Why We Need To Mine Government's Big Data

Big Data Talent War: 10 Analytics Job Trends

U.S. government agencies and healthcare organizations are swimming in a sea of data, much of it underused. Making this information readily available to researchers, entrepreneurs, and consumers could lead to improvements in healthcare and other areas--but accomplishing this goal remains a challenge.

U.S. government-led efforts to free big data are underway. The Health Data Initiative, for instance, debuted in 2010 and is designed to encourage entrepreneurs to create new applications that use healthcare data.

Similarly, HealthData.gov is a site designed to make government healthcare data readily available to everyone. This "liberated" information from the U.S. Department of Health and Human Services includes data from a wide range of federal agencies, such as the Centers for Medicare and Medicaid Services (CMS), Centers for Disease Control and Prevention (CDC), and National Institutes of Health (NIH). The information includes databases of recent medical and scientific knowledge, consumer product and government spending data, and numerous other reports, according to the HealthData.gov site.

Tim Hays, health IT strategy executive for Dynamics Research Corporation (DRC), believes that a wider implementation of advanced big data analytics could help government health agencies do more targeted studies on specific diseases, detect fraud more easily, and broadly deploy data-driven clinical support systems that predict health risks.

[ Read Unlocking Big Government Data: Whose Job Is It?. ]

Hays has first-hand knowledge of these issues. Before joining DRC, a company that provides technology management services to government agencies, he helped a variety of organizations develop data analytics strategies. That time included nine years at the National Institutes of Health, where he carried out a variety of data analysis projects. Hays has a Ph.D. in neuroscience from UCLA.

Federal and state governments are beginning to see the value of their data warehouses, said Hays in a phone interview with InformationWeek. "A variety of different agencies have different types of data, both in large volumes and less than large volumes. There are agencies such as NIH, which has access to large amounts of research data internally," he said.

These departments are quickly learning that they need subject matter experts (SMEs), as well as the right analytical tools to mine their data correctly, said Hays. "Agencies are starting to say, 'OK, let's find a concrete question that we need answered, and then figure out if we have the data.'"

Healthcare is one area where these efforts are underway. For instance, large data repositories at government health agencies are useful for researching medical issues that span long periods of time. "In the commercial sector, it's very challenging to do these kinds of longitudinal studies, simply because people come in and out of healthcare plans," said Hays. "I know how many plans I've been on in just the last five years--United, Aetna, CareFirst, Blue Cross. People come in and out of these, and it's really hard to look at a single individual."

Healthcare is a major focus of many federally sponsored data-management efforts. For instance, the U.S. Food and Drug Administration's Janus project is a clinical trial data repository that would allow the FDA and the pharmaceutical industry to research past and present clinical trials. Named for the Roman god with two faces--one sees the past, the other the future--Janus is designed to help the FDA use data from past clinical trials to enable better trials in the future.

Analytics has a strong future in both government and commerce, but Hays warned that human involvement in data analysis remains critically important. Computers alone lack the sophistication to make informed decisions in many areas of research, including healthcare, without human oversight.

"Subject matter experts are going to continue to be valuable resources, alongside those who understand the analytics, tools, and the data," Hays said.

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