The advent of low-cost wearable technologies, like Fitbit, Apple Watch, Garmin, and others, combined with near medical-grade precision and cloud-based applications are well positioned to change the way we interact with the healthcare industry.
In the very near future, many of us may be receiving proactive healthcare advice ranging from modifications to our exercise, diet, and recovery regimes to preventative treatment for potential ailments or disease based on personal, GPS, and local, regional, national data. Much of this may be possible with low-cost artificial intelligence (AI) or human learning (HL) similar to the machine learning (ML) applications that tap into the most current medical data bases.
New innovative healthcare technology is one step away
These changes may not happen overnight but societal pressures and the free market economy will create new compelling business models to provide some degree of healthcare-as-a-service based upon these new Internet of Things, edge, and data center enabled platforms. This will help address the legacy issues of the traditional healthcare industry, which has long been challenged with increasing costs associated with applying the latest and greatest technology to improve accuracy and speed of diagnosis. The machines and systems, along with the knowledge gained from the data they produce, have led to an improvement in both the length and quality of life.
However, the vast majority of these devices are large, expensive systems that reside within a medical facility and require trained technicians to operate them. Access to these machines, be they CT, CAT scanners, ultrasound machines, or a ‘simple’ stress test with ultrasound require both a clear indicating condition and a prescription from a doctor for the test. For many people the inconvenience factor alone is enough cause to postpone visiting a doctor. Such a delay may lead to a worsening condition where emergency treatment is required to deal with a life-threatening condition that could have been identified and addressed much earlier for a significantly lower cost with readily available wearable and consumer-based technology.
Wearable technology (healthcare applications) could be the right method to avoid this inconvenience
Now with connected wearables from watches to activity trackers combining heart rate and GPS data (location, elevation, speed, rate of climb) with the data freely shared on web-based applications like Strava (my profile), Garmin Connect, and FitBit you have the basis for some amazing medical / healthcare applications. Especially when the activity data is combined with information from a ‘smart scale’ and a food / calorie tracking application.
Some organizations are already leveraging wearable device data, although the depth of analysis is typically limited to factors such as the numbers of steps walked in a day, amount of exercise, weight gain or loss, and heart rate, which are used for determining applicable health insurance costs, discounts, or incentives.
However, we can do much more than merely reward good behavior. Now, with access to all this data and more (gym use/visits/applications, weather, daylight, etc.) your doctor will be able to provide new levels of healthcare service from insights gained from analyzing this data.
For example, those recent runs where you just didn’t reach your normal pace may have been indicators that you were on the verge of a cold or worse because business travel the previous week exposed you to the flu. Or maybe your resting heart rate and changing sleep patterns are suggesting work / personal life stress and a change in routine, diet, or some quality downtime are necessary lest you push your body too hard and succumb to overtraining / overworking and suffer a physical breakdown.
Not that data alone will supplant the need for a physical or blood chemistry analysis but many conditions can be screened by merely looking at heart rate, stress, weight, and exercise. There may be no need for expensive and time-consuming tests when you voluntarily perform a ‘stress test’ three or more times a week on your bike ride, run, or swim and already provide that detailed data to one or more service providers.
What if we could centralize all this data to better understand our healthcare needs?
Even though we are already providing this data freely to numerous, disparate applications across the web, once we bring the data together either directly or by authorizing our medial provider to aggregate the data from the various applications, the collected data and resulting analysis become protected data subject to HIPAA, GDPR, and a host of other data protection and privacy laws. Therefore, this information must now reside within a robust, secure data center environment and the transmission of reports or correspondence between the doctor / medical service, or even the AI/HL application, must be secure, protected, and properly stored in accordance with local regulations.
Meaning what was a mere collection of data from low-cost consumer-grade IoT devices connected at the edge of the network and used in applications spread across numerous data centers, becomes an entire system that requires some degree of availability and reliability to truly maximize the value proposition of the data.
Data that may save your life someday.
