Nope – it turns out you could do worse. Hans Rosling of the Karolinska Institute in
Sweden explains how.
Asked to teach a course on Global Health to Sweden’s
top undergrads, Dr. Rosling administered a pre-test to see what the class
already knew. Five questions in the
pre-test consisted of a pair of countries, and students were asked to select
which of the two countries had a higher infant mortality rate. To keep
things sporting, he made sure that, in each pair, one country had at least
double the infant mortality rate of the other.
On average, the students scored
1.8 out of 5. (In an amusing bit of self-deprecation, he confessed that this
made him happy because now he had a job and his course had a place in the
institute.) The problem, he observed, wasn’t ignorance, it was preconception. These top students knew statistically
significantly less about world health than chimpanzees, who, he noted, would have
scored a 2.5 answering randomly for banana bonuses.
Just so you don’t think this
world-renowned researcher was picking on his students, he also performed what
he called an “unethical” study on the professors at the Karolinska
Institute. These are the folks who hand
out the Nobel Prize for medicine. They
scored on par with the chimpanzees with 2.4 correct answers.
Dr. Rosling told this story
as an introduction to his TED talk, “Stats That Reshape Your Worldview”, which
he delivered in 2006. Yes, that’s right
– 2006. Why did I bother to blow the
dust off of a 7 year-old presentation? Because
the chimp comparison is comic and the insight is brilliant. As you read the news and watch world events
unfold, you may begin to notice, as I have, how often false preconception, rather
than ignorance, explains the ill-advised behavior that seems to be everywhere.
The other reason I chose to
write about this TED talk is because current efforts to advance healthcare using
big data reminded me of the kind of data wrangling I watched Dr. Rosling perform. Out of the information mined from millions of
patient EMRs, registries, and insurance claims, GNS Healthcare has created enormous
datasets from an impressive list of collaborator companies and institutions. The data is run through analysis algorithms that
can then be used to predict whether a given treatment is likely to work for a given
individual – one of a given gender, age, ethnicity, symptomatology, and genetic
mutation. PatientsLikeMe also performs
data analysis to help patients assess likely outcomes of particular therapies. The data they use come from subscribers of patientslikeme.com, a health
data-sharing platform of 200,000 members suffering from over 1000 different
diseases. Both organizations are among a
growing number in the industry that believe the way to less expensive, more
effective healthcare can be found in data.
In fact, as members of Orion Bionetworks, a new alliance of private
industry, non-profits, and research hospitals, they will be collaborating to
develop predictive models for Multiple Sclerosis and other chronic diseases.
Dr. Rosling would be
proud. His TED talk has over 5,000,000
views, so maybe you saw it. If not,
here’s the link: bit.ly/ZEyZhU . It’s excellent, and as far from a boring PowerPoint
presentation as you can get.
Jamie Heywood, the founder of
PatientsLikeMe, also delivered a TED talk in 2009: bit.ly/17Mgtf8 . An MIT grad, Jamie talks about the sophisticated
algorithms used by the investment industry, and asks, “Wouldn’t it be great if
the technology we use to take care of ourselves was as good as the technology
we use to make money?”
Yes, yes it would.
by Laurie
Meehan
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