By: Sam Petrie
In early April 2019, I had the opportunity to visit the University of Tennessee at Knoxville, and attend the 4th International Conference for Complexity and Systems in Healthcare. A mouthful to begin with, which was reflective of the content of the conference. All the presentations had a common thread weaving them together: using complexity science in the local space of the presenter – usually with positive results.
Excited by hearing about these success stories, I was equally as disappointed to learn that following some complexity-informed intervention, most institutions, units, or healthcare authorities went back to their old ways. Linear implementation schemes, followed by equally linear and top-down evaluation. The results are foreseeable for scholars of complexity science: continued unforeseen consequences, unproportionable change in outcome as it relates to change in system, and wasted dollars.
This left me perplexed. If there are numerous success stories being told, why was leadership reluctant to hear them? More importantly, why are there so few people at this conference? Certainly, if complexity science has such potential, there should be hundreds of people attending, from all silos of health sciences.
That was not the case.
So then, what’s the problem? Complexity science is – believe it or not – complex. Although for the people working with complexity science the problems it describes from a systems perspective seems intuitive, there is a steep learning curve for ascertaining just exactly what complexity science is.
Debate has occurred ever since it’s inception as to whether complexity science can be a definitive tool – useful in crafting solutions to the modern-day wicked problems of healthcare provision – or if it is merely descriptive. Useful for articulating the barriers to implementation or research diffusion, but nothing more.
Even if it is ‘only’ descriptive: so what? Albert Einstein, oddly enough, had this insightful opinion on solving conundrums: “The mere formulation of a problem is far more often essential than its solution, which may be merely a matter of mathematical or experimental skill.” Einstein got it right (yet again). Often times in healthcare, we come up with a solution to the wrong problem.
The mere formulation of a problem is far more often essential than its solution, which may be merely a matter of mathematical or experimental skill. – Albert Einsten
You can see this in rural eHealth, where hospitals want to optimize latency without having a dedicated space for eHealth consultations to begin with. Optimizing latency with nowhere to physically hold the consultation quite obviously limits the impact of eHealth initiatives. Complexity science helps researchers, decision-makers, and frontline healthcare professionals make sense of their environment. Understanding the complexity of the system you are a part of can go a long way in crafting an overall better system.
Which brings us back to the main point: why aren’t more people using it? This question was answered by Kevin Northup – an established complexity thinker, and great presenter. People instinctively block what they cannot understand. If you work in complexity science, the goal shouldn’t be to promote it as the ultimate paradigm in which to work. It should be to find compatibility with complexity science and logical positivism or ‘the scientific method’ which dominates lab sciences (as it rightly should).
Dialogue should exist wherever possible between different parts of the system – fostering a transparent and open atmosphere has many established benefits to organizational health. Conversations between complexity science truthers and doubters shouldn’t be to anoint one paradigm better than the other, but to find common ground. Mr. Northup also had some advice on that: focus on when complexity science isn’t there, versus when it is, and how the outcomes change. Complexity science shouldn’t replace traditional scientific methods, but supplement them, leading to impactful solutions.
My hope is that through my research I can show how using a complexity informed approach can lead to tangible benefits for patients, providers, and the system as a whole. But this approach has to co-exist with the established rules and regulations already in place within rural healthcare systems. Complexity science isn’t trying to overthrow the old establishment, but help guide it through a time of fiscal constraints, aging populations, and the continuous leadership turnover associated with a cyclical political environment.
Complexity science has some of the answers – but not all of them. If scholars want to see complexity science taken more seriously, perhaps it starts with doing away with tribalism of academia, and realizing we are all in this (currently sinking) ship together. Maybe then we see complexity science utilized more frequently in decision-making, implementation, and systems design.