I’m excited to be attending this year’s Healthcare Information and Management Systems Society (HIMSS) Annual Conference where the intersection of healthcare and IT will be more prevalent than ever before. Big Data, of course, will play a prominent role this year.
What Makes Healthcare Data Big
In many industries there’s a good understanding about the value of Big Data. In healthcare, this is still nascent. With credible consultancies like McKinsey citing the annual potential value of Healthcare Big Data being around $300 billion, it’s time for healthcare executives to take notice. One popular definition of Big Data is based on three Vs: variety of data, velocity of data, and volume. The three Vs, when combined in the setting of problem solving and prediction, create complexity. So, when we talk about refining complexity, it’s usually hand in hand with a discussion about the skills needed to make sense of Big Data and the burgeoning Data Science profession. Note that EMC has developed a Healthcare Analytics Appliance for customers who want to develop the capabilities needed to aggregate, analyze, and visualize complex data. Now, I’ll go through the Vs as they relate to the healthcare industry, so let’s dig in.
Variety of Healthcare Data
For hospital executives who have recently had $19 billion of stimulus-based incentives dropped in their laps to digitize their systems with Electronic Medical Records (EMRs), Big Data is about variety. In addition to the bounty of EMR data, which creates a longitudinal view of the patient, an average hospital has more than 100 additional applications which generate many silos of data. There is much value to be gleaned from all of these categories of data, however, unless all of the data are in the same format, that value becomes extremely difficult to discover.
Volume of Healthcare Data
The clear leader on the volume side of health data is medical imaging. In a recent report from Frost & Sullivan, the projected the amount of images being archived annually is forecasted to be in excess of one exabyte by 2016. What really makes this interesting is a trend towards perpetual archiving to generate a rich payload of metadata which is embedded in the images. When you combine this metadata with the unstructured data in other systems, you enable a number of high value use cases. Much of the work in this area has grown out of the Center for Evidence Based Imaging (CEBI), which EMC sponsors at Brigham and Women’s Hospital in Boston.
Velocity of Healthcare Data
When you walk the halls of many hospitals, you might notice small plastic tags on patients, gurneys, medical equipment and even staff or physicians. These tags, which are based on the next generation of Radio-Frequency Identification (RFID) technology, provide continuous tracking to streamline patient flow, enable better patient experience, lower supply inventories and reduce theft. This cloud-based technology, called Real Time Locations Systems (RTLS), has been in the works for several years and is rapidly coming of age with a ROI that basically pays for itself within months. The data streams in real time and provides actionable intelligence to the front lines of medicine.
Big Data Delivers Big Value for Healthcare
So what really makes healthcare data ‘big’? It’s the value derived from it, using advanced analytical techniques which provide fact-based answers to questions ranging from which therapeutic approaches work best and which patients are at highest risk for readmission or infection, to physician performance in relation to quality and cost.
For healthcare, Big Data is really big! Consider this the gold rush and stake your claim early so you can generate actionable insights to thrive and compete.
