Medical knowledge management for specific hospital departments

  • Authors:

  • Jose M. Juarez;Tamara Riestra;Manuel Campos;Antonio Morales;Jose Palma;Roque Marin

  • Affiliations:

  • Dept. of Information and Communication Engineering, University of Murcia, Facultad de Informatica, Campus de Espinardo, 30100 Murcia, Spain;Dept. of Information and Communication Engineering, University of Murcia, Facultad de Informatica, Campus de Espinardo, 30100 Murcia, Spain;Dept. of Information and Communication Engineering, University of Murcia, Facultad de Informatica, Campus de Espinardo, 30100 Murcia, Spain;Dept. of Information and Communication Engineering, University of Murcia, Facultad de Informatica, Campus de Espinardo, 30100 Murcia, Spain;Dept. of Information and Communication Engineering, University of Murcia, Facultad de Informatica, Campus de Espinardo, 30100 Murcia, Spain;Dept. of Information and Communication Engineering, University of Murcia, Facultad de Informatica, Campus de Espinardo, 30100 Murcia, Spain

  • Venue:
  • Expert Systems with Applications: An International Journal
  • Year:
  • 2009

Quantified Score

Hi-index 12.05

Visualization

Abstract

Medical knowledge representation and management is concerned with how to organise the often vague clinical experience of medical staff required for computable models. However, few knowledge management and acquisition tools have entered routine use, since such tools are not perceived by physicians as part of the clinical information process. An attempt to partially solve this problem, we identify two key aspects of knowledge representation and management tasks. The first is to adopt a medical knowledge standardisation to provide a consistent terminology control and to simplify the integration between knowledge management tools and the health information system. The second is to establish an effective knowledge acquisition process in specific medical fields by adapting knowledge acquisition tools. Therefore, the main goal of this work is to define computational models and to design mechanisms for the effective acquisition and management of medical knowledge in real-life hospital departments. To this end, we analyse the representation of medical knowledge (based on deep-causal models) and the development of knowledge management tools (based on ontologies), integrated within the information processing activities of the clinical user. Finally, we illustrate its applicability in the Intensive Care Unit and Pediatry scenarios.