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Title

Automatic medical encoding with SNOMED categories

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Published in BioMed Central Medical Informatics and Decision Making. 2008, vol. 8 Suppl 1, p. S6
Abstract BACKGROUND: In this paper, we describe the design and preliminary evaluation of a new type of tools to speed up the encoding of episodes of care using the SNOMED CT terminology. METHODS: The proposed system can be used either as a search tool to browse the terminology or as a categorization tool to support automatic annotation of textual contents with SNOMED concepts. The general strategy is similar for both tools and is based on the fusion of two complementary retrieval strategies with thesaural resources. The first classification module uses a traditional vector-space retrieval engine which has been fine-tuned for the task, while the second classifier is based on regular variations of the term list. For evaluating the system, we use a sample of MEDLINE. SNOMED CT categories have been restricted to Medical Subject Headings (MeSH) using the SNOMED-MeSH mapping provided by the UMLS (version 2006). RESULTS: Consistent with previous investigations applied on biomedical terminologies, our results show that performances of the hybrid system are significantly improved as compared to each single module. For top returned concepts, a precision at high ranks (P0) of more than 80% is observed. In addition, a manual and qualitative evaluation on a dozen of MEDLINE abstracts suggests that SNOMED CT could represent an improvement compared to existing medical terminologies such as MeSH. CONCLUSION: Although the precision of the SNOMED categorizer seems sufficient to help professional encoders, it is concluded that clinical benchmarks as well as usability studies are needed to assess the impact of our SNOMED encoding method in real settings. AVAILABILITIES : The system is available for research purposes on: http://eagl.unige.ch/SNOCat.
Keywords AlgorithmsAutomationEfficiency, OrganizationalEpisode of CareForms and Records ControlMEDLINESystematized Nomenclature of Medicine
Stable URL https://archive-ouverte.unige.ch/unige:1267
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PMID: 19007443
Structures
Research groups Groupe Geissbuhler Antoine (informatique médicale) (222)
Interfaces Homme-machine en milieu clinique (610)

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Deposited on : 2009-03-31

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