Article ID: | iaor20165046 |
Volume: | 33 |
Issue: | 6 |
Start Page Number: | 531 |
End Page Number: | 547 |
Publication Date: | Dec 2016 |
Journal: | Expert Systems |
Authors: | Sonsilphong Suphachoke, Arch-int Ngamnij, Arch-int Somjit, Pattarapongsin Cherdpan |
Keywords: | artificial intelligence: expert systems |
The integration of data from various electronic health record (EHR) systems presents a critical conflict in the sharing and exchanging of patient information across a diverse group of health‐oriented organizations. Patient health records in each system are annotated with ontologies utilizing different health‐care standards, creating ontology conflicts both at the schema and data levels. In this study, we introduce the concept of semantic ontology mapping for the facilitation and interoperability of heterogeneous EHR systems. This approach proposes a means of detecting and resolving the data‐level conflicts that generally exist in the ontology mapping process. We have extended the semantic bridge ontology in support of ontology mapping at the data level and generated the required mapping rules to reconcile data from different ontological sources into a canonical format. As a result, linked‐patient data are generated and made available in a semantic query engine to facilitate user queries of patient data across heterogeneous EHR systems.