Toward Semantic Interoperability of Electronic Health Records
Idoia Berges, Jesús Bermúdez, Arantza Illarramendi
TL;DR
The paper tackles the challenge of semantic interoperability for heterogeneous electronic health records (EHRs) by proposing an ontology-based framework centered on a canonical ontology. It introduces two key modules, DB2OntoModule and MappingModule, to translate proprietary relational schemas and per-system ontologies into a shared semantic core, while employing path mappings and SWRL rules to align disparate structures on the fly. The approach enables cross-system interpretation and integration of diagnoses by connecting canonical and application ontologies through integration mappings, and demonstrates feasibility with an end-to-end HL7-related example. While offering extensibility to standard and proprietary models and reducing human intervention through reasoning, the work also identifies scalability and Terminology Manager dependencies as practical challenges for widespread deployment.
Abstract
Although the goal of achieving semantic interoperability of electronic health records (EHRs) is pursued by many researchers, it has not been accomplished yet. In this paper, we present a proposal that smoothes out the way toward the achievement of that goal. In particular, our study focuses on medical diagnoses statements. In summary, the main contributions of our ontology-based proposal are the following: first, it includes a canonical ontology whose EHR-related terms focus on semantic aspects. As a result, their descriptions are independent of languages and technology aspects used in different organizations to represent EHRs. Moreover, those terms are related to their corresponding codes in well-known medical terminologies. Second, it deals with modules that allow obtaining rich ontological representations of EHR information managed by proprietary models of health information systems. The features of one specific module are shown as reference. Third, it considers the necessary mapping axioms between ontological terms enhanced with so-called path mappings. This feature smoothes out structural differences between heterogeneous EHR representations, allowing proper alignment of information.