Healthcare applications are complex in the way data and schemas are organised in their internal systems. Widely deployed healthcare standards like Health Level Seven (HL7) V2 are designed using flexible schemas which allow several choices when constructing clinical messages. The recently emerged HL7 V3 has a centrally consistent information model that controls terminologies and concepts shared by V3 applications. V3 information models are arranged in several layers (abstract to concrete layers). V2 and V3 systems raise interoperability challenges: firstly, how to exchange clinical messages between V2 and V3 applications, and secondly, how to integrate globally defined clinical concepts with locally constructed concepts. The use of ontologies for interoperable healthcare applications has been advocated by domain and knowledge representation specialists. This paper addresses two main areas of an ontology-based integration framework: (1) an ontology building methodology for the HL7 standard where ontologies are developed in separated global and local layers; and (2) aligning V2 and V3 ontologies. We propose solutions that: (1) provide a semi-automatic mechanism to build HL7 ontologies; (2) provide a semi-automatic mechanism to align HL7 ontologies and transform underlying clinical messages. The proposed methodology has developed HL7 ontologies of 300 concepts in average for each version. These ontologies and their alignments are deployed and evaluated under a semantically-enabled healthcare integration framework.