Having recently spoken at about a half dozen conferences on the subject of big data in government and healthcare I’ve come to the conclusion that we’re focusing, at least in healthcare, on the wrong topic. When we’re dealing with individual patients, and even population health across multiple patients, the size and velocity of the data (“big data”) isn’t anywhere near as important as “actionable data” or “useful data” – by focusing on, and frankly scaring people with, the term “big data” we’re undermining the potential immediate utility of all kinds of “small data”.

I’ve made suggestions to conference organizers to consider moving their terminology from “big data” to ‘practical data’, ‘actionable data’, or ‘useful data’, especially in the healthcare sector where a lot of the data that we have these days is not actionable yet.

Giving the amount of imaging, natural language, retrospective documentation, and other data we have in healthcare it would seem we could immediately start using “big data” tools but that’s not quite the case.

If you’re a conference organizer, I’d love to see the following topics / tracks covered soon:

  • Big Data vs. Actionable/Practical/Useful Data – which data doesn’t matter in healthcare and shouldn’t be areas of focus? Sometimes answering a negative is easier than a positive.
  • Practical statistics — Given Nate Silver’s spectacular success in predicting the Presidential election, what can healthcare learn from his practical statistics techniques?
  • Understanding data sources – where does the data come from? Without knowing data providence and sources we’re going to have a lot of trouble with analysis.
  • Understanding data integration – how do you integrate data from various sources such that they are actionable / practical / useful?
  • Understanding data governance – ownership and liquidity of data is a big question and deserves enormous attention. This is not a solved problem and needs research.
  • Tools and technology – this is pretty well covered in non-healthcare settings but time series data in healthcare has some nuances that need attention.
  • Human Capital and Hiring – how do you hire, train, and prepare data scientists, engineers, analysts, etc. to take advantage of the coming data deluge?
  • Case studies – bring in companies / people that have done something useful and ready to share repeatable capabilities. In most conferences we hear about how big data is going to be great but very little actual usage and experience in the form of case studies.

What else would you like to see from ‘big data in healthcare’ conferences?