Big data? Real world data? What do we really mean?
I was at a conference a couple of weeks ago, an interesting two days spent discussing what is big data in the life science domain, and what value can we expect to gain from better access and use.
The key note speaker kicked off the first day with a great quote from Atul Butte: “Hiding within those mounds of data is knowledge that could change the life of a patient or change the world”.
This is a really great ambition for data analytics. But one interesting topic was, what do we mean by big data? One common definition from some of the Pharma folk was, that it was any sort of data that originated outside their organization that related to patient information.
To me, this definition seems to refer more to real world data – adverse event reports, electronic health records, voice of the customer (VoC) feeds, social media data, claims data, patient group blogs. Again, any data that hasn’t been influenced by the drug provider, and can give an external view – either from the patient, payer, or healthcare provider.
Many of these real world sources have free text fields, and this is where text analytics, and natural language processing (NLP), can fit in. We have customers who are using text analytics to get actionable insight from real world data – and finding valuable intelligence that can inform commercial business strategies.
Valuable information could be found in electronic health records, but these are notoriously hard to access for Pharma, with regulations and restrictions around data use, data privacy etc.
So, what real world data are accessible?