title: Achieving clinical statement interoperability using R-MIM and archetype-based semantic transformations.
abstract: Effective use of electronic healthcare records (EHRs) has the potential to positively influence both the quality and the cost of health care. Consequently, sharing patient's EHRs is becoming a global priority in the healthcare information technology domain. This paper addresses the interoperability of EHR structure and content. It describes how two different EHR standards derived from the same reference information model (RIM) can be mapped to each other by using archetypes, refined message information model (R-MIM) derivations, and semantic tools. It is also demonstrated that well-defined R-MIM derivation rules help tracing the class properties back to their origins when the R-MIMs of two EHR standards are derived from the same RIM. Using well-defined rules also enable finding equivalences in the properties of the source and target EHRs. Yet an R-MIM still defines the concepts at the generic level. Archetypes (or templates), on the other hand, constrain an R-MIM to domain-specific concepts, and hence, provide finer granularity semantics. Therefore, while mapping clinical statements between EHRs, we also make use of the archetype semantics. Derivation statements are inferred from the Web Ontology Language definitions of the RIM, the R-MIMs, and the archetypes. Finally, we show how to transform Health Level Seven clinical statement instances to EHRcom clinical statement instances and vice versa by using the generated mapping definitions.
authors: Department of Computer Engineering, Middle East Technical University, 06531 Ankara, Turkey.
authors: Ozgur
authors: O
authors: Kilic
authors: Asuman
authors: A
authors: Dogac
mesh_terms: D000465:Algorithms; D008498:Medical Record Linkage / Q000379:methods*; D016347:Medical Records Systems, Computerized; D008962:Models, Theoretical; D012660:Semantics; D018511:Systems Integration; D018875:Vocabulary, Controlled