Think about the last piece of technology you bought that didn't work as expected.
What did you do? Return it? Give it away? Put it in a drawer with its sad digital cousins?
Most likely the stakes accompanying your poor experience were low, and you simply chalked it up to the cost of being an early adopter. What you didn't do was abandon the field completely. If you were lucky enough to have spent your hard earned money on a Betamax, when that platform failed you didn't swear off all forms of recorded entertainment. If you thought Chumby was the future of internet appliances, you haven't refused to use an iPad or Alexa strictly on principle. And if you were one of the faithful who waited in line to buy the first iPhone — the one that Apple's formerly senior director of marketing, Bob Borcher, reportedly apologized for — you haven't gone back to a flip phone or landline. You've upgraded and moved on.
The Cube didn't kill Apple. The Fire Phone didn't kill Amazon. The Nexus Player didn't kill Google.
This is the mindset Silicon Valley has brought to every space it enters: A bad product or poor user experience doesn't have any ramifications beyond that particular product or experience, and they can always wipe the slate clean and start again.
In the world of digital health this is a big problem. Here are three reasons why:
Unlike other consumer products, digital health products connect users to their own mortality. Although we refer to them as "health" products, the current crop is primarily focused on diagnosing, screening and managing illness and disease. Unless you have a specific need, most people would rather "get busy living" than "get busy dying." In other words, the ultimate stakes for current digital health products are, by design, life and death. This differentiates them from all other products these companies design and sell.
Digital health products require buy-in from both the user and their health care provider. Simply using a health-related device or app is not enough. A user must close the loop with a clinician before any meaningful action can take place. So if a patient uses a digital health product but their health care provider won't accept and incorporate the results into their treatment, it's a fail. And if a primary care doc recommends a device, but the consumer doesn't use it as "prescribed" (for any of a number of reasons) it's also a fail.
The old adage, "You don't get a second chance to make a first impression" is especially true in healthcare. This is because when adopting new technologies, the marketplace performs a kind of calculus that evaluates perceived benefit, perceived risk, cost, maturity and history. Or for the poets, how much good will let us put up with the possibility of bad; how bad is bad enough before it outweighs the possible good; what's the track record of those making claims about the possibilities of good and bad so we don't get fooled (again); and what does it all cost? With health, a bad outcome can be truly disastrous.
As a result of each of these elements, early mistakes can have a lasting impact that reverberate beyond the offending company to impact an entire industry, affecting both the regulatory landscape and broad public perception.
Think about Theranos.
The blood-testing company's collapse has resulted in skepticism across the medical, regulatory, and investment landscape. Every new microfluidics testing venture is now subject to both increased scrutiny and has to to overcome a general suspicion regarding the technology, its effectiveness, and actual benefits. In other words, everyone who follows Theranos has the burden of proving they're not Theranos before even getting to the question of whether their product will pass the risk/benefit analysis discussed above.
While this is not unique in the digital health space —consider recent stories regarding autonomous vehicle accidents and how that colors the way the entire field is perceived — the size of the healthcare market and relative ease with which products can be developed, as well as the current appeal of applying algorithms and machine learning to the imprecision of the human body, requires that extra care be taken. High tech cannot view digital health as simply the next great market opportunity.
Robin Goldstein recently completed a 22-year-tour at Apple where she served in multiple roles across the company, including Senior Engineering Manager, Principal Counsel, Associate Instructor at Apple University, and most recently Senior Manager of Health Special Projects.