. Complex Adaptive Systems (2 of 2)
• Within a CAS:
– Control is decentralized and dispersed
– Coherent behavior arises from competition and
cooperation among the agents
– The agents follow simple rules, are in constant
dynamic interaction, and can generate complex
structure.
• A CAS has a high degree of adaptive capacity and
is characterized by self-similarity, complexity,
emergence, and self-organization.

10. Components of CAS (1 of 2)
• A CAS consists of agents that interact within the
system according to patterned behavior.
• Agents are units or components of the system:
– Agents interact in a particular way
– These patterns of interaction enable the system to
function in a way that cannot be understood by
examining the system components separately
– An individual agent may also be a CAS and/or be part
of multiple systems

11. Components of CAS (2 of 2)
• Patterns are formed by agents acting from a
set of internalized rules:
– Agents have patterns of behavior that evolve over
time
– A CAS can develop rules that shape the interaction
among agents and therefore affect the agents’
patterns of behavior

12. Characteristics of CAS (1 of 2)
• Complex adaptive systems:
– Connected to other components in a system
– Are dynamic and adaptive
– Are supported by simple rules
– Exhibit the property of emergence
– Are self-organizing
– Are marked by distributed rather than centralized
control
– Exhibit diversity

13. Characteristics of CAS (2 of 2)
• Complex adaptive systems:
– Are deterministic
– Are marked by multiple layers of embeddedness
– Involve coordination dynamics
– Are sensitive to initial conditions
– Are sites of co-evolution
– A robust system can respond to external and internal
changes

14. CAS, Complex Responsive Processes,
and Organizations (1 of 2)
• Some scholars view organizations as CASs:
– Here, traditional management theory is seen as
too structured and hierarchical
– According to this view, leaders can promote
flexibility, creativity, emergence, and innovation
by providing employees with only general
direction and a few basic rules and allowing for
innovation and rewards

15. CAS, Complex Responsive Processes,
and Organizations (2 of 2)
• Other scholars argue that organizations are not
CASs but rather groups that exhibit complex
responsive processes (CRPs):
– According to this view, organizational knowledge is found
in the relationships and conversations between the people
in an organization
– These everyday conversations raise the potential for both
continuity and change
– Within nursing, CRP approaches are an important part of
relationship-centered care (RCC)

16. Implications for Practice (1 of 2)
• Practice has various size systems that are related and
connected through relationships.
• Health care organizations (HCOs) are examples of
higher-order complexity systems, because they
usually consist of several systems embedded in other
systems.
• The CAS approach is especially useful for modern
HCOs because rapid system changes make creativity,
autonomy, and flexibility more important than ever
before.

17. Implications for Practice (2 of 2)
• Viewing an HCO as a CAS promotes the emergent
model of leadership, in which an organization’s
leaders are collaborative co-participants with the
people they supervise.
• This approach also opens up new models for
research, such as action research, studies of
positive deviance, and appreciative inquiry.

18. Application to Health Care
and Nursing
• Within the clinical setting, the CAS approach
has led to equipment and methods that offer
more variability to individual patients and are
more attuned to pattern identification.
• The CAS approach also fits well with the
nursing’s holistic view of the individual.

19. Conclusion
• Complexity science focuses on relationships
among variables and allows for emergent
behaviors.
• Complex adaptive systems consist of agents
whose behaviors aren’t always predictable yet
always affect the context for other agents.
• Both complexity science and CASs represent an
alternative to the reductionist view and fit well
with modern health care and nursing.