ON-DEMAND WEBINAR SERIES

Precision or Illusion?

Solving the definition-chaos crisis in real-world evidence.

Clinical definitions for disease conditions and patient cohorts are inconsistent, unstandardized, and poorly understood — and that imprecision cascades into flawed data, flawed AI inputs, and flawed research conclusions. Navidence brings the validated phenotype definitions. PurpleLab® brings the claims data infrastructure to prove what they mean at scale.

The case for precision, in four parts.

Four fireside conversations, each built around a real ISPOR poster, walk through what happens when definitions vary, why it matters more than most teams realize, and what a more precise approach looks like in practice. Every episode runs about 15 minutes — long enough to make the case, short enough to watch between meetings.

Together, Navidence and PurpleLab are making the case for precision in real-world evidence, translating dense ISPOR research into something HEOR, commercial analytics, and medical affairs teams can actually act on.

Navidence

The semantic layer. Computable, operationalized clinical definitions — code lists and study criteria — with context on how they've been validated and used.

PurpleLab

The real-world data layer. Claims data that shows how many real patients fall under each definition, how much individual codes weigh, and how cohort demographics shift depending on the definition you choose.

The two voices behind every episode.

Scott DuVall, PhD

SVP, Real-World Evidence
PurpleLab

Formerly directed the VA's VINCI infrastructure and was a professor of biomedical informatics at the University of Utah, where he helped standardize national claims and EHR data to the OMOP common data model.

Aaron Kamauu, MD, MS, MPH

CEO & Co-Founder
Navidence

Previously led real-world data services at Parexel and founded Anolinx. A longtime voice in RWD/RWE study design, co-host of the Real-World Wednesday podcast and one of the architects behind Navidence's CODef standard.