Dr Lou Garrison Discusses Challenges of Working With Real-World Data

Working with real-world evidence-based data can pose difficulties, both when collecting and analyzing the information, but redesigned incentives could help drive entities to provide more information, said Lou Garrison, PhD, professor emeritus in the Department of Pharmacy, University of Washington.

Transcript (slightly modified)
What are the challenges of working with real-world evidence-based data? Do the benefits outweigh the negatives?
The big issue, as the report brings out, is the potential for bias. You don’t have the advantage that you do in a randomized clinical trial to sort of limit the amount of bias, so we have methodological techniques to address that that are not perfect, but we can still learn from real-world data.
At the same time, you can’t apply those techniques unless you have the data, so sadly the infrastructure that we have in America as a fragmented, complicated healthcare system means interoperability across systems is limited, so that’s a real challenge. The infrastructure standards and so on are a big challenge too, developing the data we need to follow how medicines and other things are used over time, but the other big issue is, you could say we’ve had this need for 10 years, why haven’t we seen more?
I think it has to do with economics, with incentives to produce the information. Any given entity that’s competing with other entities, so pharmaceutical manufacturers have a limited incentive to produce the data in some instances, and payers have a limited incentive, because other people can then free ride on their information, so we have incentive problems. We need to somehow find ways to encourage people and reward people who do provide the information.
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