title: Automated mapping of local radiology terms to LOINC.
abstract: We developed an automated tool, called the Intelligent Mapper (IM), to improve the efficiency and consistency of mapping local terms to LOINC. We evaluated IM's performance in mapping diagnostic radiology report terms from two hospitals to LOINC by comparing IM's term rankings to a manually established gold standard. Using a CPT-based restriction, for terms with a LOINC code match, IM ranked the correct LOINC code first in 90% of our development set terms, and in 87% of our test set terms. The CPT-based restriction significantly improved IM's ability to identify correct LOINC codes. We have made IM freely available, with the aim of reducing the effort required to integrate disparate systems and helping move us towards the goal of interoperable health information exchange.
authors.affiliation: Regenstrief Institute, Inc. and Indiana University School of Medicine, Indianapolis, IN, USA.
authors.forename: Daniel J
authors.initials: DJ
authors.lastname: Vreeman
authors.forename: Clement J
authors.initials: CJ
authors.lastname: McDonald
mesh_terms: D001185:Artificial Intelligence; D006801:Humans; D039703:Logical Observation Identifiers Names and Codes; D011871:Radiology / Q000145:classification*; D012984:Software; D018875:Vocabulary, Controlled