I remember vividly at school starting a Physics course post elementary exams and was told Newton's laws were too simple. They were everything to me. I lost something when I went into the field of learning about different dimensions. I also gained something – that area of complexity – and throughout my career I have seen this vacillation between something simple and something complex.
The search
I've always been fascinated by the complexity of things and how we might understand them. Is it through mathematical equations like in economic models – yes, to an extent. How do we explain those ecosystems? More realistically, does nature and biology really treat surrogate outcomes as simply as we often believe they are? Again, it's important not to confuse association with causation.
A language for it
I am also interested in the human condition and how as a species we communicate knowledge, and it was in my MBA that I was introduced to the work of Prof Dave Snowden. He talked about stories and the rich data that is passed on through storytelling. There were many other aspects of Dave's work that fascinated me – but the Cynefin framework certainly stopped me in my tracks. The work made sense – a jet engine is complicated, a manual can be written and understood. Simple is as it says and looks at simple correlation – like Newtonian physics. Complex is truly emergent, changing all the time – a jet engine doesn't start to grow separate fuel tanks! Chaos took me to Brownian motion and random effects. Dividing the world into Complicated, Complex, Simple and Chaos and then looking at the leadership qualities in each was certainly a revelation, and something worth more exploration. Again, this is one tool in a range of tools looking at complexity.
How deep to go
The hardest thing about complexity is the depth to go to. Yes, complexity looks like you are deep down a rabbit hole. But asking the right question and understanding how a system emerges is the skill. This is not just about data and prediction – it also has a human touch, and an ability to learn. Yes, at times I got it wrong, but most times this understanding gives a clear direction of the road to travel and the strategy to follow.
Medicine
Medicine is complex at all levels – biological, clinical and organisational – and overall this has to be delivered not by oiling the cogs on a machine but with care to humans. Trial data and market share are numbers on a projection screen, but we must always remember that there are people and families behind these numbers, and they, their doctors and their health system are making endless real-time choices – most often from experience and some basis of evidence behind them – or guesses! It's here that I see the tools of complexity being employed. How can we create systems that change the biology, enable the clinical presentation and the clinical conversation through care, and lead to better outcomes – all delivered in an organisation that truly wants the patient to gain every opportunity.
It is to me why health care is a complex adaptive system, constantly evolving, constantly changing, but the constant is that there are people involved. People working hard to do the right thing, say the right thing, and most important, that the patient improves, stabilises or cures their dis-ease. Joan Tronto's ethics of care taught me that the analytical and the moral are not separate stances. To understand a complex system honestly is to hold the rational and the caring together, and to refuse to pretend that either one alone is enough.