Research into best practices for personal experiments (aka n-of-trials)

“We spend so much effort on precision in diagnosis, yet we have very little precision about treatment,” observed Dr. Eric Larson, a professor of medicine at the University of Washington.  Experts say that even for widely-studied drugs, “the trial and error approach to medicine is not cost efficient because several of the most prominent drugs […]

8) What’s ahead?

Medicine beyond the clinic: wearables + genomics + networked patients + AI Pulling together everything that’s above, we can predict the location and shape — if not the exact form — of what what’s ahead in the next 20 years.  Obviously, large chunks of the industry of medicine will remain intact. Health care specialists and institutions focused on obstetrics, orthopedics, […]

7) What does all this mean for the medical industry?

Simpler, cheaper and serving non-consumers, disruption creeps in from the edges To get a glimpse of what’s ahead for health care — both the medical industry and the consumer services that will grow up, around and below that industry — there’s no better guide than the theory of innovation and industrial life cycles first described in 1995 by Clayton Christensen, […]

6) The medical industry can’t keep up

Diagnostics and treatments already lag best practices by 17 years Given these cascading exponential changes, what might we say about the future of US healthcare, beyond the most obvious — expect the unexpected?  Let’s start with the effect of this multi-dimensional convergence of change shock waves on the existing US medical industry. First, obviously, many innovations will be […]

5) The lamp summons a new Aladdin

Inventing two extra dimensions of change The previous section looked at the many ways patient, iterative work by engineers exponentially improves the price, power and size of technology. While vast, the previous categories of improvement are, each on their own, obvious, quantifiable, predictable in scale, if not precise time-frame. Each can be easily graphed on standard […]

4) Five categories of health technology change

More of more: devices, precision, data, users, and software  To be clear, I’m not claiming that any of the genetic data or analysis above is close to 100% accurate. Or that I know what all the numbers mean. Or that the results are in any way currently actionable — unless you’re considering asking me out on a date. […]

3) A jumbo jet in every garage, a CAT scanner in every rec room

Patient, heal thyself As I’ve monkeyed with genetic tests, friends have reminded me that patients generally know a lot less than their doctors. (Yes, an eyebrow sometimes has been arched in my direction.) Overwhelmed by complexity and without years of rigorous training, patients are prone to grabbing at simple-sounding fixes. Avoid vaccines! Stop eating gluten! Gimme […]

2) A peek at my genes relating to empathy, OCD, and cheese burger risk

Recently I spit into a little plastic tube and sent it off to 23andMe. I sprang for the $200 DNA test because it was a fast, affordable way to detect genes relating to hereditary thrombophelia — a tendency to clot. I was interested because, in early October 2018, I had experienced a pulmonary embolism — in layman’ terms, clot(s) […]

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