Resolving heterogeneities between data and processes paves the way for interoperability between different heterogeneous systems. Healthcare standards provide the base for interoperability between different Electronic Health Record (EHR) system. The problems related to data interoperability arise when two EHR system's are complaint to heterogeneous healthcare standards and want to communicate with each other. To achieve semantic data interoperability, there is need to resolve data level heterogeneity. In this paper, we propose system that enable high level of accuracy of mapping between heterogeneous healthcare standards model. The broader goal of data interoperability is achieved when these heterogeneities are resolved through ontology matching and generation of accurate mapping file, that helps in clinical message conversion from one standard to another. To justify claim we investigate HL7 and openEHR standards ontological mappings. We will discuss transformation of HL7 and openEHR models at high level and instance transformation at the realization level. The proposed approach provides accurate mappings that enables timely health information sharing among different healthcare systems to provide better healthcare to patients.

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