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Visualization of disease distribution with SNOMED CT and ICD-10
Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.ORCID iD: 0000-0001-6468-2432
Department of Neurobiology, Care Sciences and Society, Center for Family and Community Medicine, Karolinska Institutet.
Department of Neurobiology, Care Sciences and Society, Center for Family and Community Medicine, Karolinska Institutet.
Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
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2010 (English)In: MEDINFO 2010 - Proceedings of the 13th World Congress on Medical Informatics / [ed] Safran, Charles; Reti, Shane; Marin, Heimar, Amsterdam: IOS Press, 2010, Vol. 160, 1100-1103 p.Conference paper, Published paper (Refereed)
Abstract [en]

Methods for presentation of disease and health problem distribution in a health care environment rely among other things on the inherent structure of the controlled terminology used for coding. In the present study, this aspect is explored with a focus on ICD-10 and SNOMED CT. The distribution of 2,5 million diagnostic codes from primary health care in the Stockholm region is presented and analyzed through the “lenses” of ICD-10 and SNOMED CT. The patient encounters, originally coded with a reduced set of ICD-10 codes used in primary health care in Sweden, were mapped to SNOMED CT concepts through a mapping table. The method used for utilizing the richer structure of SNOMED CT as compared to ICD-10 is presented, together with examples of produced disease distributions. Implications of the proposed method for enriching a traditional classification such as ICD-10 through mappings to SNOMED CT are discussed.

Place, publisher, year, edition, pages
Amsterdam: IOS Press, 2010. Vol. 160, 1100-1103 p.
Series
Studies in Health Technology and Informatics, ISSN 0926-9630, E-ISSN 1879-8365 ; 160
Keyword [en]
Visualization, Disease distribution, Health problems, ICD-10, SNOMED CT, Terminology models
National Category
Computer and Information Science Public Health, Global Health, Social Medicine and Epidemiology
Identifiers
URN: urn:nbn:se:liu:diva-60128DOI: 10.3233/978-1-60750-588-4-1100PubMedID: 20841854ISBN: 978-1-60750-587-7 (print)OAI: oai:DiVA.org:liu-60128DiVA: diva2:355241
Conference
13th International Congress on Medical Informatics (MEDINFO 2010), 12-15 September 2010, Cape Town, South Africa
Available from: 2010-10-06 Created: 2010-10-06 Last updated: 2017-02-09Bibliographically approved

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Nyström, MikaelÖrman, HåkanÅhlfeldt, Hans

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