Article

Bridging the semantics gap between terminologies, ontologies, and information models.

Institute of Medical Biometry Medical Informatics, University Medical Center Freiburg, Germany.
Studies in health technology and informatics 01/2010; 160(Pt 2):1000-4.
Source: PubMed

ABSTRACT SNOMED CT and other biomedical vocabularies provide semantic identifiers for all kinds of linguistic expressions, many of which cannot be considered terms in a strict sense. We analyzed such "non-terms" in SNOMED CT and concluded that many of them cannot be interpreted as directly referring to objects or processes, but rather to information entities. Discussing two approaches to represent information entities, viz. the OBO Information artifact ontology (IAO) and the HL7 v3 Reference Information Model (RIM), we propose an integrative solution for representing information entities in SNOMED CT, in a way that is still compatible with RIM and the IAO and uses moderately enhanced description logics.

Full-text

Available from: Stefan Schulz, Jun 08, 2015
4 Followers
 · 
148 Views
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: The SIR-FMD project is a partnership between the Department of Genetics and Reference Centre for Rare Vascular Diseases at the Georges Pompidou European Hospital in Paris and the Medical Informatics and Knowledge Engineering Laboratory of Inserm. Its aim is to use an ontological approach to implement an information system for the French Fibromuscular Dysplasia Registry. The existing data was dispersed in numerous databases, which had been created independently. These databases have different structures and contain data of diverse quality. The project aims to provide generic solutions for the management of the communication of medical data. The secondary objective is to demonstrate the applicability of these generic solutions in the field of rare diseases (RD) in an operational context. The construction of the French FMD registry was a multistep process. A secure platform has been available since the beginning of November 2013. The medical records of 471 patients from the initial dataset provided by the HEGP-Paris, France have been included, and are accessible from a secure user account. Users are organized into a collaborative group, and can access patient groups. Each electronic patient record contains more than 2,200 items. The problem of semantic interoperability has become one of the major challenges for the development of applications requiring the sharing and reuse of data. The information system component of the SIR-FMD project has a direct impact on the standardisation of coding of rare diseases and thereby contributes to the development of e-Health.
    Studies in health technology and informatics 01/2015; 210:887-91.
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Realist ontologies organize knowledge by strict adherence to philosophical principles, ensuring robustness and coherence. According to those principles, only entities empirically verifiable can be represented. Our study aimed to analyze medical records to evaluate which kinds of entities should be represented for physicians. We classified the entities and found several entities that cannot be represented in realist ontologies. After due analysis, results suggest that a categorization that distinguishes reality from medical knowledge about reality and observations under both of them are useful to describe entities present in medical records.
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Numerous information models for electronic health records, such as openEHR archetypes are available. The quality of such clinical models is important to guarantee standardised semantics and to facilitate their interoperability. However, validation aspects are not regarded sufficiently yet. The objective of this report is to investigate the feasibility of archetype development and its community-based validation process, presuming that this review process is a practical way to ensure high-quality information models amending the formal reference model definitions.
    BMC Medical Informatics and Decision Making 08/2014; 14(1):64. DOI:10.1186/1472-6947-14-64 · 1.50 Impact Factor