Video
There are 2 main ways big data has helped to advance cancer care, but the lack of interoperability in the United States limits some of the data that can be analyzed for quality purposes, explained Bobby Green, MD, MSCE, senior vice president of clinical oncology at Flatiron Health.
There are 2 main ways big data has helped to advance cancer care, but the lack of interoperability in the United States limits some of the data that can be analyzed for quality purposes, explained Bobby Green, MD, MSCE, senior vice president of clinical oncology at Flatiron Health.
Transcript
How is big data advancing cancer care in a way that wasn't possible before?
So I would say there are 2 predominant ways that data is helping advance cancer care. The first is oncology clinics now are facing the need to report on a lot of quality metrics, and there’s a lot of burden involved in manually pulling the data. So one of the things that has really been imperative that data has helped us to do is to pull data from disparate points within electronic health records to help us auto-calculate some of the quality metrics, and really to reduce the burden on the practices for a lot of the logistical work that goes into it.
The second big area where we’re starting to see some benefit is in taking some of the claims data that has come to practices, whether it’s from CMS or from commercial payers, and using data analytics get insights into what is driving the cost of care. I think we’re very early in this area, but we have been able to see some practices taking those insights and actually thinking about how to make interventions in them to try to deliver higher value, lower cost care.
How do challenges around interoperability create a barrier to using big data in cancer care?
Interoperability is a big issue, because when you pull data points from different places to, for example, calculate quality metrics, right now in most places you are limited to being able to pull data just from the electronic health record (EHR), because it’s not easy or seamless to, for example, be able to pull a data point easily over from a hospital system, for example. And linking different data sets is critically important to be able to, for example, report on quality metrics, and we clearly aren’t there.
Interoperability is incredibly important and it helps to kind of fill in the picture. Whereas right now a lot of the times we’re stuck looking just at the EHR data.