Ambiguity in medical concept normalization: An analysis of types and coverage in electronic health record datasets

Denis Newman-Griffis, Guy Divita, Bart Desmet, Ayah Zirikly, Carolyn Penstein Rosé, Eric Fosler-Lussier

Abstract: Normalizing mentions of medical concepts to standardized vocabularies is a fundamental component of clinical text analysis. Ambiguity—words or phrases that may refer to different concepts—has been extensively researched as part of information extraction from biomedical literature, but less is known about the types and frequency of ambiguity in clinical text. This study characterizes the distribution and distinct types of ambiguity exhibited by benchmark clinical concept normalization datasets, in order to identify directions for advancing medical concept normalization research.