There’s this story about the first combat airplane cockpit, designed in 1926 by the U.S. Army. Big believers in standardization, the military first calculated the dimensions of the “average” male pilot, then designed the seat, pedals, stick, and all the rest to fit this average man. By the 1950s (and with the creation of the Air Force), the military was trying to figure out why so many pilots in training were losing control of their planes and dying.
They eventually came to two conclusions. First, the “average” male had gotten bigger in the 1950s. Second, and more importantly, not a single studied pilot matched the “average” in all dimensions. In designing for an “average” man, they were building a cockpit that wasn’t a good fit for anyone. (The original men were also all white, and women weren’t even considered (but that’s a conversation for another day.) Their solution? Make the seats, pedals, and stick adjustable, so the cockpit could be adapted to every individual.
Data Destroys the Norm
It’s no secret that this Information Age we live in is an era of big data, or that this data is frequently mined for insights into our beliefs and behaviors. Mass marketing is losing ground to hyper-targeted advertising and personalized consumer experiences. Mass manufacturing is being replaced by custom fabrication. And in healthcare, my industry, mass medicine is slowly giving way to data-driven healthcare.
This is really important in healthcare, because, as with those airplane cockpits, there has never been a “normal” patient. I’m not only referring here to the longstanding systemic racial and gender bias in who has been studied in medical research, though that is part of the problem. Diagnostic tests and medicines tested on “average” American white men frequently turn out to not work quite the same for women and people of color.
But I’m saying something more than that. Even that normal white man is an illusion. He doesn’t exist. Medicines prescribed to treat that normal man will almost always be an imperfect treatment for every individual man, for every person. Even identical twins aren’t really the same.
So how can you baseline normalcy? The more we look, the more we see that each individual is unique and that our attempts to put them in a category never really quite work.
When a marketing campaign or a production run mistargets a normal person who turns out to not exist, some money is wasted or maybe some products are never sold. When medicine gets it wrong, people get sick, stay sick, or die.
Fortunately, just as data-driven marketing and manufacturing have personalized the consumer experience, data-driven medicine is individualizing healthcare. Medical laboratories like mine can now use pharmacogenomics to test for genetic variations that influence a patientâ€™s response to certain medicines. We can even study the metabolism of certain molecules in patientsâ€™ bodies.
This isn’t abstract research available only to people enrolled in a study. This is applied science available to physicians and patients right now, and it’s the basis of a revolution in precision medicine.
Who Does the Data Serve?
So, it’s good news that data is destroying the illusion of normal and replacing it with something far more personal. But who does all this data serve? Too often, it’s not the consumer, the patient, nor the person whose data has been gathered and mined.
Many people today have justifiable concerns about all the information social media and search companies have gathered about them. This is data farmed, gathered, then sold as a commodity to whoever is willing to pay.
Yes, some regulations, such as the European Union’s General Data Protection Regulation (GDPR) and HIPAA attempt to curb this, but the economic model remains one in which people are treated as products. The customers are advertisers, big businesses, and, in my industry, insurance companies. In this country, with our still broken healthcare insurance system, many patients understandably fear what insurers will do with their data.
This all comes from anxiety over losing control of information about us, a fear that this information will be used by entities that don’t have our best interests at heart. When data can reveal the many ways in which each of us are different from the illusory norm, great power passes to those who control that data.
The Good Business of Empowering People With Data
So, what if the person who controlled that data was the person who that data was in reference to? What if we shifted our understanding of who all that data is for?
There’s an assumption in business today that individuals won’t pay fair market value (or, in some cases, won’t pay anything) even for very valuable information and services. Everything has to be cheap or free to the consumer in order to scale up and create a crowd that you can sell to.
What if that’s wrong, though? What if consumers, patients, and people value more than commodity services at the cheapest possible prices? What if they value control over their data? What if they want to be empowered with knowledge rather than monetized?
I think they are, and it’s the path my company has chosen: to produce valuable information that we use to empower patients and their doctors. People pay more for our genetics tests. Doctors order studies that the insurance companies don’t want to reimburse, studies that allow them to better serve their patients’ health. They’re not just purchasing information. They’re purchasing the healing power of knowledge.
I don’t think this model is limited to healthcare. People are increasingly fed up with the mediocrity of free. They’re seeing the costs of giving up their information to companies that turn around and sell it. They want to take back control. They want information that empowers them rather than enriches some faceless corporation. They’re tired of being a product. I think they’re ready to own who they are.