Using Ontologies for an Intelligent Patient Modelling, Adaptation and Management System

  • Matt-Mouley Bouamrane
  • Alan Rector
  • Martin Hurrell
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5332)


Health Information Management Systems (HIMS) face considerable technical and organisational barriers before successful deployment in hospitals. In addition, many existing systems have significant limitations, including: lack of flexibility and adaptability to complex requirements and processes and a general lack of “intelligence”. They offer basic patient management functionalities but do not go far beyond core functionalities. Due to their rigid architectures, these systems are hard to maintain and update. Recent advances in knowledge representation, including ontologies, can offer powerful and appealing solution to these problems. In this paper, we describe our current work on using ontologies for adapted information collection and patient representation. We describe the iterative transformation of a basic risk assessment software into a “knowledge-aware” system. We argue that using ontologies is both conceptually appealing and a pragmatic solution to implementing a shift from simple management systems to intelligent systems in healthcare. In turn, we believe such systems will efficiently support clinicians in their daily activities and will result in improved delivery of tailored patient care.


Iterative Step Computerize Physician Order Entry Risk Assessment System Health Information Management System Patient Medical History 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Matt-Mouley Bouamrane
    • 1
    • 2
  • Alan Rector
    • 1
  • Martin Hurrell
    • 2
  1. 1.School of Computer ScienceManchester UniversityUK
  2. 2.CIS InformaticsGlasgowUK

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