Deciding on things is a knowledge-based activity. In the context of clinical decision support systems (DSS) this means that representation and management of the related knowledge about underlying concepts and processes is foundational for the decision-making process. A basic challenge to be mastered is the language problem. For expressing and sharing knowledge, we have to agree on terminologies specific for each of the considered domains. For guaranteeing semantic consistency, the concepts, their relation and underlying rules must be defined, deploying domain-specific as well as high-level ontologies. Ontology representation types range from glossaries and data dictionaries through thesauri and taxonomies, meta-data and data models up to formal ontologies, the latter represented by frames, formal languages and different types of logics. Based on the aforementioned principles, special knowledge representation and sharing languages relevant for health have been introduced. Examples are PROforma, Asbru, EON, Arden Syntax, GELLO, GLIF, Archetypes, HL7 Clinical Statements, and the recently developed FHIR approach. With increasing complexity and flexibility of decision challenges, DSS design has to follow a defined methodology, offered by the Generic Component Model Framework meanwhile internationally standardized. This paper deals in detail with the basics and instances for knowledge representation and management for DSS design and implementation, thereby referencing related work of the author.

eHealth Competence Center Bavaria Deggendorf Institute of Technology Germany

Medical Faculty University of Regensburg Germany

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