The 5 V's of big data - Watson Health Perspectives

With increasing volume and velocity comes increasing variety. This third “V” describes just what you’d think: the huge diversity of data types that healthcare organizations see every day. Again, think about electronic health records and those medical devices: Each one might collect a different kind of data, which in turn might be interpreted differently by different physicians—or made available to a specialist but not a primary care provider. The challenge for healthcare systems when it comes to data variety?

Last but not least, big data must have value. That is, if you’re going to invest in the infrastructure required to collect and interpret data on a system-wide scale, it’s important to ensure that the insights that are generated are based on accurate data and lead to measurable improvements at the end of the day.

As I pointed out to Mark and Margaret, every clinician and healthcare system is different, and so there’s no “cookie cutter” way to provide high-quality patient care. The same goes for how we handle big data:

The way care is provided to any given patient depends on all kinds of factors—and the way the care is delivered and more importantly the way the data is captured may vary from time to time or place to place. For example, what a clinician reads in the medical literature, where they trained, or the professional opinion of a colleague down the hall, or how a patient expresses herself during her initial exam all may play a role in what happens next. Such variability means data can only be meaningfully interpreted when care setting and delivery process is taken into context.