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Health Informatics Journal
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Topic maps for exploring nosological, lexical, semantic and HL7 structures for clinical data

Grace I. Paterson

Medical Informatics, Faculty of Medicine Dalhousie University 5849 University Avenue Halifax, NS, Canada B3H 4H7, grace.paterson{at}dal.ca

Andrew M. Grant

Collaborative Research for Effective Diagnostics Université de Sherbrooke Centre de développement des biotechnologies de Sherbrooke Parc Biomédical du CHUS Sherbrooke (Québec), Canada, J1E 4K8, andrew.grant{at}usherbrooke.ca

Steven D. Soroka

Steven D. Soroka Division of Nephrology, Faculty of Medicine Dalhousie University 1278 Tower Road Halifax, NS, Canada B3H 2Y9, steven.soroka{at}cdha.nshealth.ca

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 reified 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.

Key Words: boundary object • chronic kidney disease • classification systems • common ground • topic map

Health Informatics Journal, Vol. 14, No. 4, 267-278 (2008)
DOI: 10.1177/1460458208096556
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