Journal of Medical Systems

, 38:134 | Cite as

Automated Mapping of Clinical Terms into SNOMED-CT. An Application to Codify Procedures in Pathology

Systems-Level Quality Improvement
First Online:
Received:
Accepted:
Part of the following topical collections:
  1. Systems-Level Quality Improvement

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.

Keywords

SNOMED CT Mapping Ontology matching Query expansion Information retrieval Clinical terminology 
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Notes

Acknowledgements

The work presented in this paper has been developed in the funded National Project OntoNeuroPhen (FIS2012-PI12/00373) by the Instituto de Salud Carlos III.

Supplementary material

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Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  1. 1.Department of Electronics and Computer Science Campus VidaUniversity of Santiago de CompostelaSantiago de CompostelaSpain
  2. 2.Department of Applied Physics Campus VidaUniversity of Santiago de CompostelaSantiago de CompostelaSpain

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