By all indications, 2013 will mark the emergence of a much more sophisticated set of tools for people to track--and diagnose--their own health problems. AliveCor, an iPhone case that can conduct an electrocardiogram, and, naturally, transmit the test to the cloud, just gained clearance from the FDA and is set to begin shipping in January. The project is aimed, at least initially, at patients with arrhythmias and other minor heart problems that need watching, to monitor their cardiac health. Meanwhile, Scanadu, has gotten a lot of attention--including from Co.Exist--for its efforts to develop a medical tricorder that can test for 15 different conditions that it plans to release next year.
At first glance, these devices may not seem that significant. As fascinating as I find AliveCor, for example, I don’t anticipate buying one next year. And this may be because devices like AliveCor and Scanadu are driven by a deceptively simple idea. As cheap sensors are being built into phones, cars, and even everyday objects like coffeemakers to help aid in diagnosis, people can--and should--take advantage of them to manage their own health.
But this simple idea hints at a much broader transformation set to take place over the next decade: As technologies enable us to bypass the doctor and measure our own health continuously, we will almost certainly need to turn to artificial intelligence and other automated tools of big data to help sort the signals of significant health concerns from the noise of random, day-to-day changes in health. Together, this combination will not only reshape how and where we interact with traditional health providers, but ultimately redefine the basic skills and work of medical professionals.
Perhaps no project better exemplifies the transformative combination of ubiquitous measurement and diagnosis by algorithm than the Parkinson’s Voice Initiative, which is an incredibly ambitious effort to diagnose Parkinson’s before its symptoms take effect. The idea is that before physical symptoms manifest, Parkinson’s patients have subtle changes in their voices that precede the disease. To find those subtle changes, the project’s leads want to turn the entire phone system into a massive medical data mining operation, where by virtue of calling a friend, your likelihood of having the early stages of Parkinson’s is being diagnosed in the background.
The potential value here is enormous. Early diagnosis for Parkinson’s, like most diseases, opens up opportunities to start treatments much sooner, slow the disease down, and enable people to start preparing to deal, emotionally and socially, with the disease.
At the same time, it’s worth pausing to consider how creepy it could feel to call your spouse to figure out whose turn it is to cook dinner after work, only to get an automated message from the phone company telling you to make an appointment with a doctor because you probably have Parkinson’s. This is, of course, the problem with automated diagnostics--most of us don’t want to learn of a debilitating illness from a machine.
And so it’s here that we can see the future of how we should expect to interact with our doctors: not as independent actors who serve as the major source of authority, but as professionals who can help us sort through and make sense of all of the different information coming from our phones, cars, and coffemakers and treat the emotional, as well as physical components of health and well-being.