Semantic patient information aggregation and medicinal decision support

  • Authors:

  • Pieterjan De Potter;Hans Cools;Kristof Depraetere;Giovanni Mels;Pedro Debevere;Jos De Roo;Csaba Huszka;Dirk Colaert;Erik Mannens;Rik Van De Walle

  • Affiliations:

  • Department of Electronics and Information Systems - Multimedia Lab, Ghent University - IBBT, Gaston Crommenlaan 8 Bus 201, B-9050 Ledeberg-Ghent, Belgium;Advanced Clinical Applications Research Group, Agfa HealthCare, Moutstraat 100, B-9000 Ghent, Belgium;Advanced Clinical Applications Research Group, Agfa HealthCare, Moutstraat 100, B-9000 Ghent, Belgium;Advanced Clinical Applications Research Group, Agfa HealthCare, Moutstraat 100, B-9000 Ghent, Belgium;Department of Electronics and Information Systems - Multimedia Lab, Ghent University - IBBT, Gaston Crommenlaan 8 Bus 201, B-9050 Ledeberg-Ghent, Belgium;Advanced Clinical Applications Research Group, Agfa HealthCare, Moutstraat 100, B-9000 Ghent, Belgium;Advanced Clinical Applications Research Group, Agfa HealthCare, Moutstraat 100, B-9000 Ghent, Belgium;Advanced Clinical Applications Research Group, Agfa HealthCare, Moutstraat 100, B-9000 Ghent, Belgium;Department of Electronics and Information Systems - Multimedia Lab, Ghent University - IBBT, Gaston Crommenlaan 8 Bus 201, B-9050 Ledeberg-Ghent, Belgium;Department of Electronics and Information Systems - Multimedia Lab, Ghent University - IBBT, Gaston Crommenlaan 8 Bus 201, B-9050 Ledeberg-Ghent, Belgium

  • Venue:
  • Computer Methods and Programs in Biomedicine
  • Year:
  • 2012

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Abstract

Although the health care sector has already been subjected to a major computerization effort, this effort is often limited to the implementation of standalone systems which do not communicate with each other. Interoperability problems limit health care applications from achieving their full potential. In this paper, we propose the use of Semantic Web technologies to solve interoperability problems between data providers. Through the development of unifying health care ontologies, data from multiple health care providers can be aggregated, which can then be used as input for a decision support system. This way, more data is taken into account than a single health care provider possesses in his local setting. The feasibility of our approach is demonstrated by the creation of an end-to-end proof of concept, focusing on Belgian health care providers and medicinal decision support.