Journal of Medical Systems

, 38:75 | Cite as

Integration of an OWL-DL Knowledge Base with an EHR Prototype and Providing Customized Information

  • Xia JingEmail author
  • Stephen Kay
  • Tom Marley
  • Nicholas R. Hardiker
Systems-Level Quality Improvement
Part of the following topical collections:
  1. Systems-Level Quality Improvement


When clinicians use electronic health record (EHR) systems, their ability to obtain general knowledge is often an important contribution to their ability to make more informed decisions. In this paper we describe a method by which an external, formal representation of clinical and molecular genetic knowledge can be integrated into an EHR such that customized knowledge can be delivered to clinicians in a context-appropriate manner.

Web Ontology Language-Description Logic (OWL-DL) is a formal knowledge representation language that is widely used for creating, organizing and managing biomedical knowledge through the use of explicit definitions, consistent structure and a computer-processable format, particularly in biomedical fields. In this paper we describe: 1) integration of an OWL-DL knowledge base with a standards-based EHR prototype, 2) presentation of customized information from the knowledge base via the EHR interface, and 3) lessons learned via the process. The integration was achieved through a combination of manual and automatic methods. Our method has advantages for scaling up to and maintaining knowledge bases of any size, with the goal of assisting clinicians and other EHR users in making better informed health care decisions.


Electronic health record (EHR) applications Knowledge bases Web ontology language (OWL) Ontology application Intelligent systems Knowledge base integration 



This work was supported by the Overseas Research Students Awards Scheme (UK), University of Salford in the UK, and partially through intramural research funds from the National Library of Medicine and the Clinical Center of the National Institutes of Health in the USA. The authors thank Dr. James J Cimino, Yongsheng Gao for very constructive discussions and suggestions, Dr. Judith Effken for helpful comments and suggestions. The authors thank Ms. Cindy Clark, NIH Library Writing Center, for manuscript editing assistance and Ms. Jennifer White for English editing.


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Copyright information

© Springer Science+Business Media New York (outside the USA) 2014

Authors and Affiliations

  • Xia Jing
    • 1
    • 5
    Email author
  • Stephen Kay
    • 2
  • Tom Marley
    • 3
  • Nicholas R. Hardiker
    • 4
  1. 1.Laboratory for Informatics Development, NIH Clinical Center and National Library of Medicine, National Institutes of HealthBethesdaUSA
  2. 2.School of Health, Sport & Rehabilitation SciencesUniversity of SalfordSalfordUK
  3. 3.Independent ConsultantSalfordUK
  4. 4.School of Nursing, Midwifery & Social WorkUniversity of SalfordSalfordUK
  5. 5.Grover W357 Department of Social & Public Health College of Health Sciences & ProfessionsOhio UniversityAthensUSA

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