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Knowledge and Information Systems

, Volume 29, Issue 2, pp 405–418 | Cite as

Using OWL ontologies for adaptive patient information modelling and preoperative clinical decision support

  • Matt-Mouley Bouamrane
  • Alan Rector
  • Martin Hurrell
Regular Paper

Abstract

We here present our research and experience regarding the design and implementation of a knowledge-based preoperative assessment decision support system. We discuss generic design considerations as well as the practical system implementation. We developed the system using semantic web technology, including modular ontologies developed in the OWL web ontology language, the OWL Java application programming interface and an automated logic reasoner. We discuss how the system enables to tailor patient information collection according to personalized medical context. The use of ontologies at the core of the system’s architecture permits to efficiently manage a vast repository of preoperative assessment domain knowledge, including classification of surgical procedures, classification of morbidities and guidelines for routine preoperative tests. Logical inference on the domain knowledge according to individual patient’s medical context enables personalized patients’ reports consisting of a risk assessment and clinical recommendations such as relevant preoperative tests.

Keywords

Clinical decision support systems Preoperative assessment and screening Knowledge representation and reasoning 

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Copyright information

© Springer-Verlag London Limited 2010

Authors and Affiliations

  • Matt-Mouley Bouamrane
    • 1
  • Alan Rector
    • 2
  • Martin Hurrell
    • 3
  1. 1.Faculty of MedicineUniversity of GlasgowGlasgowScotland, UK
  2. 2.School of Computer ScienceManchester UniversityManchesterUK
  3. 3.CIS InformaticsGlasgowScotland, UK

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