Abstract
To facilitate experts to find relevant clinical information models, we took a case study of openEHR. We proposed to use a graphical model to represent EHR archetype sets, aiming to optimize clincal information retrieval performance. In this study, we applied our graphic model to 523 OpenEHR archetypes and represented them as a graph with 5,008 nodes and 6,908 edges, which consists of 3,982 term nodes, 504 concept nodes, and 523 archetype nodes. On basis of the graphical model, it improved the performance for retrieving the clinical queries.
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