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Data Needs for Patient Overviews: A Literature ReviewCompared with SNOMED CT and openEHR
Linköpings universitet, Institutionen för medicinsk teknik, Medicinsk informatik.ORCID-id: 0000-0001-6468-2432
Linköpings universitet, Institutionen för medicinsk teknik, Medicinsk informatik.
(Engelska)Manuskript (preprint) (Övrigt vetenskapligt)
Abstract [en]

Patient overviews automatically generated fromelectronic healthcare data have different data needsdepending on their complexity. A literature reviewbased on a broad MEDLINE search found 16 suchoverviews for which the data needs were analyzedand compared with features provided bySNOMED CT and openEHR. Five systems used onlyinformation type, while five systems also presentedparticular values from its information entities. Sixsystems also aggregated or filtered the information.In addition to that, two systems provided referenceranges and three systems provided more advanceddecision support. The simple data needs can be metusing information entity markups based onSNOMED CT and SNOMED CT relationships. Morecomplex data needs can be satisfied using theopenEHR reference model and archetypes tostructure data and the archetype query language toretrieve individual data values. The most advancedoverviews also need additional methods foraggregation, filtering and connection to knowledgerepresentation.

Nationell ämneskategori
Medicin och hälsovetenskap Data- och informationsvetenskap
Identifikatorer
URN: urn:nbn:se:liu:diva-58615OAI: oai:DiVA.org:liu-58615DiVA, id: diva2:344278
Tillgänglig från: 2010-08-18 Skapad: 2010-08-18 Senast uppdaterad: 2018-01-12
Ingår i avhandling
1. Enrichment of Terminology Systems for Use and Reuse in Medical Information Systems
Öppna denna publikation i ny flik eller fönster >>Enrichment of Terminology Systems for Use and Reuse in Medical Information Systems
2010 (Engelska)Doktorsavhandling, sammanläggning (Övrigt vetenskapligt)
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.

Ort, förlag, år, upplaga, sidor
Linköping: Linköping University Electronic Press, 2010. s. 79
Serie
Linköping Studies in Science and Technology. Dissertations, ISSN 0345-7524 ; 1335
Nationell ämneskategori
Data- och informationsvetenskap
Identifikatorer
urn:nbn:se:liu:diva-58621 (URN)978-91-7393-328-5 (ISBN)
Disputation
2010-09-10, Eken, Campus US, Linköpings universitet, Linköping, 09:00 (Engelska)
Opponent
Handledare
Tillgänglig från: 2010-08-30 Skapad: 2010-08-18 Senast uppdaterad: 2020-02-19Bibliografiskt granskad

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Nyström, MikaelSundvall, ErikÖrman, HåkanÅhlfeldt, Hans

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