With all the hype surrounding big data, pinning down its ideal usage is important for planning the development and expanding uses. What goal should the healthcare industry have in mind as it explores the possibilities for improved care and lowered costs that big data presents?

“People that talk about big data often talk about…creating an open source network that somehow aggregates all this data and we can get better outcomes,” Zach Landman, MD, and CMO at DoctorBase, told Healthcare IT News in a recent interview.

Landman went on to draw an analogy to Facebook.  He suggested that “more and more people over time could potentially be open to the idea of sharing their information for the greater good,” although he noted that it is unlikely that patients would agree to share their patient data in a public manner similar to how people share personal information on the popular social network.

Still, without even beginning to discuss—though in no way belittling—the serious privacy concerns such a health information network would raise, another issue obstructs current efforts to make the most of big data.  

[See also: Top 3 paths big data will blaze.]

Big data, true to its name, comprises massive amounts of data, but what sets it apart from traditional data warehouses is the variety of data sets from which analysts try to derive insights into how to better target care in the population to which the data refers.  

The issue, as Landman put it, is that “a single hospital oftentimes has a dozen or more systems within the network and those are constantly changing and vendors are constantly changing and typically are proprietary software.”  There is no guarantee that disparate data systems (EMR, lab results, prescriptions, ICU, to give examples of data that may be collected on different systems within a single hospital) will function together, even within the network of a single hospital. “That’s something that isn’t even ever discussed when people are talking about just creating a big data system for a hospital.”

Software companies make themselves more competitive in the current market by hoarding patient data and amassing proprietary data sets. While this makes sense from a business standpoint, this practice freezes data within companies that refuse to integrate with others. There is no economic incentive for companies to voluntarily open their proprietary data, but “without that,” said Landman, “I don’t know how much big data can truly accomplish.”  

[See also: Intermountain, Deloitte put data to work.]