Fracking healthcare big data: Drilling for value or just hot gas?

Flames? Coming out of the water faucets? Fire coming out of any plumbing egress cannot be a good thing. I don’t know if you’ve seen the videos of this, but fracking, a convergence of deregulation and new technology, opens unprofitable mining areas and has the nasty polluting side effect of forcing flammable gas into water faucets.

A slang term for hydraulic fracturing, fracking creates fractures in rock formations by injecting fluid into cracks to force them further open and allow more oil and gas to flow out for extraction. In other words, fracking flushes value out of mines previously difficult to process and get value from with traditional methods and tools.

A frack-tured analogy to big data? Hold on ... big data is a collection of data sets so large and complex that it becomes difficult to process using traditional database management tools or data processing applications. Consider that just weeks ago IBM CEO Virginia Rometty stated that “data is the new natural resource,” and my analogy is not quite as tortured as you may think. 

The big data definition above lacks important elements found in Gartner’s:  "high volume, velocity and/or variety information assets that demand cost-effective, innovative forms of information processing that enable enhanced insight, decision-making, and process automation." (From Gartner Group’s “Big Data’s Trends and Opportunities.”) Long winded, yes, but it teases out several important points: data volume, velocity and variety, and for cost effective decision making insight.  It’s not just big data, but big analytics for big benefits.

Show me the value or else it's all hot gas.

What about big data and healthcare? No one who has visited a doctor’s office doubts the opportunity. A report earlier this year from McKinsey states the U.S. healthcare sector could create more than $300 billion in value every year if it were to “use big data creatively and effectively to drive efficiency and quality.” Sounds like hype, however, cut it in half - $150 billion – and it is still worth paying attention to.

A branch of healthcare informatics, healthcare’s big data sources could include patient data, clinical trial data, social network discussions, doctors’ notes and Internet-connected monitoring equipment. Recent healthcare reforms like the move towards Electronic Health Records (EHRs), Meaningful Use and Health Information Exchanges (HIE) will drive the standardization, aggregation and increasing value of data forward.

Data pollution is a big problem here, though. The simple term ‘standardization of data’ hides layers of complexities that are not unlike rock formations. From data entry to secondary uses and aggregation, issues with interpretation, corruption and translation abound. 

Consider the data lifecycle for a moment. For example, data is created in the doctor’s office.  How?  Frequently it is dictated and transcribed (accurately?) into an unstructured, non-standard report. To use our mining analogy, it is a sloppy, amorphous and moving data slurry. How can you aggregate and mine that for value?

Medical billing coders can misinterpret and miscode. 

Vendors allow non-standard data entry within their own systems ( know who you are...), and do not easily allow integration with other systems or content providers. 

Clinical data is corrupted as it is translated across standards, regional and national registers and Health Information Exchanges.

Add to this the rush to and crush of moving to Meaningful Use, and big data become a big problem fast.

So yes, if you are in healthcare IT, you should be paying attention to healthcare big data within the context of big analytics and big benefits. 

However, beware the jargonauts: vendors aggressively connecting whatever they sell as an answer to a (not ‘the’) big data question. Seeking to solve the tactical problem of their own product and services sales, they are not above flushing a little gas of their own around this currently over-hyped term.

Healthcare organizations, on the other hand, seek to solve the strategic issue of extracting the information’s value within their ecosystem. 

Getting to the value for healthcare writ large (practitioner, organization, industry, patient and populous) is more than a move from legacy systems (see HIT legacy systems: Outrunning the Zombie Apocalypse) to a new shiny technology or two. Given the tactical tangle of changing technologies, standards, terminology sets and accelerating governmental reforms, a more strategic view – an information strategy – is crucial. If your big data is a big mess, how do you mine it?

The IBM CEO is right: data should be thought of as a natural resource. Plan your information strategy now, if you haven’t already, or you may burn up a lot of resources without the results you need.   

More in the next post.

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