Establishing semantic interoperability in the course of clinical document exchange using international standard for metadata registry

Around the world electronic health records data are being shared and exchanged between two different systems for direct patient care, as well as for research, reimbursement, quality assurance, epidemiology, public health, and policy development. It is important to communicate the semantic meaning of the clinical data when exchanging electronic health records data. In order to achieve semantic interoperability of clinical data, it is important not only to specify clinical entries and documents and the structure of data in electronic health records, but also to use clinical terminology to describe clinical data. There are three types of clinical terminology: interface terminology to support a user-friendly structured data entry; reference terminology to store, retrieve, and analyze clinical data; and classification to aggregate clinical data for secondary use. In order to use electronic health records data in an efficient way, healthcare providers first need to record clinical content using a systematic and controlled interface terminology, then clinical content needs to be stored with reference terminology in a clinical data repository or data warehouse, and finally, the clinical content can be converted into a classification for reimbursement and statistical reporting. For electronic health records data collected at the point of care to be used for secondary purposes, it is necessary to map reference terminology with interface terminology and classification. It is necessary to adopt clinical terminology in electronic health records systems to ensure a high level of semantic interoperability.

Design of an Integration System for Bioinformatics Data Sources Using a Global MDR / 대한의료정보학회지

OBJECTIVES: Nowadays, as the amounts of biological data are rapidly increasing, bioinformatics has become one of the important research issues. The bioinformatics data sources are, however, distributed and heterogeneous, and therefore, often poorly integrated and difficult to use together. As many bioinformatics analyses need to make use of multiple information sources, the problem of integration of bioinformatics data sources has become an important one. The purpose of this paper is to present an integration system for bioinformatics data sources. METHODS: To solve this problem, we present an integration system for bioinformatics data sources using a global MDR, which provides users with efficiency and convenience as if they use one system. We deal with the extraction of data elements for bioinformatics MDRs by using ISO 11179 mandatory attributes. RESULTS: A global bioinformatics MDR schema for given MDRs and the results of query processing are presented. CONCLUSIONS: The proposed system and concepts in this paper may be a good solution for the integration of diverse bioinformatics data sources.