Unraveling Complexity: An Introduction to Systems Thinking
Discover how systems thinking can transform your understanding of healthcare.
This blog is based on a topic covered in Episode 1: Complex Systems & the Improvement Toolbox, with Dr. Kedar Mate.
If you haven’t listened to it yet, check it out on Apple, Spotify, Substack or wherever you get your podcasts.
Introduction.
In today’s complex and interconnected world, you can’t go far without bumping into the term system.
Whether it’s the vastness of the solar system, local politics, or our very own circulatory system - the world is full of them. These systems are often complex, dynamic and can have unexpected patterns.
Narrow approaches fall short.
Historically, the method of reductionism has been very effective - that is breaking things down into small and smaller pieces or fundamental phenomena1. From there, we categorize and study those tiny puzzle pieces, usually in isolation.
While this has served us incredibly well in many scientific disciplines, it does have some limits. These fundamental phenomena are nested in a system and have complex interactions. By zooming in too much, we can miss the full picture.
It’s like trying to understand the global economy by reducing it down to just a single dollar bill.
Something more holistic.
One such approach to this is called Systems Thinking (from System Dynamics2). This model provides a way to help see the bigger picture and uncover the ‘how’ and the ‘why’ of a system. Through this understanding, we can then leverage opportunities to improve systems by restructuring them3.
So what is a system?
In a crude sense, a system is just a group of things, interacting, within a border, performing some function over time.
Note that the function may not be the intended function, but it is what is observed regardless.
“Every system is perfectly designed to get the results it gets.”4
The ‘things’ (components) within a system, can be anything - people, processes, tools, as long they’re interconnected.
In reality, anything could be a component, and everything is interconnected. So to stop us from including the entire universe in our system, some pragmatic choices will need to be made.
This means creating a border to enclose the system and determining the appropriate level of detail of components and their interconnection(s).
In healthcare, borders can be contentious. They are often predefined by our history, politics, culture, economics, funding etc. Sometimes for good reason, sometimes not. So depending on the question, narrowing down to the essentials you wish to examine can simplify the approach. This will take some trial and error.
Next, take a closer look at the interconnections (relationships) between those components. There you will see how things flow between them, such as energy, effort, resources and information.
Finally, stepping back from the system once all the pieces are in play, we can then deduce the true function of the system.
What systems thinking allows you to see.
When you apply systems thinking some unique patterns emerge. Patterns not found by just looking at components but found when looking at the system as a whole. In other words, you find a system is more than the sum of its parts (emergence).
By then closely observing the components, relationships and flow of information over time, the system reveals its true behaviour.
Feedback loops combine these features and illustrate their behaviour through their interactions. These interactions, then feedback into the loop and influence subsequent cycles.
Above is a simplistic example of a hypothesised causal loop diagram that shows how hiring staff impacts quality, satisfaction and clinic reputation, which in turn then impacts the hiring of staff and so on.
One can imagine, how each element interacts with the next, potentially creating a positive or negative feedback loop.
Illustrated from left to right above, hiring new staff could improve the quality of care - as the preexisting staff now have more time to care for their patients. This in turn causes an improvement in staff satisfaction with their work as they finally have more time. This improved satisfaction then improves the reputation of the clinic due to patients now having a better experience. This feeds into the quality and quantity of new applicants.
This is an example of a reinforcing feedback loop and is denoted with an ‘R’.
Reinforcing loops results in growth. This causes amplification and can compound change in a particular direction.
The other type of feedback loop is called balancing.
Balancing loops are a source of stability. These try to keep a desired state and can also be a source of resistance when a change is attempted.
Features of systems to keep in mind.
Relationships between things may be non-linear, with unpredictable feedback loops. Thus intervening may cause a larger untended impact, which could either destabilize or embed a system.
Systems are typically resilient, often self-repairing to ensure their own perpetuation. This can mean strange or even harmful behaviours can be embedded and require careful understanding to remove.
Systems have ‘Path dependency’, which is to say particular events/outcomes are constrained by prior events/processes/decisions. Therefore identifying these areas is prime for changing the behaviour of a system.
A period of growth followed by stagnation can be caused by a shift in dominance from a reinforcing loop to a balancing loop.
Systems can be driven by the wider environment too, so be wary of impacts from the boundary.
An example of a systems diagram from Hagenaars et al, mapping the dynamics of overcoming obesity policy inertia.5
Putting this into practice.
The Action Scales Model6 is one way to approach understanding a system and identify areas of leverage.
This looks to identify several categories; events (or behaviours), structures (patterns, relationships), goals (the ambition of that system) and beliefs (norms, values, attitudes), then use this understanding to the opportunity to shift the current system towards the desired system.
Summary.
In a nutshell, Systems Thinking can offer a new way to better understand complex problems in our world. It starts first by recognising the systems we’re in and realising we can change them. If you found this introduction interesting, I’d highly recommend reading the book “Thinking in Systems: A Primer” by Donnella Meadows.
“No system are neutral…systems were all built by people, structured with our own biases…and they can be improved by people just as well” — Dr Kedar Mate.
https://en.wikipedia.org/wiki/Reductionism
http://dln.jaipuria.ac.in:8080/jspui/bitstream/123456789/2495/1/The%20beginning%20of%20system%20dynamics.pdf
Thinking in Systems: A Primer, Book by Donella Meadows
https://www.ihi.org/communities/blogs/origin-of-every-system-is-perfectly-designed-quote
https://healthpolicy.ucsf.edu/events/ihps-grand-rounds-applying-systems-thinking-health-policy-research-examples-obesity-politics
https://journals.sagepub.com/doi/10.1177/17579139211006747