Posted by Michael Douglas
The healthcare industry is brimming with interesting IoT applications. According to Andy Castonguay, Principal Analyst at Machina Research, The U.S has the highest spending per capita for healthcare in the western world - 22% of America’s GDP was spent on healthcare between 2014 and 2015. Expert panels at IoT World in Santa Clara discussed how connected things can solve some of the industry’s main challenges around reducing costs and improving patient care. How IoT can do that:
Presenters took care to mention the need for a more efficient “Feedback Loop,” or using the data produced by users and machines to improve healthcare data and adjust further inputs for increasingly better results. However, this feedback loop is inhibited in many ways.
Consumer adoption of personal connected devices such as Fitbit or Jawbone are on the rise, and these devices are constantly collecting data (a person's movement, certain body metrics, and changes over time). However, there is a wide chasm between FDA-approved data and data produced by other means such as wearables. This mountain of data might be useful for what’s called “patient self reported data,” which could potentially help doctors better assess patient needs and improve the healthcare system as a whole. This leads to the question: what’s the value of wearable devices focused on fitness? If this data isn’t utilized by doctors to improve health outcomes, is it all a waste?
It’s still unclear if all doctors will take advantage of self-reported patient data. One method to make self reported data more useful is to contextualize it with time and location - giving users more accurate data to bring to their doctors. Christine Lemke, co-founder and President of Evidation Health stated “You can’t take data that you don’t know if you can trust to make clinical decisions on, there needs to be a lot more validation on use cases, devices and data sets.” Data analytics will play a huge part both with FDA and non-FDA approved data to help doctors make better informed decisions.
Some corporations are starting to implement penalties within their wellness programs for employees who refuse to use corporate supplied wearable devices by making them pay more for their insurance. We then must question the validity of such initiatives if the actual data used is not FDA approved and cannot and will not be used by doctors.
Perhaps one of the most interesting components of IoT in healthcare is preventive medicine. For example, how do we prevent illness or sickness before it occurs using these connected devices. One of the most innovative examples of this was Propeller Health, a company that has developed a solution for Chronic Pulmonary Disease sufferers. They have placed a Bluetooth chip at the top of an asthma inhaler which is collecting data on the amount of medicine inhaled by the patient, and frequency of inhaling. The inhaler is connected to an app on a smartphone that is in turn pinging the user to ask what their level of discomfort or pain is and the user is then able to enter that data into the app. Once you combine the two sets of data together it starts to show a more comprehensive and interesting picture of what’s happening with that patient and can lead to fewer visits to the hospital by adjusting their inhaler medication accordly. According to Castonguay “Early indications from the data leads Propeller Health to believe that the solution is reducing acute care visits from between 15-20%.”
Judging by the Propeller Health example, we can see how IoT devices are helping clinicians make more informed decisions based on data derived from both devices and users. If wearable device companies such as Fitbit or Jawbone want to have a sustainable future and truly improve users’ lives, they may need to fundamentally rethink their business models. Going through FDA approval, providing extensive clinical trial studies, proving use cases such as Heart Attack reduction, and reduction in type 2 diabetes may become essential. Device OEM's taking on this responsibility will have to take care to avoid producing inaccurate data that could potentially put lives at risk.