We are asking our members to share their data and their electronic health records.
To collect the data, to bring it together, is what ASCO will do.
A typical randomized clinical trial is set up with a specific question—generally an interventional question—and the design for a statistically accurate clinical trial to answer this question definitively.
When you look at big data, there is opportunity to take it from a different point of view, which is to let the data speak to us. What trends do we see that we do not understand but want to understand better?
One of the ways to make observational data more useful, more accurate, more reliable and trustworthy is to link datasets so that you can triangulate, fill in the gaps, and have a more complete understanding.
Dr Miller: Maybe also verify some of those data fields, because the SEER data are curated by humans.
The second is hypothesis generation—looking at the data without any preconceived notion.
One of the things we are finding in Cancer Lin Q and other data sources is that we need to work with both the EHR vendors and our physicians to do a better job, frankly, of documentation so that it is more clear and accurate.
We have all seen cutting and pasting; things like this really lead to the problem of not very good data. Besides working with our practices to get better-quality data into their records so that better data come up to Cancer Lin Q, we have been having discussions with SEER for over a year now about linking data.
Dr Miller: We have seen that some studies have used things like the Surveillance, Epidemiology, and End Results (SEER) database.
How does Cancer Lin Q compare to the SEER database?