Under most circumstances, the ability to recall facts, to memorize, to follow an established order or process is generally considered a mark of intelligence or ability., But under unfamiliar conditions of uncertainty, the ability to analyze and respond intelligently require different methods of thinking.
Methods we have not explored as well or as thoroughly as we should have during this pandemic, instead reverting to more familiar tendencies and processes that have netted mistake after mistake. At first, we sought miracle drugs and ran ad hoc clinical studies verifying, then refuting, and again reverifying the efficacy of drugs repurposed from other diseases into a makeshift COVID-19 treatment.
In hindsight we were clearly putting square pegs into round holes, and the results were about as effective as you would imagine based on that analogy. Studies produced questionable results with serious side effects the likes of which at times outweighed any purported benefit. Yet we kept searching for new drugs, novel solutions, like a veritable modern-day holy grail search. When hydroxychloroquine was rendered marginally effective at best, we tried remdesivir, when that too proved marginal, we tried another – and another – all with marginal at best results.
And as we head into the heart of Fall 2020, the treatment options we have available are all collectively marginal at best.
Iterative approaches to drug development and trialing is nothing new, and really the standard approach to developing therapeutics. And while it may appear that repurposing medications for bacterial and autoimmune conditions for a viral condition seems a stretch at best, the rationale in using the medications was to address the inflammatory process that appears similarly among different infection types and is the major exacerbator for adverse clinical outcomes.
Indeed many hospitals have developed protocols that use a combination of these medications to mitigate the inflammatory responses among patients in critical conditions due to COVID-19.
Yet these are marginal improvements at best. And healthcare researchers are scrambling to find other options or therapeutics that may build up the efficacy of these protocols.
Which leads me to ask: what if we are wrong in our approach to COVID-19 treatment?
It seems we continuously try to compare COVID-19 to other diseases, viruses, or inflammatory processes in an attempt to find a semblance of familiarity out of something grossly unfamiliar and uncertain. And we find ourselves marginally improving at best.
Which is ironic, because the solution is in the uncertainty itself – if we can study it. But healthcare has a tendency to simplify the unknown and approach linearly that which is inherently complex. If we see a patient with an array of unknown symptoms and signs, we break each symptom and sign down piece by piece, step by step, until we relate it to something more familiar, more easily processed.
That is the mode of thinking in healthcare, simplify and make linear. Which has worked well in a normal, stable world – before COVID-19. And one of the reasons why people love to proclaim that COVID-19 has “changed everything” – aside from trying to jump start their improvised career as futurologists – is because COVID-19 upended the core assumptions that we take for granted in how we approach medicine.
What were once known constants are now variables. And when you have enough constants or stable factors turning into variables, the system goes from simple and linear to complex and uncertain.
And in a complex world, the uncertainty is the defining feature. The probability of certain movements, of certain trends, of certain symptoms and signs can never be defined with full certainty.
And many of the greatest thinkers who studied the universe understood how to think through this complexity. Albert Einstein developed his famed theories of relativity by applying complex mathematical frameworks called Riemannian geometry into physics. He was among the first to realize that probability, and therefore uncertainty, are the governing principles in the universe.
A universe in which healthcare is a part of, yet we fail to recognize the complexity part of healthcare when we approach novel and uncertain clinical scenarios. Not because we are incapable of studying the uncertainty, but largely because the methods through which we are trained to think in healthcare are not conducive for studying uncertainty.
When faced with uncertainty, we must rely on the mental faculties that promote imagination rather than the traditional mode of thinking that has come to represent healthcare. In the former, we appreciate the uncertainty and study what we do not know. In the latter, we simplify the uncertainty and reframe it into what we have seen before or what is familiar.
Which explains why we try to define COVID-19 in terms of what we have seen or what we know, when we should explain COVID-19 in terms of what we do not know, and allow the uncertainty to guide our thinking.
This is not to say we should simply look at every symptom, every patient, and every clinical scenario as though it is something brand new. Rather, we should apply associative principles of thinking to understand healthcare – principles of thinking we find in imagination in which two things that may not directly be related are compared, consequently enhancing the overall quality of understanding.
A recent Nature article found that machine algorithms can approximate physician decision-making by integrating associative thinking into the model. In other words, if an algorithm can combine the linear thinking commonly seen in healthcare with association patterns relating less commonly seen concepts, then the outcomes of the machine algorithm are equivalent to a physician’s outcomes.
Which may seem obvious enough – combine common and less common factors together and you will be right often. True enough. But the implications of this study are more important than the actual results. This study demonstrates that imaginative thinking, nonlinear associative thinking along less common lines can improve clinical outcomes.
Much like how Einstein took complex mathematical functions and applied them into the burgeoning field of Quantum Mechanics, thereby revolutionizing modern physics, we can revolutionize decision-making processes in healthcare by focusing on imagination, the associative patterns of thought that cross correlate things that may not be obvious but things that are related in ways to improve our understanding.
Healthcare cannot afford marginal advancements, not with the heightened pace of advancement spurred on by COVID-19. We need dynamic steps forward, dynamic modes of thinking to advance healthcare.
We need to use our imaginations.
Opioid epidemic in one chart – correlation conflated with causation
There is no cause-and-effect relationship between prescribing and overdose mortality. But millions of patients are being denied safe and effective pain care.
Seniors over age 62 are prescribed opioids for pain three times more often than youth under age 19. But youth have overdose rates three times higher than seniors. No medical model can explain these demographics.
Source: Richard A Lawhern, PhD, Patient Advocate