Public health entities are inevitably sitting on massive data sets. Growing archives of stored patient records, population reports, and lab results are thrusting data volume measures into the petabyte scale.

Agencies, on average, currently store data that could require more than “20 million four-drawer filing cabinets filled with text,” according to MeriTalk’s recent report, ‘The Big Data Gap.”

The copiousness of big data doesn’t need any clarification, but the significance of it does – as health entities work to implement EHRs, convert to ICD-10, and reach meaningful use, the importance of grappling with big data needs to be defined.

Amongst the growing projects issued to the public health sector, what are big data’s challenges and what are its benefits?

Here are our top five obstacles:

1. Health industry behind with big data
Chris Belmont (pictured at left), CIO and vice president of Ochsner Health Systems – a non-profit delivery system located in southeast Louisiana – pointed to a cultural reliance on paper as chief among the reasons health care is lagging other industries.

“We have a culture of being more retrospective and reactive: as in, ‘give me a report and I’ll act on it;’ that’s so 1990’s, and before… So I guess our culture still is, ‘give me a two-dimensional piece of paper with data on it, and I’ll find out things.’”

With some entities essentially addicted to paper, and others engaging with EMRs, fluency across the industry is interrupted, Belmont said.

[Related: Tapping big data for early indications of preventable conditions.]

Even though EHR-use has increased – from about 20 percent a few years ago, to nearly 60 percent today – but “it’s really still a paper-based system,” said Roger Foster, senior director of DRC’s high performance technologies group, which provides technology solutions to government programs.

Other industries, Foster explained, have maximized - or are working to maximize – the potential of stored data. He pointed to NOAA, which has been working to coordinate data across sites to outline weather trends and climate patterns.

2. Mobilizing data to reach across systems
Fluency doesn’t always extend across an organization itself; there’s often disparity between the compilation methods within an organization.

“There’s such a variation of how data is collected,” Foster said, “it’s hard to drive those methods to a meaningful outcome.”

Belmont and Foster agreed that harnessing big data can help reach that end. And Ochsner Health System can attest. The organization has been working to mobilize big data using a platform engineered by Informatica, a data integration company.

One of the main reasons for mobilizing their data, Belmont said, is Ochsner’s need for communication across internal systems. “We have a total of about 225 information systems that we support here at Ochsner. And all of these systems, more or less, keep their data in islands,” Belmont explained. “The real value is not necessarily reporting out of those individualized transactional systems, it’s the ability to aggregate and correlate that data horizontally across those organizations.”

[See also: With eye on public health, Delaware, Michigan roll out clouds.]

IBM’s global healthcare ambassador Lorraine Fernandes expanded on the differences in data forms, citing the growth of unstructured data as another reason public health organizations ought to mobilize – the sooner the better. IBM has been providing clients like Harvard Medical School and Wellpoint with big data analytics technology.

“With big data you have the ability to analyze that unstructured data,” Fernandes said, including reports from clinic equipment, telehealth devices, and home health monitors. “The reality is there’s a tremendous amount of data that is unstructured. There is a variety of data in healthcare, while you see that in all industries, it takes many different forms in healthcare.”

As Belmont echoed, reigning in big data will generate fluidity across a system’s varying data forms.

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