Modeling Patient Safety Incidents Knowledge with the Categorial Structure Method
Identifieur interne : 000362 ( Pmc/Corpus ); précédent : 000361; suivant : 000363Modeling Patient Safety Incidents Knowledge with the Categorial Structure Method
Auteurs : Julien Souvignet ; Cédric Bousquet ; Pierre Lewalle ; Béatrice Trombert-Paviot ; Jean Marie RodriguesSource :
- AMIA Annual Symposium Proceedings [ 1942-597X ] ; 2011.
Abstract
Following the WHO initiative named World Alliance for Patient Safety (PS) launched in 2004 a conceptual framework developed by PS national reporting experts has summarized the knowledge available. As a second step, the Department of Public Health of the University of Saint Etienne team elaborated a Categorial Structure (a semi formal structure not related to an upper level ontology) identifying the elements of the semantic structure underpinning the broad concepts contained in the framework for patient safety. This knowledge engineering method has been developed to enable modeling patient safety information as a prerequisite for subsequent full ontology development. The present article describes the semantic dissection of the concepts, the elicitation of the ontology requirements and the domain constraints of the conceptual framework. This ontology includes 134 concepts and 25 distinct relations and will serve as basis for an Information Model for Patient Safety.
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PubMed: 22195191
PubMed Central: 3243289
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Paviot, Beatrice" sort="Trombert Paviot, Beatrice" uniqKey="Trombert Paviot B" first="Béatrice" last="Trombert-Paviot">Béatrice Trombert-Paviot</name><affiliation><nlm:aff id="af1-1300_amia_2011_proc"> INSERM U872, Eq. 20, Paris, France</nlm:aff></affiliation><affiliation><nlm:aff id="af2-1300_amia_2011_proc"> University of Saint Etienne, Department of Public Health and Medical Informatics, Saint-Etienne, France</nlm:aff></affiliation></author><author><name sortKey="Rodrigues, Jean Marie" sort="Rodrigues, Jean Marie" uniqKey="Rodrigues J" first="Jean Marie" last="Rodrigues">Jean Marie Rodrigues</name><affiliation><nlm:aff id="af1-1300_amia_2011_proc"> INSERM U872, Eq. 20, Paris, France</nlm:aff></affiliation><affiliation><nlm:aff id="af2-1300_amia_2011_proc"> University of Saint Etienne, Department of Public Health and Medical Informatics, Saint-Etienne, France</nlm:aff></affiliation><affiliation><nlm:aff id="af3-1300_amia_2011_proc"> WHO FIC Collaborative Centre for International Classifications in French Language, Paris, France</nlm:aff></affiliation></author></analytic><series><title level="j">AMIA Annual Symposium Proceedings</title><idno type="eISSN">1942-597X</idno><imprint><date when="2011">2011</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p>Following the WHO initiative named World Alliance for Patient Safety (PS) launched in 2004 a conceptual framework developed by PS national reporting experts has summarized the knowledge available. As a second step, the Department of Public Health of the University of Saint Etienne team elaborated a Categorial Structure (a semi formal structure not related to an upper level ontology) identifying the elements of the semantic structure underpinning the broad concepts contained in the framework for patient safety. This knowledge engineering method has been developed to enable modeling patient safety information as a prerequisite for subsequent full ontology development. The present article describes the semantic dissection of the concepts, the elicitation of the ontology requirements and the domain constraints of the conceptual framework. This ontology includes 134 concepts and 25 distinct relations and will serve as basis for an Information Model for Patient Safety.</p></div></front></TEI><pmc article-type="research-article"><pmc-comment>The publisher of this article does not allow downloading of the full text in XML form.</pmc-comment>
<front><journal-meta><journal-id journal-id-type="nlm-ta">AMIA Annu Symp Proc</journal-id><journal-title-group><journal-title>AMIA Annual Symposium Proceedings</journal-title></journal-title-group><issn pub-type="epub">1942-597X</issn><publisher><publisher-name>American Medical Informatics Association</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="pmid">22195191</article-id><article-id pub-id-type="pmc">3243289</article-id><article-id pub-id-type="publisher-id">1300_amia_2011_proc</article-id><article-categories><subj-group subj-group-type="heading"><subject>Articles</subject></subj-group></article-categories><title-group><article-title>Modeling Patient Safety Incidents Knowledge with the Categorial Structure Method</article-title></title-group><contrib-group><contrib contrib-type="author"><name><surname>Souvignet</surname><given-names>Julien</given-names></name><degrees>MS</degrees><xref ref-type="aff" rid="af1-1300_amia_2011_proc"><sup>1</sup></xref></contrib><contrib contrib-type="author"><name><surname>Bousquet</surname><given-names>Cédric</given-names></name><degrees>PharmD, PhD</degrees><xref ref-type="aff" rid="af1-1300_amia_2011_proc"><sup>1</sup></xref><xref ref-type="aff" rid="af2-1300_amia_2011_proc"><sup>2</sup></xref></contrib><contrib contrib-type="author"><name><surname>Lewalle</surname><given-names>Pierre</given-names></name><degrees>MA</degrees><xref ref-type="aff" rid="af2-1300_amia_2011_proc"><sup>2</sup></xref></contrib><contrib contrib-type="author"><name><surname>Trombert-Paviot</surname><given-names>Béatrice</given-names></name><degrees>MD, PhD</degrees><xref ref-type="aff" rid="af1-1300_amia_2011_proc"><sup>1</sup></xref><xref ref-type="aff" rid="af2-1300_amia_2011_proc"><sup>2</sup></xref></contrib><contrib contrib-type="author"><name><surname>Rodrigues</surname><given-names>Jean Marie</given-names></name><degrees>MD, PhD</degrees><xref ref-type="aff" rid="af1-1300_amia_2011_proc"><sup>1</sup></xref><xref ref-type="aff" rid="af2-1300_amia_2011_proc"><sup>2</sup></xref><xref ref-type="aff" rid="af3-1300_amia_2011_proc"><sup>3</sup></xref></contrib></contrib-group><aff id="af1-1300_amia_2011_proc"><label>1</label> INSERM U872, Eq. 20, Paris, France</aff><aff id="af2-1300_amia_2011_proc"><label>2</label> University of Saint Etienne, Department of Public Health and Medical Informatics, Saint-Etienne, France</aff><aff id="af3-1300_amia_2011_proc"><label>3</label> WHO FIC Collaborative Centre for International Classifications in French Language, Paris, France</aff><pub-date pub-type="ppub"><year>2011</year></pub-date><pub-date pub-type="epub"><day>22</day><month>10</month><year>2011</year></pub-date><pub-date pub-type="collection"><year>2011</year></pub-date><volume>2011</volume><fpage>1300</fpage><lpage>1308</lpage><permissions><copyright-statement>©2011 AMIA - All rights reserved.</copyright-statement><copyright-year>2011</copyright-year><license><license-p>This is an Open Access article: verbatim copying and redistribution of this article are permitted in all media for any purpose</license-p></license></permissions><abstract><p>Following the WHO initiative named World Alliance for Patient Safety (PS) launched in 2004 a conceptual framework developed by PS national reporting experts has summarized the knowledge available. As a second step, the Department of Public Health of the University of Saint Etienne team elaborated a Categorial Structure (a semi formal structure not related to an upper level ontology) identifying the elements of the semantic structure underpinning the broad concepts contained in the framework for patient safety. This knowledge engineering method has been developed to enable modeling patient safety information as a prerequisite for subsequent full ontology development. The present article describes the semantic dissection of the concepts, the elicitation of the ontology requirements and the domain constraints of the conceptual framework. This ontology includes 134 concepts and 25 distinct relations and will serve as basis for an Information Model for Patient Safety.</p></abstract></article-meta></front></pmc></record>Pour manipuler ce document sous Unix (Dilib)
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