While my interest is always in the convergence of technology like the Internet of Things and healthcare IT, the role of sensors in managing health and wellness is just exploding.
“The most popular device functionality in the wearable tech market is heart rate monitoring, with nearly 12 million such devices shipped in 2013. Pedometers and activity trackers accounted for a combined 16 million shipments over the same period.” (According to a report released Thursday by ABI Research)
– Source: New report shows smartwatches and AR glasses have their work cut out.
“The role of analytics, especially healthcare analytics, should be to inform, encourage and drive healthcare consumers to improve our behaviors or decisions without being intrusive.”
You can’t turn anywhere without reading about the latest running gadgets, fitness bands, Bluetooth blood pressure cuffs, etc. In the inevitable rush to wearable computing, one key idea can get lost: what are we doing with all of that data?
The data produced by these devices and sensors has to be interpreted and turned into information that is actionable. The fitness band that looks at your goal of 10,000 steps, sees that you are at 8,000 steps right after dinner and encourages you for one final walk around the neighborhood, will ultimately win out over all others. In order to pull off that trick, we need analytics and, sometimes, predictive analytics.
Just as the sensors are working in the background without us even taking notice, the role of analytics, especially healthcare analytics, should be to inform, encourage and drive healthcare consumers to improve our behaviors or decisions without being intrusive. The goal of healthcare analytics or informatics should be to create an environment for the healthcare consumer that makes life better, easier and more enjoyable.
An example is when the running app sees your pace slowing down towards the end of a run, then it kicks in a song with a faster pace to help you finish strong. Today those apps require you to recognize that situation and take action of pressing a button. It’s all there but it’s not automated. What we need is that invisible intelligence that recognizes the situation and then takes action to assist us.
At HIMSS 2014, we will be seeing this jump in interest in predictive analytics as it applies to healthcare, especially two distinct types of predictive analytics.
- One type is the traditional forecasting model of advanced analytics that trends past information to predict future states.
- The second type of predictive analytics is statistical models that encompass multiple feeds or variables to predict a future outcome. This modeling is rapidly moving past the arena of data scientists who create the models and is moving more within the grasp of smart business analysts. These models can predict your longevity based on multiple factors like your BMI, blood sugar readings for diabetics and other factors from your medical history.
Of course, we want to be able to predict health outcomes, especially when faced with several choices for changing our behaviors or lifestyle. It will be exciting to see how healthcare application vendors are addressing this important next step in analytics.
The use of predictive analytics could really change the nature of a patient engagement with your doctor. How will we react when we see the outcome of our current lifestyle? Will we shut off Netflix bingeing and head to the gym? See you at HIMSS 2014 to find out! Stop by Perficient’s booth #2035 and tell us what you found out!