Canadian Health Care Is A Complex System

In previous writings, I considered how components of traditional diffusion of innovations, knowledge-attitude-practice (KAP), and positive deviance (PD) could be applied to my practice of thoracic surgery.  Within this realm I function primarily as a health advocate assisting my patients in the multiple facets, surgical and other, of navigating through their illnesses.  In this present paper I will consider the other component of my health care provider dialectic, the health activist.  As a health activist I strive to empower and emancipate individual Canadians toward playing a role in achieving health care system change.  The take home lessons to be operationalized in pursuit of health care change relate to complex adaptive systems and how they pertain to my proposed study of Canadian health care through Appreciative Inquiry (AI). 

Health care is complicated and complex

The Canada Health Act, implemented in 1968, provides federal oversight to the provision of health care by individual provinces and aims to enhance the well-being of Canadian residents through facilitating access to health services (  The federal government exerts influence in the enforcement of the five tenets of the CHA: public administration, comprehensiveness, universality, portability, and accessibility, through the funding agreement with the provinces in the Canada Health Transfer (CHT) Accord (  The CHT agreement expires in 2014 and is already the topic of intense political discussion (Wingrove, Howlett, Seguin, & Moore, 2011).  Canadian health care is an issue that has been extensively studied over the past ten years through several national expert driven problem based forums including: the 2002 Romanov Commission (http://www.hc-sc.gc./hcs-sss/hh-rhs/romanov-eng.php), the 2001 Kirby Report (, and the 2002 Mazankowski Report (  Glouberman and Zimmerman (2002) consider Canadian health care reform from the perspective that many health experts incorrectly employ a complicated system paradigm to issues more correctly viewed through a complex adaptive system lens (p. 2). 

A question to consider is whether health care is primarily: a complicated system, a complex system, or perhaps a combination of both in the setting of dialectic tensions. Stacey (2002), by way of The Stacey Matrix, has attempted to categorize simple, complicated, and complex issues based upon the degree of certainty (close to – far from) on the x-axis and the level of agreement (close to – far from) on the y-axis for the issue in question.  Stacey (2002) describes simple systems existing when cause and effect linkages can be determined and this rational decision making occurs when the issue is close to certainty and close to agreement. In situations where there is either more disagreement (political decisions) or more uncertainty (judgemental decisions) the decisions can be described as complicated (Stacey, 2002).  In the extreme situation where there is both high uncertainty and high disagreement there are anarchy or chaos decisions and in the area between the chaos and complicated decisions lie the complex decisions (Stacey, 2002).  This zone of complex adaptive systems is comprised of events with interdependent constantly changing agents and emergent non-controllable outcomes (Singhal, Buscell, & Lindberg, 2010, p. 39).  The hallmark of a complex system is that the future outcomes and behaviors can not be predicted with certainty and the closest we can get to is maybe (Singhal et al, 2010, p. 39; A.Singhal, personal communication, November 25, 2011).  This uncertainty can be uncomfortable for organizations with a classic top-down problem solving culture where improvement comes from more consistency and more control.  Once it is appreciated, however, that social and human systems are complex in nature then it can be understood that the quality of the interaction in the complex relationship, as expressed through immediate authentic and accurate feed-back, is of prime importance in the maintaining a healthy system (A.Singhal, personal communication, November 25, 2011).

Glouberman and Zimmerman (2002) compare and contrast the specific theoretical, causality, evidence, and planning characteristics of complicated and complex systems in health and health care (p. 10).  Complicated systems are linear, tension and fluctuations are suppressed, the solution is external to the system, and adaptation is to a static environment while complex systems are non-linear, tension and fluctuations are seen as opportunity, the solution is part of the system, and interaction occurs with the rest of a dynamic environment (Glouberman and Zimmerman, 2002, p. 10).  The causality of complicated systems is simple, designed for certain intended predictable outcomes in contrast to the mutual causality of complex systems from which emerge uncertain non-predictable adaptive outcomes (Glouberman and Zimmerman, 2002, p. 10).  The authors describe planning in complicated systems as being focused on convergent thinking with evidence dominated by the averages and ignoring the outliers as opposed to complex systems where the focus is on divergent thinking and emergent decisions where outliers, especially the positive deviants, are seen as possible key determinants in the process (Glouberman and Zimmerman, 2002, p. 10).  Papa, Singhal, and Papa (2006) summarize four main principles of complex social systems: mutual causality – interdependent emergent outcomes, butterfly effect – big change can occur from small interactions, valuing outliers – deviance provides valuable insight, and celebrating paradoxes – tapping the power of polar opposite ideas (pp. 235-241).  If these are key components to a complex adaptive systems then methodologies, such as Appreciative Inquiry, utilized to study health care and to organize for system change must be consistent to these principles.

Appreciative Inquiry in health care

Appreciative inquiry (AI), first described by Cooperrider and Srivastra (1987), is a strengths based approach to organizational and system change that explores ideas that people have about what is valuable and tries to work out how these ideas can lead to knowledge creation about the social world (Reed, 2007, p. 2; Danielle & Cooperrider, 2008, p. 190).  In the AI process participants address a chosen affirmative topic through a dialogue laden 4-D cycle of: discovery, dreaming, designing, and destiny. (Cooperrider , Whitney, & Stavros, 2008, p. 5; Reed, 2007, p. 35).  In the discovery process, individuals engage in a positive question based one-on-one dialogue to discover the most vital and alive moments and stories in relation to the affirmative topic (Cooperrider et al., 2008, p. 6).  In the dream stage participants work together to creatively build on the collective outcomes of the discovery stage to envision new ideas of what might be in a preferred future (Cooperrider et al., 2008, p. 6; Reed, 2007, p. 35). In the design stage participants work together to co-construct an ideal vision through a provocative proposition based on what has worked well in the past and what has been envisioned for the future (Cooperrider et al., 2008, p. 7; Reed, 2007, p.35).  The destiny stage directs the energy toward realizing the provocative proposals through thinking and committing to specific tasks and actions (Cooperrider et al., 2008, p. 7; Reed, 2007, p. 35).  The main assumption of the 4-D AI model is that an organization is not a problem to be solved but is rather a solution to be embraced (Cooperrider, Whitney, & Stavros, 2008, p. 5; Reed, 2007, p. 26). 

Reed (2007) notes that the social constructionist and critical theory worldviews most closely reflect the central tenets of AI as a research framework (p. 56).  Social constructionist knowledge and worlds are negotiated and co-constructed through dialogue and in critical theory the role of inquiry is to challenge established processes in an attempt to emancipate participants from the restrictions of the established order (Reed, 2007, p. 58).  This critical construction of reality in AI corresponds closely with Paulo Freire’s idea of the necessary role of dialogue and people’s participation in social change development (Papa et al, 2006, p. 164).  In AI the teacher – facilitator expert – is learner and the learner – participant – is teacher in a collective iterative transformative process that enables people, as described by Freire, to be engaged in their own welfare (Papa et al, 2006, p. 164).  AI remains true to the four main principles of complexity science as outlined by Papa et al. (2006, p. 234).  There is mutual causality in AI as the outcomes of the process are truly emergent, uncertain, and non-predictable. AI encourages the provocative proposition which celebrates the paradox and embraces the tension of the dialectics.  The bottom-up participatory nature of AI allows small positive changes to have the potential to create large effects and the positive deviant outliers in AI have the stories which are discovered and ultimately processed into destiny where this action leads to a new way of thinking.

Conclusion: Applying AI to the complex system of Canadian health care

My specific operationalization will be to apply these lessons to my thesis research where I will conduct an AI dialogue around Canadian health care with 48 members of the Kelowna community who represent the widely divergent socio-economic, educational, and health spectrum of Canadians.  AI, through its critical and social constructionist world view and the close alignment of it principles to complex adaptive systems, is an ideal methodology to be utilized to study health care through participatory dialogue with the goal of creating positive system change within Canadian health care.  Glouberman and Zimmerman (2002) attempt to refine the questions asked of the Canadian health care system by moving the perspective from that of a complicated system to a complex system (p. 25).  Possibly this should be taken further as the questions should be allowed to emerge when they are ready from a holistic interdependent relationship involving all Canadians.  We have had many outside-expert derived studies of Canadian health care so let’s now hear from the real inside-experts, all Canadians.

I remain mindful of the fact that we exist in a social system that can at any time or in any circumstance be functioning anywhere within Stacey’s certainty – agreement matrix and complexity, complicated, simple, and chaos can all co-exist. What I see now and will strive to remind myself of is the fact that dialectics exist, whether they are between complicated systems and complex systems or between any of the other polarities that we encoumter. The dialectic tension is what gives life to human systems. 


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