The discipline and model of the complex adaptive systems also commonly referred to as complexity science has become one of the most preferred alternatives to the currently outlined paradigms. Complex adaptive systems allow for the demonstration of some of the identifiable characteristics such as unpredictability, embeddedness, self-organization, and non-linearity among others. These systems do outline evolving behaviors arising from simple rules and the interconnections (Roussel, 2016)therein among the diverse elements with porous boundaries which interact and respond to the environment. Basically, in a complex adaptive system, the understanding of individual parts does not automatically guarantee that one will gain an insight into the whole system. The understanding of the complex adaptive systems in one way or the other is complicated, non-linear, and unpredictable, since the internal and external elements have various changes, interdependencies, and perturbations.
Research on complex adaptive systems involves various disciplines providing an insightful blend of social and natural sciences. This interdisciplinary study leads to the development of system-level models as well as visions that allow for phase transition, emergent behavior, and heterogeneous agents. These are assumed complex in that they outline a dynamic network of interactions and in addition, the relationships therein are not combinations of distinct fixed units. The enormous complexities of the health care systems make it quite hard for policymakers to use various mechanical levers such as penalties, payments, certifications, and surveys to control healthcare systems as well as its accelerating costs (Begun, Zimmerman, & Dooley, 2003). These mechanical approaches often translate to unintended consequences. To help guide the future policies, and at the same time avoid the unanticipated consequences of regulations which might arise therein, physicians and policymakers need to have a better understanding of healthcare as a complex system and in that case, apply the complexity science to achieve set goals.
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The role of a leader of a complex adaptive system is to view the health care system as a mechanical system rather than a complex system. In doing so, the leader, manager or the nurse, in this case, will be able to exploit the various intrinsic properties of this dynamic behavior and guide the health care in a more favorable direction (Sittig & Singh, 2015). Some of the properties in this regard include a non-linear interaction of the component parts, emergent, dependence on simple rules and self-organized behavior.
The implementation of complex adaptive systems idea can translate into an improved organization and health care services in the sense that it defines the different aspects of team behavior. The multi-disciplinary approach of these systems allows for various entities to come together and work towards a common cause (Roussel, 2016). In working together, different healthcare entities outline the best of their care and in the process, improved patient outcomes are likely. Collaborative efforts both internally and externally can amount to a considerable boost in the organization and health care services.
A planned change theory can be applied in the implementation of the complex adaptive systems. This theory focuses more on the roles and responsibilities of the change agent. In this case, the roles and responsibilities of the multiplayers in the health care system must be reconsidered. The participation of these elements is quite important in the realization of the positive effects of the complex adaptive systems model. The change process starts with first diagnosing the problem, followed by the assessment of motivation and capacities for change in the system. After this, an establishment of the change objectives and strategies follows. In the end, the helping relationships are gradually terminated as the change becomes part of the organizational culture. So basically, the complex adaptive systems in healthcare are an important aspect which needs to be integrated into the healthcare system for better performance and improved patient outcomes.
References
Begun, J. W., Zimmerman, B., & Dooley, K. (2003). Health care organizations as complex adaptive systems. Advances in Health Care Organization Theory , 253 , 288.
Roussel, L. (2016). Management and leadership for nurse administrators (7th ed.). Burlington, MA: Jones and Bartlett ISBN 978-1-284-06762-0
Sittig, D. F., & Singh, H. (2015). A new socio-technical model for studying health information technology in complex adaptive healthcare systems. In Cognitive Informatics for Biomedicine (pp. 59-80). Springer, Cham.
