Big Data Analytics Brings Big Potential to Healthcare

By Asha Nayak, MD, Ph.D.

This week, I was thrilled to join Intel CEO Brian Krzanich on stage during his keynote at Oracle* Open World to describe the great potential of big data analytics in healthcare. I talked about the critical role of tools like the Trusted Analytics Platform (TAP) in accelerating medical discovery and impact for patients.

As a practicing clinician and Intel’s Global Medical Director, I am especially excited about the ability to monitor patients outside of the clinic using wearable, at-home, and mobile devices. In addition to their usefulness in monitoring, many of these devices are two-way — creating an avenue to reach individuals in real time with custom recommendations. This has very broad implications well beyond the examples around cardiovascular and Parkinson’s studies I cited in the keynote.

For outwardly healthy individuals, wearable and mobile can help clinicians detect a variety of conditions earlier. For example, today many people have intermittent atrial fibrillation that they learn of only after arriving at the hospital with their first stroke. Imagine if we could detect this silent and asymptomatic condition at home, in time to prompt a person to get early treatment and prevent that first stroke.

Another example is pre-ecclampsia1, which affects two percent to 18 percent of pregnancies, depending on where you are in the world. It is a progressive condition that threatens the lives of both mother and fetus. One of its first signs is rising blood pressure. Earlier detection and treatment are known to improve outcomes for both mother and child. These are two of many examples of how we can prevent suffering, improve outcomes, and potentially lower costs by detecting disease earlier.

It’s very important to note that monitoring devices must be accurate (especially in the hands of untrained users), and must be validated (in combination with their back-end analytics) for accuracy – in order to be effective in these types of applications.

For individuals with chronic disease, there is also great value in helping people tailor how they manage their unique symptoms and disease progression. Technology can help to guide a patient within the bounds of a physician’s prescription/instructions. For example, patients with asthma treat themselves with prescribed oral and inhaled medications when symptoms occur.

Imagine if - using biometric and environmental sensors, real-time analytics, and push-alerts — an asthma patient could be alerted to the risk or early-onset of a flare before symptoms begin. Early intervention has the potential to help patients avoid or reduce the severity of their flare and reduce the amount of medication needed to control it. This is an example of how we can better treat conditions that are already diagnosed.

My enthusiasm in this area is shared by many, across disciplines, and around the world. In addition to Intel, numerous academic, government and commercial organizations have recognized the value of integrating multiple health data streams, and are investing heavily in discovery from large population datasets. As you can see from this chart, these efforts, representing just a few that are underway today, are diverse both in focus and location:

Organization Target # of Participants Status
UK Biobank 500,000 Fully enrolled, dataset growing
Michael J Fox Foundation 1,000 (US & Europe) Actively enrolling
UCSF Health eHeart Study 1,000,000 (worldwide) Actively enrolling
Stanford & Duke Baseline Study 10,000 Pilot phase (2015), then expanding
Qatar SIDRA Medical & Research Center 350,000 Enrolling in 2016
Saudi Genome Project 100,000 Planning phase (2015)
US Precision Medicine Initiative 1,000,000 Planning phase (2015)

So to all the researchers out there, this is an amazing time to ask questions we never thought we could answer before. Think about associations between clinical parameters and pretty much anything we can measure today — from behavior to diet to location to genetic composition and more. Bigger and bigger datasets are being integrated. Tools like TAP are making it easier to query these complex information streams, including data generated outside the clinic, and to find answers that I believe will help us live healthier.

The entire keynote can be found here with the healthcare discussion beginning at 33:00.

Visit intel.com/healthcare to find out more about Intel’s efforts in Health and Life Sciences.

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