Big Data is essential to improving health care outcomes according to EMC

Big data is going through a transformation, and health care IT will be a major beneficiary of its analytics capabilities, according to Dave Dimond, chief strategist for industry solutions at EMC, a major provider of cloud computing, data backup and big data infrastructure. Mr Dimond is convinced that the health care industry can use big data analytics to better detect diseases and aid medical research.

Speaking to Enterprise IT Technology website, eWeek, he stated:

“There’s a fair amount of hype in big data in general. In health care it’s coming together. Although the concept of big data may not have been as well-understood a year ago, rather than just being aligned with research, it’s getting more focused. Our position on health care is that big data is real.”

In fact, EMC has predicted a threefold increase in health care data between the beginning of 2013 and the beginning of 2016. The amount of health care data will eventually reach 15 zettabytes worth of information. One zettabyte being equal to roughly 15 million iPads of data, according to Mr Dimond. A zettabyte is equal to 1,000 exabytes; and one exabyte is the equivalent of 1 million terabytes.

As the U.S. health care industry shifts from pay for service—or pay per pill—to Medicare incentives for outcomes under the Affordable Care Act, big data analytics will play a role in helping doctors predict outcomes for patients they’re responsible for monitoring and treating. Predictive analytics can also help a doctor to determine whether a patient is more likely to need to be readmitted into hospital. Big data will allow hospital systems to centralise information from their multiple facilities. Mr Dimond believes this will enable the health organizations to monitor and keep track of data for a large patient population more effectively and monitor health outcomes better:

“To win in this business model [of accountable care] and thrive, they need to be able to do analytics,” said Dimond. “They need to be able to access data.”

Many health organizations may already have access to some big data applications, but they haven’t been in the position to pull all the data together effectively, largely because these data applications are all in incompatible, unstructured formats, according to Mr Dimond. Though a minority of healthcare providers are using big data technology well, the majority will need further help and encouragement to get the best of their enterprise data warehousing he believes.

Advanced big data analytics will also bring additional benefits in the future according to the EMC executive. When researchers can analyse entire human genomes, they will be able to compare populations of individuals. Then scientists will examine analytics models to see how data from electronic health records correlates with the genome data to help determine the cause of various illnesses. Analytic models will also enable medical researchers to evaluate whether certain treatments will prove to be effective. Analytics applications will also enable health care organizations to analyse financial data and billing:

“The data scientist can look at accumulating all the data possible from a number of sources—clinical systems, financial systems, outside providers, skilled nursing homes and putting it together in a way where you can look at it as a sandbox point of view.”

Analytics software such as EMC’s Greenplum Chorus can help by pulling disparate health care data all into one place. Chorus is a collaborative data science platform that allows for file sharing, versioning, change-tracking and archiving.  The Greenplum analytics platform also incorporates Hadoop, and the open-source software framework will enable health organizations to reduce unstructured data and associate it with structured data, according to Mr Dimond.

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