Wearables, Big Data, and Analytics in Healthcare

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Wearables, Big Data, and Analytics in Healthcare

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Written by Mark Gamble

As wearable technology – including smartwatches, fitness trackers, and even clothing and shoes with integrated sensors – moves  into the mainstream, healthcare organizations are exploring ways to use these devices to simplify, transform and accelerate patient-centric care. Their goals include boosting people’s health, improving patient outcomes, streamlining manual processes and opening new avenues for medical research and epidemiology. Analytics, data visualization and reporting are central to those efforts.

Transforming Data into Insight and Action

Wearables today can monitor and gather wearers’ activity level, heart rate, and other vital signs; reward wearers for healthy activities and habits; and alert the wearer and others, such as doctors, emergency responders and family members when problems arise. “Wearable health technology brings three distinctly beneficial trends to the table – connected information, community, and gamification,” writes Vala Afshar on the Huffington Post. “By harnessing this trifecta, healthcare leaders have new ways to build engagement and create accurate, far-reaching views of both personal and population health.”

Wearables are both producers of data (collecting and transmitting wearers’ data) and consumers of data, receiving and displaying information about the wearer’s well-being and progress. Wearables are textbook generators of big data, with high velocity, volume and variety. And as in any big data scenario, transforming that data into insight and action requires a powerful, scalable analytics, data visualization and reporting platform.

Wearables in healthcare share many characteristics with the networks of sensors in Internet of Things (IoT) applications. But healthcare adds additional complexities and wrinkles, particularly regarding security. With IoT, everyone agrees that security is important, but the rules and standards vary and are subject to debate. However, when individuals’ personal health data is in the mix, more (and more complicated) laws, security regulations and privacy concerns kick in.

“A person’s health information is particularly sensitive,” writes Victoria Horderen in the Chronicle of Data Protection.  “[B]oth in a legal sense (because health information is categorized as sensitive under EU data protection law) but also in an obviously everyday sense – people feel that their health information (in most but not all circumstances) is private.” Horderen writes specifically about the EU Data Protection Regulation, but the points she makes apply globally. The takeaway, I think, is that a platform supporting a wearable initiative in healthcare requires a robust, proven security foundation.

Many Use Cases

With a flexible big data platform supporting wearables, many healthcare use cases arise. Most of these are possible with today’s technology, while others could be on the horizon using future generations of devices. Some use cases include:

  • A person under observation for heart disease can use a wearable to monitor his or her heart rate 24/7, not just while at the doctor’s office. The wearable enables collection of both historical and point-in-time data, and the platform enables in-depth analysis of the data.
  • Alerts presented on a smartwatch can provide customized encouragement for good behavior (such as walking or stair climbing) and positive lifestyle choices (such as getting enough sleep). Such uses are ripe for gamification; if the wearer walks a certain number of steps (customized for the individual) rewards are unlocked. People are more likely to embrace a wearable if it provides an element of fun and positive feedback.
  • Data from large numbers of wearers can be anonymized and aggregated to perform epidemiological studies. Data can be segmented by geography, activity level, and demographics if wearers choose to opt in.
  • A wearable paired with a GPS-enabled smartphone can transmit coordinates and pertinent data to first responders in case of an emergency and alert family members of the wearer’s status.
  • A surgeon wearing smart glasses can monitor patient vital signs and other medical equipment in real time during an operation without turning away from the patient.

Think Small, Think Big

As these use cases indicate, a platform for wearables in healthcare needs to operate on a micro level, sending customized, personalized alerts, recommendations and actions to individuals based on their own data. But a platform should also enable macro-level analysis of vast quantities of data to spot trends and identify correlations within large populations.

The ability to analyze data on a large scale not only holds promise for medical research, but it also improves the wearable’s value to the individual user: An intelligent platform with access to individual and aggregate data can, for example, tell the difference between an heart rate spike due to exercise – a good thing to be encouraged – and a cardiac episode requiring attention and intervention on a case-by-case basis, not just a pre-set threshold.

One last bit of good news for healthcare providers who want to embrace wearables: Doctors are more trusted than any other group with consumers’ personal data. According to research by Timothy Morey, Theo Forbath and Allison Schoop and published in the May 2015 issue of Harvard Business Review, 87 percent of consumers find primary care doctors “trustworthy” or “completely trustworthy” with their personal data. That percentage is greater than credit card companies (85 percent), e-commerce firms (80 percent), and consumer electronics firms (77 percent), and much higher than social media firms (56 percent). As wearable use grows, that healthy goodwill is worth building on.

Mark Gamble is Senior Director, OpenText Analytics Technical Marketing. Katharina Streater and Fred Sandsmark contributed to this post.

big data, big data applications, iot, wearables

Opinions expressed by DZone contributors are their own.

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