Ontology-driven execution of clinical guidelines

  • Authors:

  • David Isern;David SáNchez;Antonio Moreno

  • Affiliations:

  • Universitat Rovira i Virgili, Departament d'Enginyeria Informítica i Matemítiques, Intelligent Technologies for Advanced Knowledge Acquisition (ITAKA) Research Group, Tarragona, Cataloni ...;Universitat Rovira i Virgili, Departament d'Enginyeria Informítica i Matemítiques, Intelligent Technologies for Advanced Knowledge Acquisition (ITAKA) Research Group, Tarragona, Cataloni ...;Universitat Rovira i Virgili, Departament d'Enginyeria Informítica i Matemítiques, Intelligent Technologies for Advanced Knowledge Acquisition (ITAKA) Research Group, Tarragona, Cataloni ...

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

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Abstract

Clinical guidelines (CG) contain general descriptions, defined by health care organisations, of the way in which a particular pathology should be treated. Their adoption in daily care offers several benefits to both patients and practitioners, such as the standardisation of the delivered care and the reduction of errors, but, at the same time, there are several issues that limit their application. CGs are designed to cover a disease taking into account the available evidence but are not designed to be deployed in a particular hospital or healthcare institution. CGs include general recommendations that should be translated according the particular settings before adoption in daily care. This adoption should also specify accountable information about the responsible actors of performing actions in healthcare teams in order to avoid errors arising during delegation/assignment of tasks. In addition, this enactment is not performed taking into account a central knowledge base or a single actor. This paper proposes the combination of a multi-agent system modelling complex healthcare organisations and knowledge representation techniques in order to build a general framework for enabling the enactment of CGs in the context of a medical centre. As a main contribution, the ontological paradigm and the expressiveness of modern ontology languages are used to design, implement and exploit a medico-organisational ontology aimed to provide the semantics required to support the execution of clinical guidelines. The knowledge-driven guideline enactment is managed by a multi-agent system modelling in a distributed fashion the clinical entities involved in the care delivery.