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Wearables and Devices Will Drive a New Paradigm in Managing Clinical Data
[This is the third in a series of posts by Intel’s Chuck Freedman, API Strategist and Director of Vertical Insights, looking at the benefits of APIs from many perspectives. Through these articles, Chuck will explore how the value APIs deliver appear differently to consumers, developers, partners and others benefitting from APIs. Read the first and second posts.]
Within the past 2 years, your wrist has become prime quantified data collecting real estate. Chances are you are one of the tens of millions of consumers who have purchased a wearable device to monitor your activity and fitness. With the device, you also enjoy a companion app which visualizes and helps you evaluate data collected by your fitness wearable on the screen of your mobile phone, tablet, or on your desktop.
The projections range, but most experts agree that sales of wearable devices will increase and likely double in the next 2 years. ABI Research forecasts the global market for health and fitness wearables to reach 170 million devices by 2017. Leading the market are accelerometer and sensor-driven bands and watches that track movement, sleep, posture, calories burned and more. These devices have dedicated shelves and displays at major retailers like Best Buy and Apple stores.
Popularity of activity tracking devices is being driven by platforms and apps aggregating, interpreting and sharing your data in new ways. These services, effectively API customers of the data generated by devices, allow users to link together and track use in new ways. CarePass, from Aetna, lets you choose your own devices and app use towards achieving fitness goals. Sites like fi.tt focus on counting steps, while rewarding users for their achievements in a social context.
While activity tracking devices fall under the category of fitness and health, they are, in a medical sense, all available “over the counter”. Even the FDA-approved BodyMedia Armbands, collecting 5000 data points per minute including body temperature, targets health professional at a level of wellness and weight management programs. These activity/fitness/lifestyle devices and apps have earned their place on a user’s body. However, new waves of wearable technologies, some equally stylish, with capabilities of more clinical use, are about to engage consumers as patients on a different level.
The value proposition for wearables in health will soon start to go well beyond activity tracking and fitness use. Key sensors will expand personal data collected to include heart rate, blood oxygen level, blood pressure and more. Slightly more invasive devices allow mobile evaluation of blood sugar and other aspects of blood chemistry. Users can also manually input fitness and diet information into mobile devices to create a more complete picture of their quantified self as it pertains to healthcare.
Beyond their technical capabilities and targeted healthcare use, there are several distinctions between these types of health wearables to consider.
The nature of data will drive more dedicated use.
Considering how and why a device will be used, it should yield more dedicated quantified data being collected. Unlike the activity devices, which can be worn or taken off at the user’s casual discretion, devices intended to track more specific health conditions will likely be used at constant or specific, even prescribed, times. In the activity world, wearing a device to track steps taken and activity during the workday, while hiking or working out is a choice the user can make day to day. However, once you depend on a device to measure vitals like heart rate or blood sugar, the user will likely need to adhere to certain times to capture measurement, or benefit from constant monitoring for days at a time.
The purpose of clinical devices could determine their availability to consumers and patients.
User interest in devices capturing more clinical data should create enough demand to see many of them generally available in popular retail channels. However, the potential prescribed or managed use of a device for the purpose of collecting clinical data should determine its availability to consumers or patients. Consider the difference between over the counter cold medicine and antibiotics. Mitigated risk to a consumer is apparent in how these are distributed.
With newly available clinical devices, proper use of this kind of device, especially to obtain its data in a secure manner, will rely on instruction and guidance of a care provider. Depending on market potential and cost to manufacturer, these devices, like their prescription drug counterparts, may also require (or benefit from) insurance coverage to obtain. These factors affect popularity, availability and general awareness of a product, which means these devices, may only be presented to a user or patient when needed.
Managing personal health data between device and provider means managing personal health data.
Earlier I detailed how activity/fitness devices with well-managed platforms are being easily aggregated into other apps and services. While they do obtain data specific to a user, we can all agree the number of steps a user takes on a given day is a relatively benign compared to vital information like blood sugar count. In order for new clinical devices to be effective tools for evaluating a user or patient’s health, data must, at some point, must be associated with the user themselves. This is where data crosses into a territory of personal health records, personally associated data, which is subject to layers of compliance and policy.
The approach of making this device data available at any degree of openness through APIs to partners and developers is no longer viable. Unlike their activity and fitness device counterparts, wearable devices with a clinical purpose will need to subscribe to new platform strategies and architecture. Certainly, data can be de-identified and made available for research purposes in a more traditional open manner. However, platforms managing access to user-associated health data need to establish a more secure and compliant API approach where the end-recipient of that data is as managed as the data itself. New data distribution models will be adopted where intermediary services, likely owned by health institutions, can own the flow of data from device all the way through to the care provider evaluating it.
Experience working with decades of healthcare policy will meet more recently established API management best practices. These solutions are emerging just as new clinical devices and wearable technology merge the quantified self with the healthier body. We are arriving at a time where available technology and managed data can give care providers deeper and more cost affective insight into a patient’s health.