From The Laws of Medicine, a short book by Siddhartha Mukherjee:
My medical education had taught me plenty of facts, but little about the spaces that live between facts. I could write a thesis on the physiology of vision. But I had no way to look through the fabric of confabulation spun by a man with severe lung disease who was prescribed “home oxygen,” but gave a false address out of embarrassment because he had no “home.” (The next morning, I got an irate phone call from the company that had attempted delivery of three canisters—to a Boston storefront that sold auto parts.)
I had never expected medicine to be such a lawless, uncertain world. I wondered if the compulsive naming of parts, diseases, and chemical reactions-frenulum, otitis, glycolysis—was a mechanism invented by doctors to defend themselves against a largely unknowable sphere of knowledge. The profusion of facts obscured a deeper and more significant problem: the reconciliation between knowledge (certain, fixed, perfect, concrete) and clinical wisdom (uncertain, fluid, imperfect, abstract).
Medicine is a soft science involving the application of limited knowledge amidst uncertainty. Historically, it was wholly unscientific. In the modern era, we apply the philosophy of Karl Popper:
In his 1934 book, The Logic of Scientific Discovery, the philosopher Karl Popper proposed a crucial criterion for distinguishing a scientific system from an unscientific one. The fundamental feature of a scientific system, Popper argued, is not that its propositions are verifiable, but that its propositions are falsifiable-i.e., every theory carries an inherent possibility of proving it false. A theory or proposition can only be judged “sci-entific” if it carries within it a prediction or observation that will prove it false. Theories that fail to generate such “falsifiable” conjectures are not scientific. If medicine is to become a bona fide science, then we will have to take up every opportunity to falsify its models, so that they can be replaced by new ones.
Mukherjee posits three “laws”:
LAW ONE
A strong intuition is much more powerful than a weak test.LAW TWO
“Normals” teach us rules; “outliers” teach us laws.LAW THREE
For every perfect medical experiment, there is a perfect human bias.
These amount to: 1) The conditional probability of Bayesian reasoning means that bad tests done indiscriminately yield more noise than information. 2) Outliers shouldn’t be ignored, but should be studied. The rare exceptions often drive our discoveries. 3) Cognitive biases are an inescapable part of the human condition.
Regarding medicine as presaged by Lewish Thomas, who in 1983 published the most popular book about the dawn of modern medicine in The Youngest Science:
Thomas would not have predicted this stickiness of uncertainties and constraints; the future of medicine that Thomas had imagined was quite different. “The mechanization of scientific medicine is here to stay,” he wrote optimistically in The Youngest Science. Thomas presaged a time when all-knowing, high-precision instruments would measure and map all the functions of the human body, leaving little uncertainty and even fewer constraints or gaps in knowledge. “The new medicine works,” he wrote. “The physician has the same obligations that he carried, overworked and often despairingly, fifty years ago-but now with any number of technological maneuvers to be undertaken quickly and with precision…. The hospitalized patient feels, for a time, like a working part of an immense, automated apparatus.
He is admitted and discharged by batteries of computers, sometimes without even learning the doctors’ names. Many patients go home speedily, in good health, cured of their diseases…. If I were a medical student or an intern, just getting ready to begin, I would be more worried about this aspect of my profession. I would be apprehensive that my real job, taking care of sick people, might soon be taken away, leaving me with the quite different occupation of looking after machines.”
In reality, things have panned out quite differently: despite the increasing accuracy of tests, studies, and equipment, the doctors of today have to contend with priors, outliers, and biases with even deeper and more thoughtful engagement than doctors of the past. This is not a paradox.
Ironically, Thomas’s passage from 1983 feels more prescient about current fears than Mukherjee’s from 2015.