title: Using an ontological modeling to evaluate the consistency of clinical practice guidelines: application to the comparison of three guidelines on the management of adult hypertension.
abstract: Every year, numerous clinical practice guidelines (CPGs) are published on a same topic. They may be conflicting, thus infringing clinicians' confidence in adhering to them. In order to build a clinical decision support system to assist GPs in the management of hypertension, we have considered three recent CPGs written in French. We developed a methodological framework to evaluate how consistent the three CPGs were. After a manual extraction of recommendation rules, all patient profiles covered by the CPGs have been identified. Then, ontological modeling and reasoning were used to build a subsumption graph of all profiles. This graph allows the retrieval of recommendations that could be conflicting. Results show that if rules are different in the three CPGs according to a document-based approach, many profiles are related through subsumption, and no critical inconsistencies were discovered when implementing an ontological modeling.
authors.affiliation: Vidal, Issy-les-Moulineaux, France.
authors.forename: Alexandre
authors.initials: A
authors.lastname: Galopin
authors.affiliation: AP-HP, DRCD, Paris, France.
authors.forename: Jacques
authors.initials: J
authors.lastname: Bouaud
authors.affiliation: Vidal, Issy-les-Moulineaux, France.
authors.forename: Suzanne
authors.initials: S
authors.lastname: Pereira
authors.affiliation: Sorbonne Universités, UPMC Université Paris 06, UMR_S 1142, LIMICS, Paris, France.
authors.forename: Brigitte
authors.initials: B
authors.lastname: Séroussi
mesh_terms: D000328:Adult; D000959:Antihypertensive Agents / Q000627:therapeutic use*; D064229:Biological Ontologies; D020000:Decision Support Systems, Clinical / Q000592:standards* / Q000706:statistics & numerical data*; D003661:Decision Support Techniques; D005602:France; D019983:Guideline Adherence / Q000706:statistics & numerical data; D006801:Humans; D006973:Hypertension / Q000188:drug therapy*; D050316:Medical Order Entry Systems / Q000592:standards* / Q000706:statistics & numerical data; D009323:Natural Language Processing; D017410:Practice Guidelines as Topic; D018875:Vocabulary, Controlled
chemical_list: D000959:Antihypertensive Agents