Conference Paper

Ontology Driven CPG Authoring and Execution via a Semantic Web Framework.

DOI: 10.1109/HICSS.2007.408 Conference: 40th Hawaii International International Conference on Systems Science (HICSS-40 2007), CD-ROM / Abstracts Proceedings, 3-6 January 2007, Waikoloa, Big Island, HI, USA
Source: DBLP


Clinical Practice Guidelines (CPG) are used by healthcare practitioners to standardize clinical practic e and to provide evidence mediated health-care. Currently, ther e have been considerable efforts to computerize CPG so as to operationalize them within Clinical Decision Support Systems (CDSS) and to deploy them at the point of care. In our work, we take a semantic web approach - employing a domain ontology, a patient ontology, decision rules and a rule execution engine - towards the computerization and execution of CPG for CDSS. We present an ontology-driven approach for computerizing CPG and executing them based on individual patient instances. In our work we extend the Guideline Element Model (GEM) for computerizing CPG. We have (i) defined a CPG ontology based on the Document Type Definition (DTD) of GEM for ontologically representing a GEM encoded CPG; (ii) developed CPG decision logic definition tool and defined CPG rule syntax that allows practitioners to abstract and define decision logic rules based on the CPGs decision-variables inherent within the CPG; (iii) developed a forward-chaining CPG execution engine that executes the set of CPG execution logic rules using the JENA reasoning system; and (iv) implemented an automated justification tree generation module that provides the inference trace for the solution in order to assist practitioners in understanding the rationa le for the proposed recommendations. In practice, given a patient instance our CDSS is able to derive CPG based clinical recommendations. We will present a working prototype of our CPG-based CDSS for the EU Radiation Protection 118 Referral Guideline for Imaging (RPG).

Download full-text


Available from: Sajjad Hussain
  • Source
    • "They provide solutions to problems of CDSS development relating to data integration, knowledge representation and reasoning [2]. Application examples of Semantic Web Technologies in CDS systems include among others, encoding of clinical practice guidelines [4] and disease management [5] [6] [7]. None of these systems handles temporal information and deal with evolution of a disease in time. "
    [Show abstract] [Hide abstract]
    ABSTRACT: In our study we present a design for a decision support system for patients suffering from Bipolar Disorder (BD). Bipolar Disorder is a recurrent and highly disabling psychiatric illness that evolves constantly in time and often leads to crucial incidents. We focus on Bipolar Depression and especially on a Breakthrough Depressive Episode scenario that occurs when a patient shows depressive symptoms during pharmaceutical treatment. Using Semantic Web Technologies we developed SybillaTUC, a prototype Clinical Decision Support System which combines the clinical guidelines for Bipolar Disorder with a patient's condition and his medical record. The system is able to predict the evolution of the disease for each patient, alerting the clinician on the possibility of a crucial incident suggesting optimal treatment.
    Full-text · Conference Paper · Jul 2014
  • Source
    • "As a result there have been different methods suggested to transform CPGs into a computer understandable format [16] [17] [18] [19] [20]. Such computerized CPGs are used with decision support systems to provide evidence-based assistance [15] [21]. It has been observed that healthcare practitioners, when using CPGs, tend to validate or to supplement their understanding of the CPGs [22] [23]. "
    [Show abstract] [Hide abstract]
    ABSTRACT: A framework has been developed that automatically generates context-specifi c query, and determines its query type, from computerized clinical practice guidelines (CPGs). The generated query can be submitted to PubMed using web services to retrieve and link relevant medical literature pertaining to the computerized CPGs content. This framework makes use of contexts, semantics, statistical information and meta-information of the medical phrases in the Extended-Knowledge Components of the computerized CPG content. The medical literature retrieved and linked, by our framework, is found to be relevant to the knowledge of the computerized CPG.
    Full-text · Article · Jan 2010
  • Source
    • "The quality of decisions at point of care is enhanced by evidence-based knowledge, which is contextually-relevant and semantically-related for the problem at hand. Clinical practice guidelines are regarded as a rich source of up-to-date knowledge of evidencebased best clinical practices [1] [2]. ,QHVVHQFH³&OLQLFDO-practice-guidelines (CPGs) are originally textual documents, usually structured as a set of clinical situations, for which evidence-EDVHGWKHUDSHXWLFUHFRPPHQGDWLRQVDUHSURYLGHG´>@7RPDNHEHWWHUXVHRI such CPG heterogeneous knowledge, it is necessary to computerize them and then incorporate them in a clinical decision support system (CDSS) [2]. "
    [Show abstract] [Hide abstract]
    ABSTRACT: Contextually sensitive and semantically related evidence-based knowledge play an important role in decision-making. Clinical practice guidelines (CPG) are being developed to provide a rich source of up-to-date knowledge of evidence-based best clinical practices. Such knowledge assists healthcare practitioner in specific clinical circumstances at their decision-points. In many studies, it was shown that the effectiveness of CPG could be improved with their computerization. In this paper, we present our CPG-knowledge computerization framework that has been developed and implemented along the lines of knowledge management approaches. This framework adds context, semantics and related meta-information to the CPGs knowledge content using an extended-knowledge component ontology and UMLS. It also transforms them into a set of structured 'extended-knowledge components'. These extended-knowledge components constitute a 'CPG knowledge base', which is used for providing assistance at point of care.
    Full-text · Article · Feb 2009 · Studies in health technology and informatics
Show more