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What big data means for health data analytics, in practical terms

An Intel executive explains what big data means for health care, as well as what the chip vendor is doing to improve quality and clinical research through health data analytics.

"Big data," the latest IT and informatics catchphrase, describes the gathering and analysis of the structured and unstructured data a business creates. In healthcare, discussions around big data most frequently apply to quantifying clinical data to develop quality improvement programs as well as research for new treatments.

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The concept, pardon the pun, seems bigger than that. Once accountable care organizations, health information exchanges and the Centers for Medicare and Medicaid Services (CMS) gather quality data on a national scale, how will they use health data analytics to accomplish what looks like the opposing goals of slashing costs while improving patient outcomes?

At the Health Information and Management Systems Society's HIMSS 2012 conference, sat down with Intel Corp. health IT director Rick Cnossen to get the big-picture perspective on health data analytics and how it might eventually affect the health care CIO's daily work life.

SearchHealthIT: What does big data, a fairly vague umbrella term, mean when specifically applied to health data analytics?

Cnossen: It certainly has been the topic of a lot of discussion recently. At Intel we get together once a year with CEOs from some of the bigger technology companies. We look to the future three to five years [and discuss] what trends they see and how can we help them with those trends with technology. [Last year] we identified a few things, and big data was certainly one of those.

One of the things that is going to be driving big data, moving forward, is what we call "the Internet of things." By 2015, the prediction is that there's going to be 15 billion different connected devices just spewing data. That data has to be collected somewhere. That's going to drive some of the big data storage.

Another phenomenon coming up is cloud computing. If you look at the amount of computing that's going to be required for the intelligent systems, by 2015, it's 20 times the compute power [we have presently]. That needs to be done in a way that's smart in terms of collecting our data, processing our data and cloud computing for virtualization. By putting this cloud computing infrastructure in place you also give way to a lot easier access for the data, worldwide.

A specific health care example in a project called caBIG -- at least 25 different countries in the world [are] collecting cancer data. What were the symptoms of the patients, what were the demographics of the patients, what treatment did they do, what treatments were effective and what wasn't effective? Whatever your age, whatever your background, whatever disease you may or may not have -- people like you who have had this kind of cancer, [you can see] what worked and what didn't work.

There's a lot of opportunity [for health data analytics]. As we start collecting data, there's all kind of usages.

Rick Cnossen, health IT director, Intel

How are people going to innovate, and how are people going to roll with these trends? In health care, specifically, [three] things are going to drive that.

These will drive a significant about of big data that's going to be out there.

This sounds like something that will drive CIOs to react differently, depending on the size of their organization. The bigger they are, the more involved in these initiatives they will be.

I think we're going more toward a virtualized, cloud-based system, even if you're a [smaller] company. As private clouds become more and more secure and people become more comfortable moving in that direction, I think it's going to become more normal that data resides outside your boundaries -- where there's a flexible, nimble, highly available, secure environment that you don't have to worry about…[and where] someone else can do it in a more cost-effective way.

There's a lot of opportunity [for health data analytics]. As we start collecting data, there's all kind of usages. Imagine collecting voice data in assisted-living facilities -- we could tell there's some cognitive decline in the beginning of Alzheimer's. For example, someone might have more pauses between words that you can measure, or the amount that they say "ah" and "um." If you start collecting that, [you can] say, "This patient is starting to have cognitive decline, let's intervene and start providing a higher quality of care." Or even gait analysis…for Parkinson's patients. What if we were able to take preventive action for some of these diseases just by collecting data and mining it?

Intel's a chip maker. What do you guys care about big data?

[Laughs] I think we're the third-largest employer of software engineers in the world now, with the acquisition of McAfee Inc. and Wind River Systems Inc. We're much more than a chip company. We're also a solutions and software provider company.

As you look at big data, data centers are going to have to expand rapidly. The data center includes server…infrastructure, networking and…storage. We're a big part of the storage solutions out there. In order to store this data effectively and efficiently, there's a lot more processing that has to take place right now. Encryption, deduplication, identifying common patterns in the storage and compressing it…it's a lot more server-intensive up front.

That's why Intel is involved in the cloud build-out, big data, and the Internet of things.

Let us know what you think about the story; email Don Fluckinger, Features Writer or contact @DonFluckinger on Twitter.

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