Modeling Contextual Knowledge for Clinical Decision Support.

In theory, the logic of decision rules should be atomic. In practice, this is not always possible; initially simple logic statements tend to be overloaded with additional conditions restricting the scope of such rules. By doing so, the original logic soon becomes encumbered with contextual knowledge. Contextual knowledge is re-usable on its own and could be modeled separately from the logic of a rule without losing the intended functionality. We model constraints to explicitly define the context where knowledge of decision rules is actionable. We borrowed concepts from Semantic Web, Complex Adaptive Systems, and Contextual Reasoning. The proposed approach provides the means for identifying and modeling contextual knowledge in a simple, sound manner. The methodology presented herein facilitates rule authoring, fosters consistency in rules implementation and maintenance; facilitates developing authoritative knowledge repositories to promote quality, safety and efficacy of healthcare; and paves the road for future work in knowledge discovery.