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Views of diagnosis distribution in primary care in 2.5 million encounters in Stockholm: a comparison between ICD-10 and SNOMED CT
Karolinska Institutet, Huddinge. (Department of Neurobiology, Care Sciences and Society, Center for Family and Community Medicine)
Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.ORCID iD: 0000-0001-6468-2432
Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
Karolinska Institutet, Huddinge. (Department of Neurobiology, Care Sciences and Society, Center for Family and Community Medicine)
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2010 (English)In: Informatics in Primary Care, ISSN 1476-0320, E-ISSN 1475-9985, Vol. 18, no 1, 17-29 p.Article in journal (Refereed) Published
Abstract [en]

Background Primary care (PC) in Sweden provides ambulatory and home health care outside hospitals. Within the County Council of Stockholm coding of diagnoses in PC is mandatory and is done by general practitioners (GPs) using a Swedish primary care version of the International Statistical Classification of Diseases version 10 (ICD-10). ICD-10 has a mono-hierarchical structure. SNOMED CT is poly-hierarchical and belongs to a new generation of terminology systems with attributes (characteristics) that connect concepts in SNOMED CT and build relationships. Mapping terminologies and classifications has been pointed out as a way to attain additional advantages in describing and documenting healthcare data. A poly-hierarchical system supports the representation and aggregation of healthcare data on the basis of specific medical aspects and various levels of clinical detail. Objective To describe and compare diagnoses and health problems in KSH97-P/ICD-10 and SNOMED CT using primary care diagnostic data and to explore and exemplify complementary aggregations of diagnoses and health problems generated from a mapping to SNOMED CT. Methods We used diagnostic data collected throughout 2006 and coded in electronic patient records (EPRs) and a mapping from KSH97-P/ICD-10 to SNOMED CT to aggregate the diagnostic data with SNOMED CT defining hierarchical relationship Is a and selected attribute relationships. Results The chapter level comparison between ICD-10 and SNOMED CT showed minor differences except for infectious and digestive system disorders. The relationships chosen aggregated the diagnostic data to 2861 concepts showing a multidimensional view on different medical and specific levels and also including clinically relevant characteristics through attribute relationships. Conclusions SNOMED CT provides a different view of diagnoses and health problems on a chapter level and adds significant new views of the clinical data with aggregations generated from SNOMED CT Is a and attribute relationships. A broader use of SNOMED CT is therefore of importance when describing and developing primary care. © 2010 PHCSG, British Computer Society.

Place, publisher, year, edition, pages
The British Computer Society , 2010. Vol. 18, no 1, 17-29 p.
Keyword [en]
Classification; Diagnosis; ICD-10; Medical records systems computerised; Primary care; SNOMED CT
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:liu:diva-57019PubMedID: 20429975OAI: oai:DiVA.org:liu-57019DiVA: diva2:324045
Available from: 2010-06-14 Created: 2010-06-09 Last updated: 2017-12-12
In thesis
1. Enrichment of Terminology Systems for Use and Reuse in Medical Information Systems
Open this publication in new window or tab >>Enrichment of Terminology Systems for Use and Reuse in Medical Information Systems
2010 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Electronic health record systems (EHR) are used to store relevant heath facts about patients. The main use of the EHR is in the care of the patient, but an additional use is to reuse the EHR information to locate and evaluate clinical evidence for treatments. To efficiently use the EHR information it is essential to use appropriate methods for information compilations. This thesis deals with use of information in medical terminology systems and ontologies to be able to better use and reuse EHR information and other medical information.

The first objective of the thesis is to examine if word alignment on bilingual English-Swedish rubrics from five medical terminology systems can be used to build a bilingual dictionary. A study found that it was possible to generate a dictionary with 42 000 entries containing a high proportion of medical entries using word alignment. The method worked best using sets of rubrics with many unique words that are consistently translated. The dictionary can be used as a general medical dictionary, for use in semi-automatic translation methods, for use in cross-language information retrieval systems, and for enrichment of other terminology systems.

The second objective of the thesis is to explore how connections from existing terminology systems and information models to SNOMED CT and the structure in SNOMED CT can be used to reuse information. A study examined whether the primary health care diagnose terminology system KSH97-P can obtain a richer structure using category and chapter mappings from KSH97-P to SNOMED CT and the structure in SNOMED CT. The study showed that KSH97-P can be enriched with a poly-hierarchical chapter division and additional attributes. The richer structure was used to compile statistics in new manners that showed new views of the primary care diagnoses. A literature study evaluated which kinds of information compilations those are necessary to create graphical patient overviews based on information from EHRs. It was found that a third of the patient overviews can have their information needs satisfied using compilations based on SNOMED CT encodings of the information entities in the EHR and the structure in SNOMED CT. The other overviews also need access to individual values in the EHR. This can be achieved by using well-defined information models in the EHR.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2010. 79 p.
Series
Linköping Studies in Science and Technology. Dissertations, ISSN 0345-7524 ; 1335
National Category
Computer and Information Science
Identifiers
urn:nbn:se:liu:diva-58621 (URN)978-91-7393-328-5 (ISBN)
Public defence
2010-09-10, Eken, Campus US, Linköpings universitet, Linköping, 09:00 (English)
Opponent
Supervisors
Available from: 2010-08-30 Created: 2010-08-18 Last updated: 2015-09-22Bibliographically approved

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Nystrom, MikaelÅhlfeldt, Hans

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