Topic maps for exploring nosological, lexical, semantic and HL7 structures for clinical data.
A topic map is implemented for learning about clinical data associated with a hospital stay for patients diagnosed with chronic kidney disease, diabetes and hypertension. The question posed is: how might a topic map help bridge perspectival differences among communities of practice and help make commensurable the different classifications they use? The knowledge layer of the topic map was generated from existing ontological relationships in nosological, lexical, semantic and HL7 boundary objects. Discharge summaries, patient charts and clinical data warehouse entries rectified the clinical knowledge used in practice. These clinical data were normalized to HL7 Clinical Document Architecture (CDA) markup standard and stored in the Clinical Document Repository. Each CDA entry was given a subject identifier and linked with the topic map. The ability of topic maps to function as the infostructure ;glue' is assessed using dimensions of semantic interoperability and commensurability.
Paterson
Grace I
GI
Dalhousie University, Halifax, NS, Canada B3H 4H7. grace.paterson@dal.ca
Grant
Andrew M
AM
Soroka
Steven D
SD
D003195:Computer Communication Networks / Q000592:standards; D048909:Diabetes Complications; D006302:Health Services Research; D006801:Humans; D006973:Hypertension / Q000150:complications; D007676:Kidney Failure, Chronic / Q000209:etiology; D008498:Medical Record Linkage / Q000592:standards; D016347:Medical Records Systems, Computerized / Q000145:classification / Q000592:standards*; D011381:Programming Languages; D012660:Semantics; D009626:Terminology as Topic