Early diagnosis of persons with von Willebrand disease using a machine learning algorithm and real-world data.

Background: Von Willebrand disease (VWD) is underdiagnosed, often delaying treatment. VWD claims coding is limited and includes no severity qualifiers; improved identification methods for VWD are needed. The aim of this study is to identify and characterize undiagnosed symptomatic persons with VWD in the US from medical insurance claims using predictive machine learning (ML) models.