The science of complexity lays a conceptual foundation for understanding “complex adaptive systems.” What all complex adaptive systems have in common is that they are all bound by the same set of physical laws. Their “behavior,” i.e., growth, maintenance, and death, can all be described using the same set of mathematical relationships. These systems (animals, plants, ecosystems, etc.) are the most productive and functionally effective systems known to man.
Unfortunately, our health care system has not been bound by the same physical laws and mathematical relationships as other complex adaptive systems. Thus, it has not been able to implement the same mechanisms that our ecosystems and cells have in order to obtain optimization in their ability to perform a function. This is most blatantly highlighted by the fact that 100,000 to 400,000 (depending on the source) Americans die each year due to medical errors.
The integration of the science of complexity into medicine, nursing, allied, and public health is one course of action that would eliminate many of the issues currently present in our health care system.
What is complexity?
For a complete detailed explanation, I recommend taking a course on complexity, or reading Geoffrey West’s book, Scale. I will summarize to say that understanding complexity is not about understanding the individual parts of a system and their properties but understanding the manner in which the individual parts are arranged. How they are interconnected, and how this leads to a systems macroscopic behavior.
One of the most powerful technical accomplishments of the last decade was the development of neural networks. Prior to their development, things like SIRI and ALEXA would not have been possible. Neural networks were developed from understanding the arrangement of neurons not from understanding their individual properties. In order to solve the problems associated with our health care system, we need to understand the connectivity of its component parts and how the nature of that connectivity leads to its observable macroscopic behavior (medical error).
Prior to his passing, Stephen Hawking came out saying that, “The science of the next generation will be the science of complexity.” Which indicates how critical the science of complexity will be in our ability to improve medicine by inducing changes into our health care system.
Health care administration
All complex adaptive systems have some form of a feedback mechanism in place to ensure they can reach a level of optimization organically. Balancing outgrowth, repair, and performance in such a manner that allows the system to be maintained while performing its function. Feedback mechanisms are scale-invariant and substrate independent. From metabolic cascades inside of cells to hormonal axis’ within organisms to economies, feedback is absolutely essential for any complex system to adapt, maintain itself, or grow.
When feedback is ignored, the system will quickly spiral out of control and collapse: A cancerous cell ignores the feedback mechanisms that normally would trigger apoptosis. Beta cells in a diabetic person’s pancreas ignore the elevated levels of blood glucose. A wall street executive ignores feedback intrinsic to market forces and continues their excessive risk-taking.
All of these events happen at massively different scales and take place in unmistakably different forms, but they all have the same trend: when feedback is ignored, the system collapses. The cancer grows, the blood sugar rises, the patient dies, and the stock market crashes. Health care systems have little to zero feedback mechanisms in place. When they are implemented, there is an almost immediate improvement. Understanding complexity science will enable health care administrators to understand better how we can most effectively implement these all too essential feedback mechanisms into the health care system enabling the system to perform its function effectively without being compromised by the demands for safety protocols.
I once had the opportunity to interact with a nurse as she performed an NG tube insertion. As she was setting things up for the procedure, I noticed that she placed the tube bare on the table tray adjacent to the patient’s bed. I also noticed that she was not wearing gloves as she applied the lubricant, nor did she wash her hands prior to doing the procedure.
When I asked her why she didn’t wash her hands or don gloves she answered me with a quick “because the stomach is not a sterile place, you don’t need to worry about being clean.” When I specifically brought up the possibility of Clostridium difficile infection, as endospores can survive incredibly harsh conditions. She responded by saying: “C diff is a normal part of everyone’s gut flora, it only makes you sick if you take antibiotics.” (Just for reference, here is a link to the many different hypervirulent strains that have been identified.)
This single anecdote highlights one of the major problems with our health care system. Providers, more often than not, think in terms of “all or nothing.”
Medicine and nursing are not science; they are based off of it. Unlike biology or physics, there is no central unified theory of medicine.
This means that students of nursing or medicine do not have the same set of guiding principles that one has when studying mathematics or physics, and as such, must rely on memorization as the primary means to manage the overwhelmingly massive amount of information that they are required to study prior to entering their professions.
The innate response to learn new information and understand new concepts quickly is to simplify them into an “all or nothing” framework as was illustrated by the responses that the nurse gave me during our discussion.
Understanding complexity can provide a solution to the problems caused by “all or nothing” frameworks.
Complexity is all about understanding how all of the parts are interconnected, not the individual parts of a system. This framework does two things in the context of provider education:
1. It provides students a means of universally applicable concepts that enable them to digest and understand the information required for their profession. As previously illustrated: cancers, diabetes, and other various pathologies are different substrates of a more abstract concept of a system ignoring feedback.
2. It forces one to see things in terms of their dynamics and integration, rather than as blind linear reactions. Thus, complexity cannot be simplified into an all or nothing framework. This enables one to understand the critical details of a system: such as the relationships between patient, microbe, and an NG tube, all without being burdened by the excessive “baggage” of the underlying details.
Thank you to Geoffrey West at the Santa Fe Institute, and Max Tegmark at MIT as their writings on AI and complexity science are what paved the way for the material in this article.
Robert Trent is a graduate student.
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