Big Data Life Savers

March 17, 2017 Greg Stack

With almost two billion smart phones worldwide, and over 15 percent of Americans owning wearables such as Fitbits, the collection of health and lifestyle data has never been easier. But with this tsunami of data flowing in from so many sources, how can clinicians ensure they’re capitalizing on its benefits and not drowning in it?

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The gamification of health and wellbeing has many consumers monitoring everything from how many steps they take in a day to their heart rates and even sleeping patterns—and that’s just the start. The amount of data being recorded by smart devices is exponentially increasing and will play an important role in almost all stages of the healthcare cycle.

In fact, smart devices—and the data they collect—are already acting as lifesavers. This week, a Fitbit user noticed her fitness tracker was reporting that her heart was beating 150 times per minute, 50 beats faster than her normal resting heart rate. She immediately visited a doctor and was quickly diagnosed with an atrial fibrillation, a type of abnormal heart rhythm that can potentially lead to stroke.

On the surface, it’s easy to see the benefits of a clinician being able to access this new health data—especially with individuals and a small data set. However, it’s not nearly as simple when managing large numbers of patients generating oceans of data. Healthcare organizations are already strapped for resources, and with all this new, non-traditional data starting to be paired with traditional data—such as electronic medical records (EMR)—it may seem overwhelming.

This is where big data platforms come in.

Acting like buckets, these platforms collect relevant data, filter out the irrelevant, and present it to the clinician in a meaningful way, as Jerry Hart, Orion Health product lead for data and analytics, explains.

“(Orion Health’s Amadeus platform) is focused on getting all the relevant data together, making it available to the clinician at the point of care, and then using that to assist clinicians who need to make sense of an ever-increasing amount of data about an individual. This includes not only a meaningfully curated presentation of the data, but also gaining insights using machine learning functionality.

“This means more than just understanding trends in a population and identifying key metrics around utilization and quality measurement: It’s all about how we can enable those on the front line to be more proactive around certain elements of the population and change those metrics." 

These platforms can buoy a clinician’s decision-making process, further assisting them in efficient and accurate diagnosis and helping them to navigate through the waves of data—both big and small. They allow clinicians to take advantage of the transformation of healthcare and avoid being swamped by the new streams of data. 

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Learn why healthcare organizations need a big data platform. Download the ebook now!

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