Evaluation of alternative standardized terminologies for medical conditions within a network of observational healthcare databases.
Large electronic databases of health care information, such as administrative claims and electronic health records, are available and are being used in a number of public health settings, including drug safety surveillance. However, because of a lack of standardization, clinical terminologies may differ across databases. With the aid of existing resources and expert coders, we have developed mapping tables to convert ICD-9-CM diagnosis codes used in some existing databases to SNOMED-CT and MedDRA. In addition, previously developed definitions for specific health outcomes of interest were mapped to the same standardized vocabularies. We evaluated how vocabulary mapping affected (1) the retention of clinical data from two test databases, (2) the semantic space of outcome definitions, (3) the prevalence of each outcome in the test databases, and (4) the reliability of analytic methods designed to detect drug-outcome associations in the test databases. Although vocabulary mapping affected the semantic space of some outcome definitions, as well as the prevalence of some outcomes in the test databases, it had only minor effects on the analysis of drug-outcome associations. Furthermore, both SNOMED-CT and MedDRA were viable for use as standardized vocabularies in systems designed to perform active medical product surveillance using disparate sources of observational data.
Observational Medical Outcomes Partnership, Foundation for the National Institutes of Health, 9650 Rockville Pike, Bethesda, MD 20814, USA. reich@omop.org
Christian
C
Reich
Patrick B
PB
Ryan
Paul E
PE
Stang
Mitra
M
Rocca
D059019:Clinical Coding / Q000592:standards*; D016208:Databases, Factual; D057286:Electronic Health Records / Q000592:standards*; D006801:Humans; D012660:Semantics; D009626:Terminology as Topic; D018875:Vocabulary, Controlled