After years of trying to build a market for themselves, wearable devices have started to find purchase in the larger marketplace. And while casual devices like the FitBit are gaining traction, the application of more specialized wearable medical devices hold a lot of potential. But the big picture application of these devices don’t come from personal information but from the big data analytics they can provide. Combined with machine learning, electronic health records, and virtual doctor’s visits, these devices can rapidly facilitate big medical advantages.
The problem is that the medical community has yet to figure out exactly what to do with this data. While servers are filling up with piles upon piles of information on patients, much of this information doesn’t read the medical professionals who can put it to good use. Many medical professionals look forward to a future where an emergency room patient’s medical bracelet can be scanned, providing doctors with detailed health records as well as current vitals, but the real challenge is finding out how to reach this level of integration.
And while these sort of analytics can play a big role in emergency situations, they can be just important when it comes to preventative care. Diagnosing conditions based off of the anecdotal and sometimes inaccurate reporting of patients is tricky, but when you combine the analytics that wearable devices and electronic records provide with assisted analysis from A.I. and other technological methods, doctors have far more tools available to them. This could take the form of machines that recognize voice tremors that could indicate Alzheimer’s or EKG features that help patients identify heart irregularities before they become more serious. There’s a great amount of potential for these technologies to serve as diagnostic tools, and devices like the newest Apple Watch are already starting to integrate these technologies in consumer end products.
Finally, analytics can help the healthcare industry prevent medical fraud, a major issue estimated to cost the industry more than a billion dollars every year. A.I. that can identify tonal inconsistencies in phone calls could red flag and prioritize potential fraud cases and help isolate bad actors within the healthcare sector.
There’s a lot of promise in these emerging technologies, but it’s not something that the healthcare industry can tackle alone. For these innovations to take hold, they’ll require a greater saturation of these type of technologies in the consumer market and more initiative from private organizations willing to help develop the infrastructure necessary.