Using SNOMED CT to Group Adverse Drug Reactions
Author Information
Author(s): Iulian Alecu, Cedric Bousquet, Marie-Christine Jaulent
Primary Institution: Université Paris Descartes, Faculté de Médecine; Inserm, U729; SPIM, Paris, France
Hypothesis
Can WHO-ART terms be classified into semantic categories using SNOMED CT?
Conclusion
SNOMED CT's structure can automate the grouping of WHO-ART terms, improving the retrieval of related adverse drug reactions.
Supporting Evidence
- 85.9% of WHO-ART terms were successfully mapped to SNOMED CT synonyms.
- The new method improved groupings, achieving 87% coverage of the Haemorrhage SSC.
- Previous methods failed to match any WHO-ART terms in the Haemorrhage SSC.
Takeaway
This study shows that we can use a special medical dictionary to better organize and find information about drug reactions.
Methodology
The study proposes a new method that integrates associative relationships from SNOMED CT to improve the grouping of WHO-ART terms.
Limitations
The method's effectiveness is limited by the existing structure of WHO-ART and the availability of relevant SNOMED CT terms.
Digital Object Identifier (DOI)
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