title: Automating identification of adverse events related to abnormal lab results using standard vocabularies.
abstract: Laboratory data need to be imported automatically into central Clinical Study Data Management Systems (CSDMSs), and abnormal laboratory data need to be linked to clinically related adverse events. This import of laboratory data can be automated through mapping to standard vocabularies with HL7/LOINC mapping to the metadata within a CSDMS. We have designed a system that uses the UMLS metathesaurus as a common source to map or link abnormal laboratory values to adverse event CTCAE coded terms and grades in the metadata of TrialDB, a generic CSDMS.
authors.affiliation: Yale University School Of Medicine, USA.
authors.forename: C A
authors.initials: CA
authors.lastname: Brandt
authors.forename: C C
authors.initials: CC
authors.lastname: Lu
authors.forename: P M
authors.initials: PM
authors.lastname: Nadkarni
mesh_terms: D002984:Clinical Laboratory Information Systems; D019411:Clinical Laboratory Techniques / Q000009:adverse effects*; D003628:Database Management Systems; D006801:Humans; D039703:Logical Observation Identifiers Names and Codes; D017432:Unified Medical Language System; D018875:Vocabulary, Controlled