title: Automated mapping of clinical terms into SNOMED-CT. An application to codify procedures in pathology.
abstract: Clinical terminologies are considered a key technology for capturing clinical data in a precise and standardized manner, which is critical to accurately exchange information among different applications, medical records and decision support systems. An important step to promote the real use of clinical terminologies, such as SNOMED-CT, is to facilitate the process of finding mappings between local terms of medical records and concepts of terminologies. In this paper, we propose a mapping tool to discover text-to-concept mappings in SNOMED-CT. Name-based techniques were combined with a query expansion system to generate alternative search terms, and with a strategy to analyze and take advantage of the semantic relationships of the SNOMED-CT concepts. The developed tool was evaluated and compared to the search services provided by two SNOMED-CT browsers. Our tool automatically mapped clinical terms from a Spanish glossary of procedures in pathology with 88.0% precision and 51.4% recall, providing a substantial improvement of recall (28% and 60%) over other publicly accessible mapping services. The improvements reached by the mapping tool are encouraging. Our results demonstrate the feasibility of accurately mapping clinical glossaries to SNOMED-CT concepts, by means a combination of structural, query expansion and named-based techniques. We have shown that SNOMED-CT is a great source of knowledge to infer synonyms for the medical domain. Results show that an automated query expansion system overcomes the challenge of vocabulary mismatch partially.
authors.affiliation: Department of Electronics and Computer Science Campus Vida, University of Santiago de Compostela, Santiago de Compostela, La Coruña, 15782, Spain, joseallones87@gmail.com.
authors.forename: J L
authors.initials: JL
authors.lastname: Allones
authors.forename: D
authors.initials: D
authors.lastname: Martinez
authors.forename: M
authors.initials: M
authors.lastname: Taboada
mesh_terms: D001331:Automation; D059019:Clinical Coding; D009317:National Library of Medicine (U.S.); D009323:Natural Language Processing; D010336:Pathology / Q000145:classification*; D058996:Quality Improvement; D013030:Spain; D039061:Systematized Nomenclature of Medicine; D014481:United States