Health Policy And Implementation Challenges To Achieving Big Data Outcomes

John Loonsk | Government Health IT | April 29, 2013

Big Data must be near the top of its hype cycle by now. As with other technologies, it may eventually deliver on a great deal of this hype, but the outcomes will probably arrive later than the current frenzy would suggest.

Part of the delay is that “new” technologies, like Big Data, are frequently restrained by “old” policies and the “old” approaches of existing technologies. It takes time, and sometimes policy and utilization changes, to fully accommodate a new technology’s potential. This two-part series of articles will point to key places in health policy and data use where current approaches may be impeding full Big Data outcomes.

Knowing big data when you see it
The term “Big Data” is being applied to many different things now, but exactly what is included is not always clear. One way that Big Data is defined is by the use of specific tools, such as the Hadoop framework, that are needed to practically deal with extremely large data stores. But while this is a convenient way to define things, it is also a somewhat circular definition. What is more, it does not really speak to the changes in approach and the differing utilization considerations that are involved in taking advantage of huge stores of data.