International audience ; Breast cancer is identified as the most common type of cancer in women worldwide with 1.6 million women around the world diagnosed every year. This prompts many active areas of research in identifying better ways to prevent, detect, and treat breast cancer. DESIREE is a European Union funded project, which aims at developing a web-based software ecosystem for the multidisciplinary management of primary breast cancer. The development of an intelligent clinical decision support system offering various modalities of decision support is one of the key objectives of the project. This paper explores case-based reasoning as a problem solving paradigm and discusses the use of an explicit domain knowledge ontology in the development of a knowledge-intensive case-based decision support system for breast cancer management.
International audience ; Breast cancer is identified as the most common type of cancer in women worldwide with 1.6 million women around the world diagnosed every year. This prompts many active areas of research in identifying better ways to prevent, detect, and treat breast cancer. DESIREE is a European Union funded project, which aims at developing a web-based software ecosystem for the multidisciplinary management of primary breast cancer. The development of an intelligent clinical decision support system offering various modalities of decision support is one of the key objectives of the project. This paper explores case-based reasoning as a problem solving paradigm and discusses the use of an explicit domain knowledge ontology in the development of a knowledge-intensive case-based decision support system for breast cancer management.
International audience ; Breast cancer is identified as the most common type of cancer in women worldwide with 1.6 million women around the world diagnosed every year. This prompts many active areas of research in identifying better ways to prevent, detect, and treat breast cancer. DESIREE is a European Union funded project, which aims at developing a web-based software ecosystem for the multidisciplinary management of primary breast cancer. The development of an intelligent clinical decision support system offering various modalities of decision support is one of the key objectives of the project. This paper explores case-based reasoning as a problem solving paradigm and discusses the use of an explicit domain knowledge ontology in the development of a knowledge-intensive case-based decision support system for breast cancer management.
International audience ; Breast cancer is identified as the most common type of cancer in women worldwide with 1.6 million women around the world diagnosed every year. This prompts many active areas of research in identifying better ways to prevent, detect, and treat breast cancer. DESIREE is a European Union funded project, which aims at developing a web-based software ecosystem for the multidisciplinary management of primary breast cancer. The development of an intelligent clinical decision support system offering various modalities of decision support is one of the key objectives of the project. This paper explores case-based reasoning as a problem solving paradigm and discusses the use of an explicit domain knowledge ontology in the development of a knowledge-intensive case-based decision support system for breast cancer management.
Breast cancer is identified as the most common type of cancer in women worldwide with 1.6 million women around the world diagnosed every year. This prompts many active areas of research in identifying better ways to prevent, detect, and treat breast cancer. DESIREE is a European Union funded project, which aims at developing a web based software ecosystem for the multidisciplinary management of primary breast cancer. The development of an intelligent clinical decision support system offering various modalities of decision support is one of the key objectives of the project. This paper explores case-based reasoning as a problem solving paradigm and discusses the use of an explicit domain knowledge ontology in the development of a knowledge-intensive case-based decision support system for breast cancer management.
Résumé Objectifs : Développer et étudier l'impact d'un système informatique de tableaux de bord de Suivi (TBS) basé sur des recommandations. Méthodes : Un groupe de médecins généralistes a défini la structure et les fonctionnalités du système (rappel des procédures et des dates de réalisation, visualisation synthétique des informations). L'éditeur du logiciel de dossier médical éO l'a implémenté. Plan expérimental : étude randomisée, contrôlée, en grappes, comparant éO + TBS (groupe intervention) versus éO (groupe témoin). Population : utilisateurs de éO et leurs patients diabétiques et/ou hypertendus ≥ 25 ans. Données extraites des dossiers informatisés, après anonymisation, en aveugle du groupe de randomisation. Critère de jugement : caractère à jour du suivi pour chaque procédure, dans chaque groupe, avant et après intervention. Impact mesuré par la différence absolue d'évolution entre les groupes, ajustée sur l'âge, le sexe, l'origine géographique et la catégorie professionnelle des patients. Résultats : Cinquante médecins ont inclus 2 715 patients. Résultats en faveur du groupe intervention pour 14 des 16 procédures analysées. Différence ajustée statistiquement significative, chez les diabétiques, pour l'IMC, l'examen des pieds, l'électrocardiogramme, l'examen du fond d'œil, chez les hypertendus pour l'IMC et la protéinurie à la bandelette. Conclusions : Les TBS facilitent l'application des recommandations en consultation. Ils sont facilement transposables à d'autres logiciels, pour toutes les pathologies chroniques et la prévention. L'utilisation des TBS contribuerait à structurer et coder uniformément les informations des dossiers médicaux quel que soit le logiciel, et fournirait à chaque médecin des indicateurs de la qualité de sa pratique. Prat Organ Soins 2009;40(3):177-189
Les objectifs du site P2Vie sont de mettre à profit les nouvelles technologies de l'information et de la communication pour réunir dans un système d'informations les éléments destinés au senior, permettant ainsi d'améliorer la prévention du vieillissement et d'optimiser la prise en charge des sujets dont l'état nécessite de recourir au système de soins. Plus spécifiquement, ce projet a permis de définir trois grands objectifs: la constitution d'un serveur d'informations médicales, celle d'un serveur d'informations socio-administratives et l'élaboration d'un carnet de santé électronique géré par le senior. Les perspectives attendues sont la mise en place d'un partenariat avec un site santé afin de proposer ce service au grand public.
Background: C3-Cloud is an integrated care ICT infrastructure offering seamless patient-centered approach to managing multimorbidity, deployed in three European pilot sites. Challenge: The digital delivery of best practice guidelines unified for multimorbidity, customized to local practice, offering the capability to improve patient personalization and benefit. Method: C3-Cloud has adopted a co-production approach to developing unified multimorbidity guidelines, by collating and reconciling best practice guidelines for each condition. Clinical and technical teams at pilot sites and the C3-Cloud consortium worked in tandem to create the specification and technical implementation. Results: C3-Cloud offers CDSS for diabetes, renal failure, depression and congenital heart failure, with over 300 rules and checks that deliver four best practice guidelines in parallel, customized for each pilot site. Conclusions: The process provided a traceable, maintainable and audited digitally delivered collated and reconciled guidelines.
