Managing clinical guidelines contextualization in the GLARE system

  • Authors:
  • Paolo Terenziani;Stefania Montani;Alessio Bottrighi;Mauro Torchio;Gianpaolo Molino;Gianluca Correndo

  • Affiliations:
  • Dipartimento di Informatica, Univ. Piemonte Orientale “A. Avogadro”, Alessandria, Italy;Dipartimento di Informatica, Univ. Piemonte Orientale “A. Avogadro”, Alessandria, Italy;Dipartimento di Informatica, Univ. Piemonte Orientale “A. Avogadro”, Alessandria, Italy;Laboratorio di Informatica Clinica, Torino, Italy;Laboratorio di Informatica Clinica, Torino, Italy;Dipartimento di Informatica, Universita' di Torino, Torino, Italy

  • Venue:
  • AI*IA'05 Proceedings of the 9th conference on Advances in Artificial Intelligence
  • Year:
  • 2005

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Abstract

Computer-based tools to manage clinical guidelines are gaining an increasing relevance within the areas of Artificial Intelligence (AI) in Medicine and Medical Informatics. One of the most relevant obstacles to the application, use and dissemination of clinical guidelines is the gap between the generality of guidelines (as defined, e.g., by physicians' committees) and the peculiarities of the specific contexts of application. First, computer-based guideline managers must be integrated with the Hospital Information System (HIS), and usually different DBMS are adopted by different hospitals. Second, general guidelines do not take into account the fact that the tools needed for laboratory and instrumental investigations might be unavailable at a given hospital. Finally, a sort of “continuous adaptation” has to be supported, to manage the updates needed to cope with new clinical procedures. GLARE is a guideline manager which adopts advanced AI techniques to address the above contextualization issues.