Before reading Dr. Eric Topol’s Creative Destruction of Medicine, I wasn’t sure what to expect. Topol, a cardiologist with a background in genetics, was a prominent figure in the take-down of Vioxx. He was at the Cleveland Clinic back then, around 2004, and has since moved to direct the Translational Science Institute at Scripps. He was a few years ahead of me in academic medicine and, by almost any parameter, far more successful.
He’s a TED speaker, I knew. From the TED bio: “Eric Topol uses the study of genomics to propel game-changing medical research.” His work sounds exciting! I first read of the new book in a recent, tech-minded interview in Wired. Seemed like it might be all theory, no touch-y, little reality. With this lead-in, I wasn’t quite prepared to like this book, although I was interested.
Topol’s book is fantastic. I couldn’t put it down because it’s chock-full of good, critical ideas about clinical medicine. The title, “Creative Destruction,” is a reference to Joseph Schumpeter’s theory of radical transformation through innovation. In Chapter 1, he outlines the “Digital Landscape” and explains, simply, how a convergence of advances in technology over the past 40 years – like personal computers, cell phones, the Internet, connectivity and instant access to data – have set the stage for a dramatic shift in medical culture and practice. Doctors, for some reason, have been slow to adapt digital technology to health care, but this is changing, fast.
One theme that emerges through the book is the capacity for technology – by “knowing” and processing so much real-time information about each person’s condition – to inform more effective, individualized treatments. This comes up in his critique of evidence-based medicine and later, when he considers progress in molecular oncology and again, in a section on the pitfalls of old-fashioned, large clinical trials involving many (hundreds or thousands of) patients unlikely to benefit.
Topol’s comfortable writing about the intersection of science and medicine as few physicians are. He describes several clinical episodes, like when the first patient with a stroke received TPA, a clot-dissolving agent. The point is, he’s been there, at some of the world’s best hospitals, where innovative treatments have been applied. But he’s also seen first-hand disappointment, too. This grounds the work. There’s a long chapter on “Biology” which offers, among other insights, a realistic critique of genetic information that many doctors don’t understand. He identifies value in hypothesis-free research, and considers high-throughput screening.
I should mention two provocative details, among many. One appears in Chapter 3, on “empowered” medical consumers. At the Cleveland Clinic Foundation, where he’d worked and served on the Board of Governors, Topol observed busy, otherwise-occupied trustees who contributed significant time and money to the hospital. One reason they did so, he says, was so they might have access to the best doctors “in case anyone in my family or I get sick” (p. 50). He cites flaws in popular hospital ranking systems, like U.S. News & World Report, and offers tips for how to find a good doctor for a particular condition, like checking publications in Google Scholar and looking for senior authors of highly-cited papers. He writes:
“The heterogeneity of the quality of care is not adequately appreciated, and all too often consumers accept the convenient, easy alternative…If this involves a physician or surgeon who does procedures or operations, it is essential to ask for the exact number of procedures performed per year and cumulatively over his or her career…” (pp. 52-53).
The point here is that physicians are not machines. Some are more capable than others, and the quality of care received depends on the doctor’s training, experience and other human qualities.
Another gem, in Chapter 11, pertains to the “science of individuality.” We’re at a threshold, Topol says, of eliminating ignorance in medicine. For doctors and informed patients who happen upon this review: idiopathic, essential and cryptogenic diseases will be gone. Instead, we’ll have conditions defined molecularly or, even if not understood, rooted in the concept of N=1. He writes:
…a new body of data that can be derived from any individual, both at baseline and after an intervention……This opportunity leverages the immense molecular biological, physiologic, and anatomic data that can be determined for any individual, and reinforces that the ultimate goal of an intervention is to have a markedly favorable impact on each n-of-1, rather than the current model, which emphasizes population medicine with the relatively small chance that any individual may derive benefit.
What he’s saying is that the more quickly and inexpensively we can gather and process details about a patient’s medical condition, the more cleverly we can apply treatments designed to help, even in the absence of large trials.
I love this idea.