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Two teams can size the same market using the exact same healthcare claims data and land millions of patients apart. The data is identical, but the cohort definition is not, and almost nobody checks the range. While real-world data can map treatment flows, disease progression, outcomes, and cost of care across payers, every insight rests on a definition that usually goes untested and may not even be published at all. In this episode, Scott L. DuVall, PhD, SVP of Real-World Evidence at PurpleLab, whose CARES initiative puts high-precision data and methods behind real-world research, explains which definitional choices move a result, what to ask before building on numbers you didn't produce, and the four requirements he would insist on for every study.






