Last March, Apple released ResearchKit, an open-source platform that allows developers to create apps that collect data for health research. From the start, results were pretty well astonishing: researchers from Stanford University who partnered with ResearchKit to create a heart health study reported that 11,000 users signed up within 24 hours.
Generally, they said, getting 10,000 study participants would take a year—and that’s if you were working with a large number of medical centers.
What that means is that health researchers could soon have access to a veritable avalanche of data, which, when organized and interpreted, could offer major insight into when and why various health crises occur.
According to some, ResearchKit and other apps like it could predict the next major outbreak of a disease like Ebola. Hence the term, “predictive biometrics.”
From tracking your sleep cycles to predicting a heart attack
Biometrics in health applications have been growing in popularity for years—the Fitbit, which measures the number of steps you take among other biometrics, is probably the one that many of us are most familiar with. But the Fitbit is just one of many devices and apps that are designed to measure our biometric data, from sleep cycles and heart rate to blood glucose levels.
Predictive biometrics are, essentially, the next step. They can be used in all kinds of settings and scenarios—aging, for example. One app, Agewell Biometrics’ Equilibrium, can accurately test and predict an individual’s risk of falling.
Other possibilities for predictive biometrics are what panelists at a SXSW event on the topic call “invisible” —in other words, the capability to gather data when we do something as simple as open an email on our phones. At random intervals, the phone could perform a quick facial scan to measure heart rate or blood pressure.
The potential amount of data that scans like that could produce is truly staggering. Already, the individual data that users of products like the Fitbit, Jawbone, and Garmin’s Vivofit are producing is being hailed as the sign of a new chapter in health.
For instance, if a person feels ill, or has a chronic condition that requires regular doctor visits, they can go to their physician armed with data on their heart rate, or glucose levels, or sleep cycles. Then the physician could potentially use those data points to aid a diagnosis or treatment plan.
When you think about what all that individual data could tell us about ourselves as a population—if it was aggregated and organized—you get a basic idea of what ResearchKit and other predictive biometric apps might be able to offer us in the near future.
That “if” is key, for as far as we currently know, there’s no standard method of organizing or aggregating the data that could come from thousands of individuals (as the author of this Fortune magazine article asks, “how is a researcher supposed to compare what the Fitbit algorithm calls a step to what the Jawbone algorithm calls a step?”). There’s also the issue of where to store all this hypothetical data, once it starts rolling in.
Think you might have an idea that will help solve these problems? Pivot International works with software and mobile app entrepreneurs all the time. We’ve even got our own team of software specialists who can work with you to make your idea a reality. Contact us today!