Posted by: DrJosephKim
fitness, medical device, mhealth, quantified self
We seem to be hearing the term “big data” in healthcare a lot these days. After all, the use of EHR systems across the country have led to huge amounts of health data that needs to get analyzed so that clinicians can deliver more effective care. The focus will shift from collecting data to analyzing and using that data effectively.
So, while that’s happening across hospitals and major health systems, patients are going out and shopping for self-monitoring gadgets. This year at CES, we saw several new “quantified self” (QS) gadgets from major manufacturers like Fitbit, Basis, and several others. Nike is out there with their Nike+ Fuelband. You’ll see billboards featuring this device across the country. Jawbone is taking a second round at their Up self-tracking wristband. Misfit Wearables will be coming out with a waterproof metal tracking device called the Shine.
Plus, these devices aren’t simply glorified pedometers anymore. Some are incorporating biometric sensors that will measure heart rate, skin temperature, metabolic rate, blood pressure, and much more. Soon, we may see these devices incorporated into continuous glucose monitoring sensors for patients with diabetes. Or, we may track all-day blood pressure in patients who have high blood pressure (hypertension). Where will it end? More importantly, who’s going to have time to look at all this data and decipher what is clinically significant vs. background “noise” that has no significance?
We don’t have a clear answer because there is no sustainable reimbursement model supporting the QS movement right now. Early adopters who are using self-monitoring gadgets to stay more motivated to lose weight and exercise more and experiencing clinically beneficial weight loss, increasing cardiovascular capacity, and better overall fitness. However, doctors would love to jump on the QS movement and play a role if someone would be willing to reimburse them for their time.
At the end of the day, we’ll need to see IT systems that can crunch and decipher all the QS data to filter what’s clinically meaningful so that doctors and other health care professionals can provide useful advice to patients. That’s the next phase for QS. Right now, there are computer systems that can scan breast mammograms or cardiac EKGs to detect abnormal patterns. Once the system flags the abnormality, it must get confirmed by a human (usually a doctor) before the results get sent to a patient. In the same way, someone will build such an ecosystem for some of these QS devices. Of course, this means that the device will now get classified as a medical device that must get FDA clearance, so I’m sure that the majority of QS devices won’t pursue that route. On the other hand, some will explore that option, particularly if the device is specific to a chronic disease like diabetes or hypertension. That’s what I’m waiting to see. I predict that by 2015, we’ll see some of these QS medical devices in mainstream use.