“This book is about information, imperfection, uncertainty, and the future of medicine. “
“I studied cell biology, anatomy, physiology, pathology, and pharmacology. …. But all this information could, I soon realized, be looked up in a book or found by a single click on the Web. The information that was missing was what to do with information—especially when the data was imperfect, incomplete, or uncertain. “
“I had never expected medicine to be such a lawless, uncertain world. “
“The “laws of medicine,” as I describe them in this book, are really laws of uncertainty, imprecision, and incompleteness. They apply equally to all disciplines of knowledge where these forces come into play. They are laws of imperfection.”
“Looking back, I realize that I lived for a year, perhaps two, like a clockwork human, moving from one subroutine to the next. Days folded into identical days, all set to the same rhythm. By the end of my first month, even “flex” had turned into reflex. The only way to break the deadly monotony was to read.”
“...a fundamental question: Is medicine a science? If, by science, we are referring to the spectacular technological innovations of the past decades, then without doubt medicine qualifies. But technological innovations do not define a science; they merely prove that medicine is scientific”
“Physics is replete with such laws… There are fewer laws in chemistry. Biology is the most lawless of the three basic sciences: there are few rules to begin with, and even fewer rules that are universal. “
Law One - Intuition ------------------------
Patient was seriously ill, but illness cannot be diagnosed from battery of tests. A chance observation of a conversation between two patients in the hospital cafeteria sparked an intuitive diagnosis. “a test can only be interpreted sanely in the context of prior probabilities. “
“You need a strong piece of “prior knowledge”—I’ve loosely called it an intuition—to overcome the weakness of a test.”
“The “prior knowledge” that I am describing is the kind of thing that old-school doctors do very well, and that new technologies in medicine often neglect. “Prior knowledge” is what is at stake when your doctor—rather than ordering yet another echocardiogram or a stress test—asks you about whether your feet have been swelling or takes your pulse for no apparent reason.”
“It applies not only to medicine but to any other discipline that is predicated on predictions: economics or banking, gambling or astrology. The core logic holds true whether you are trying to forecast tomorrow’s weather or seeking to predict rises and falls in the stock market. It is a universal feature of all tests.”
Law Two - Outliers -------------------------
Kepler’s Law - because Kepler refused to dismiss the outlying (unexplained) “backwards” movement of Mars.
“1908, when psychiatrists encountered children who were withdrawn, self-absorbed, emotionally uncommunicative, and often prone to repetitive behaviors, they classified the disease as a strange variant of schizophrenia. But the diagnosis of schizophrenia would not fit.”
“Children with this disease seemed to be caught in a labyrinth of their own selves, unable to escape. In 1912, the Swiss psychiatrist Paul Eugen Bleuler coined a new word to describe the illness: autism—from the Greek word for “self.””
“Medicine is in the midst of a vast reorganization of fundamental principles. Most of our models of illness are hybrid models; past knowledge is mish-mashed with present knowledge. These hybrid models produce the illusion of a systematic understanding of a disease—but the understanding is, in fact, incomplete. “
“Every outlier represents an opportunity to refine our understanding of illness.”
One success case out of many failures are often dismissed or regarded as one patient anecdotes. “The trouble with such “exceptional responders,” as Solit called them, was that they had traditionally been ignored, brushed off as random variations, attributed to errors in diagnosis or ascribed, simply, to extraordinary good fortune. “
“We have spent much of our time in medicine dissecting and understanding what we might call the “inlier” problem. By “inliers,” I am referring to the range of normalcy; we have compiled a vast catalog of normal physiological parameters: blood pressure, height, body mass, metabolic rate. Even pathological states are described in terms that have been borrowed from normalcy: there is an average diabetic, a typical case of heart failure, and a standard responder to cancer chemotherapy.”
“ 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.”
Law Three - Bias ---------------------
On success rates of recoveries from new drugs administered to patients assigned to young residents. “The assignment had no premeditated bias, yet the simple desire to help patients had sharply distorted the experiment.”
“Every science suffers from human biases. Even as we train massive machines to collect, store, and manipulate data for us, humans are the final observers, interpreters, and arbiters of that data. In medicine, the biases are particularly acute for two reasons. The first is hope: we want our medicines to work. Hope is a beautiful thing in medicine—its most tender center—but it is also the most dangerous. “
“when you enroll a patient in a study, you inevitably alter the nature of the patient’s psyche and, therefore, alter the study. The device used to measure the subject transforms the nature of the subject.”
“The reverential status of randomized, controlled trials in medicine is its own source of bias. “
“These distortions—call them heuristic biases—are not peripheral to the practice of medicine. Virtually every day I’m asked to decide whether a particular drug will work for a patient—an African-American man, say—when the trial was run on a population of predominantly white men in Kansas. Women are notoriously underrepresented in randomized studies. In fact, female mice are notoriously underrepresented in laboratory studies. “
“Extracting medical wisdom from a randomized study thus involves much more than blithely reading the last line of the study published in some august medical journal. It involves human perception, arbitration, and interpretation —and hence involves bias.”
“The advent of new medical technologies will not diminish bias. They will amplify it. More human arbitration and interpretation will be needed to make sense of studies—and thus more biases will be introduced. Big data is not the solution to the bias problem; it is merely a source of more subtle (or even bigger) biases.”
“The greatest clinicians who I know seem to have a sixth sense for biases. They understand, almost instinctively, when prior bits of scattered knowledge apply to their patients—but, more important, when they don’t apply to their patients. They understand the importance of data and trials and randomized studies, but are thoughtful enough to resist their seductions. What doctors really hunt is bias.”
“Priors. Outliers. Biases. That all three laws of medicine involve limits and constraints on human knowledge is instructive. “
“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. Tests and therapies may have evolved, but so has medicine itself. “
“In Lewis Carroll’s Through the Looking-Glass, the Red Queen tells a bewildered Alice that the queen has to keep running to stay in place—because the world keeps running in the opposite direction. “
“This experiment—and hundreds of similar studies at the frontiers of medicine—suggest that human decision making, and, particularly, decision making in the face of uncertain, inaccurate, and imperfect information, remains absolutely vital to the life of medicine. There is no way around it. “”
““The [political] revolution will not be tweeted,” wrote Malcolm Gladwell. Well, the medical revolution will not be algorithmized.”
Oh, and the very last line of this chapter, of this book! Has to be about politics and tweeting. How accidentally prophetic. Published Oct 2015. Can’t help but laugh (or cry, or both!)
“I studied cell biology, anatomy, physiology, pathology, and pharmacology. …. But all this information could, I soon realized, be looked up in a book or found by a single click on the Web. The information that was missing was what to do with information—especially when the data was imperfect, incomplete, or uncertain. “
“I had never expected medicine to be such a lawless, uncertain world. “
“The “laws of medicine,” as I describe them in this book, are really laws of uncertainty, imprecision, and incompleteness. They apply equally to all disciplines of knowledge where these forces come into play. They are laws of imperfection.”
“Looking back, I realize that I lived for a year, perhaps two, like a clockwork human, moving from one subroutine to the next. Days folded into identical days, all set to the same rhythm. By the end of my first month, even “flex” had turned into reflex. The only way to break the deadly monotony was to read.”
“...a fundamental question: Is medicine a science? If, by science, we are referring to the spectacular technological innovations of the past decades, then without doubt medicine qualifies. But technological innovations do not define a science; they merely prove that medicine is scientific”
“Physics is replete with such laws… There are fewer laws in chemistry. Biology is the most lawless of the three basic sciences: there are few rules to begin with, and even fewer rules that are universal. “
Law One - Intuition
------------------------
Patient was seriously ill, but illness cannot be diagnosed from battery of tests. A chance observation of a conversation between two patients in the hospital cafeteria sparked an intuitive diagnosis. “a test can only be interpreted sanely in the context of prior probabilities. “
“You need a strong piece of “prior knowledge”—I’ve loosely called it an intuition—to overcome the weakness of a test.”
“The “prior knowledge” that I am describing is the kind of thing that old-school doctors do very well, and that new technologies in medicine often neglect. “Prior knowledge” is what is at stake when your doctor—rather than ordering yet another echocardiogram or a stress test—asks you about whether your feet have been swelling or takes your pulse for no apparent reason.”
“It applies not only to medicine but to any other discipline that is predicated on predictions: economics or banking, gambling or astrology. The core logic holds true whether you are trying to forecast tomorrow’s weather or seeking to predict rises and falls in the stock market. It is a universal feature of all tests.”
Law Two - Outliers
-------------------------
Kepler’s Law - because Kepler refused to dismiss the outlying (unexplained) “backwards” movement of Mars.
“1908, when psychiatrists encountered children who were withdrawn, self-absorbed, emotionally uncommunicative, and often prone to repetitive behaviors, they classified the disease as a strange variant of schizophrenia. But the diagnosis of schizophrenia would not fit.”
“Children with this disease seemed to be caught in a labyrinth of their own selves, unable to escape. In 1912, the Swiss psychiatrist Paul Eugen Bleuler coined a new word to describe the illness: autism—from the Greek word for “self.””
“Medicine is in the midst of a vast reorganization of fundamental principles. Most of our models of illness are hybrid models; past knowledge is mish-mashed with present knowledge. These hybrid models produce the illusion of a systematic understanding of a disease—but the understanding is, in fact, incomplete. “
“Every outlier represents an opportunity to refine our understanding of illness.”
One success case out of many failures are often dismissed or regarded as one patient anecdotes. “The trouble with such “exceptional responders,” as Solit called them, was that they had traditionally been ignored, brushed off as random variations, attributed to errors in diagnosis or ascribed, simply, to extraordinary good fortune. “
“We have spent much of our time in medicine dissecting and understanding what we might call the “inlier” problem. By “inliers,” I am referring to the range of normalcy; we have compiled a vast catalog of normal physiological parameters: blood pressure, height, body mass, metabolic rate. Even pathological states are described in terms that have been borrowed from normalcy: there is an average diabetic, a typical case of heart failure, and a standard responder to cancer chemotherapy.”
“ 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.”
Law Three - Bias
---------------------
On success rates of recoveries from new drugs administered to patients assigned to young residents. “The assignment had no premeditated bias, yet the simple desire to help patients had sharply distorted the experiment.”
“Every science suffers from human biases. Even as we train massive machines to collect, store, and manipulate data for us, humans are the final observers, interpreters, and arbiters of that data. In medicine, the biases are particularly acute for two reasons. The first is hope: we want our medicines to work. Hope is a beautiful thing in medicine—its most tender center—but it is also the most dangerous. “
“when you enroll a patient in a study, you inevitably alter the nature of the patient’s psyche and, therefore, alter the study. The device used to measure the subject transforms the nature of the subject.”
“The reverential status of randomized, controlled trials in medicine is its own source of bias. “
“These distortions—call them heuristic biases—are not peripheral to the practice of medicine. Virtually every day I’m asked to decide whether a particular drug will work for a patient—an African-American man, say—when the trial was run on a population of predominantly white men in Kansas. Women are notoriously underrepresented in randomized studies. In fact, female mice are notoriously underrepresented in laboratory studies. “
“Extracting medical wisdom from a randomized study thus involves much more than blithely reading the last line of the study published in some august medical journal. It involves human perception, arbitration, and interpretation —and hence involves bias.”
“The advent of new medical technologies will not diminish bias. They will amplify it. More human arbitration and interpretation will be needed to make sense of studies—and thus more biases will be introduced. Big data is not the solution to the bias problem; it is merely a source of more subtle (or even bigger) biases.”
“The greatest clinicians who I know seem to have a sixth sense for biases. They understand, almost instinctively, when prior bits of scattered knowledge apply to their patients—but, more important, when they don’t apply to their patients. They understand the importance of data and trials and randomized studies, but are thoughtful enough to resist their seductions. What doctors really hunt is bias.”
“Priors. Outliers. Biases. That all three laws of medicine involve limits and constraints on human knowledge is instructive. “
“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. Tests and therapies may have evolved, but so has medicine itself. “
“In Lewis Carroll’s Through the Looking-Glass, the Red Queen tells a bewildered Alice that the queen has to keep running to stay in place—because the world keeps running in the opposite direction. “
“This experiment—and hundreds of similar studies at the frontiers of medicine—suggest that human decision making, and, particularly, decision making in the face of uncertain, inaccurate, and imperfect information, remains absolutely vital to the life of medicine. There is no way around it. “”
““The [political] revolution will not be tweeted,” wrote Malcolm Gladwell. Well, the medical revolution will not be algorithmized.”
Oh, and the very last line of this chapter, of this book! Has to be about politics and tweeting. How accidentally prophetic. Published Oct 2015. Can’t help but laugh (or cry, or both!)