Emerging Concepts in Medical Education V: Complexity

This is the last post from Elaine van Melle  in the “Emerging Concepts” series. See here for her previous posts on the process to identify emerging concepts in medical education and discussions on social media and financial incentives, systems thinking, hand over and global health, and professional identify and emotion.  In this finale, the influence of complexity science is addressed.

– Jonathan


1. What is complexity science?

Complexity occurs when many connected parts are intertwined. The clinical consultation is a good example of complexity. As part of the consultation, the clinician, patient and others (e.g., family members, social service agencies, media etc.) interact. It is through their interaction that the course of action emerges; a course which may be non-linear and unpredictable. Accordingly, the clinical consultation can be referred to as a complex adaptive system where

  • ‘complex’ implies a great number of connections between a wide variety of agents;
  • ‘adaptive’ suggests the capacity to evolve; and
  • ‘system’ is the set of interdependent parts or agents.

Simply stated then, complexity science is the study of complex adaptive systems (CAS).

2. Why is complexity science important?

In healthcare we are surrounded by CAS. For example, at the level of the individual, health is a quality that emerges through the interaction between physical, emotional and social experiences. As already described, the clinical consultation can also be characterized as a CAS where numerous participants interact to produce healing. The healthcare system itself consists of multiple interacting agents such as hospitals, clinics, nursing homes, patients’ homes, health care providers, families and patients. Complexity science is important because it provides a way of making sense of the authentic world: dynamic, unpredictable, emergent, evolving and adaptable.

3. What challenges does complexity science present?

Typically, in trying to understand these systems, the approach has been to examine the individual parts. Such a ‘reductionistic’ or ‘mechanistic’ approach has its limitations; understanding the parts does not necessarily explain how the system functions as a whole. For example, although much is now known about the structure and sequencing of DNA, we still have limited understanding as to how a specific disease is triggered. What is required is a shift to examining overall system behaviour. Complexity science, with its emphasis on examining the relationship among parts, provides this focus.

4. How does complexity science apply to the CanMEDS Roles?

Under conditions of complexity, knowledge is an uncertain and emergent phenomenon. This perspective has implications for each of the Roles. For example, in the Medical Expert Role, complexity requires the physician to be able to deal with uncertainty as part of the clinical consultation. Under conditions of complexity, clinical practice is described as being ‘emergent’ where treatment is not a static, single act, but rather becomes the accumulation of small acts which are continually revisited and reassessed on an ongoing basis.

In closing . . .

It is important to acknowledge that not all situations exhibit characteristics of complexity. For example, in the clinical consultation complexity is minimized where there is a high degree of certainty about the correct course of action and agreement among the individuals involved. And so, it is important to note that complexity science is meant to complement, not replace, other (e.g. reductionist) ways of analysis.

Figure 1 – A Complex Adaptive System: Semiautonomous agents interact such that they create system wide patterns which subsequently influence later interactions of the agents.  Reproduced with permission (Eoyang & Holladay, 2013)


Selected References

Capra F. 2002. The Hidden Connections. A Science for Sustainable Living. New York, NY: Random House.

Cresswell JW, Klassen AC, Plano Clark VL. Best practices for mixed-methods research in the health sciences. Bethesda, MD: National Institutes of Health.

Eoyang GH, Holladay RJ. 2013. Adaptive Action: Leveraging Uncertainty in Your Organization. Stanford, CA: Stanford University Press.

Fenwick T. 2012. Complexity science and professional learning for collaboration: a critical reconsideration of possibilities and limitations. Journal of Education and Work. 25:141-162.

Hafferty FW, Castellani B. 2010. The increasing complexities of professionalism. Acad Med 85:288-300.

Johnson S. 2001. Emergence: The Connected Lives of Ants, Brains, Cities and Software. New York, NY: Scribner Publications. IBM Systems Journal 42(3):462-483.

Kernick D (Ed.) 2004. Complexity and Healthcare Organization. Oxon, UK: Radcliffe Medical Press.

Lingard L, McDougall A, Levstik M, Chandok N, Spafford MM, Schryer C. 2012. Representing complexity well: a story about teamwork, with implications for how we teach collaboration. Med Ed 46:869-877.

Lipsitz LA. 2012. Understanding healthcare are a complex system: The foundation for unintended consequences. JAMA 308:243-244.

NAPCRG. North American Primary Care Research Group. 2009. A complexity science primer: What is complexity science and why should I learn about it?

Snowden DJ, Boone ME. 2007. A leader’s framework for decision making. Harvard Business Review :1-8.

Sturmberg JP, Martin CM. (Eds). 2013. Handbook of Systems and Complexity in Health. New York, NY: Springer+Business Media.