Reconciliation of Multiple Guidelines for Decision Support: A case study on the multidisciplinary management of breast cancer within the DESIREE project

Brigitte Seroussi, Gilles Guézennec, Jean-Baptiste Lamy, Naiara Muro, Nekane Larburu, Boomadevi Sekar, Coralie Prebet, Jacques Bouaud

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Citations (Scopus)

Abstract

Breast cancer is the most common cancer among women. DESIREE is a European project which aims at developing web-based services for the management of primary breast cancer by multidisciplinary breast units (BUs). We describe the guideline-based decision support system (GL-DSS) of the project. Various breast cancer clinical practice guidelines (CPGs) have been selected to be concurrently applied to provide state-of-the-art patient-specific recommendations. The aim is to reconcile CPG recommendations with the objective of complementarity to enlarge the number of clinical situations covered by the GL-DSS. Input and output data exchange with the GL-DSS is performed using FHIR. We used a knowledge model of the domain as an ontology on which relies the reasoning process performed by rules that encode the selected CPGs. Semantic web tools were used, notably the Euler/EYE inference engine, to implement the GL-DSS. "Rainbow boxes" are a synthetic tabular display used to visualize the inferred recommendations.
LanguageEnglish
Title of host publicationAMIA Annual Symposium Proceedings
Pages1527-1536
Publication statusE-pub ahead of print - 8 Nov 2017
EventAMIA Annual Symposium 2017 - Washington DC, United States
Duration: 4 Nov 20178 Nov 2017

Conference

ConferenceAMIA Annual Symposium 2017
Abbreviated titleAMIA
CountryUnited States
Period4/11/178/11/17

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Practice Guidelines
Guidelines
Breast Neoplasms
Semantics
Neoplasms

Cite this

Seroussi, B., Guézennec, G., Lamy, J-B., Muro, N., Larburu, N., Sekar, B., ... Bouaud, J. (2017). Reconciliation of Multiple Guidelines for Decision Support: A case study on the multidisciplinary management of breast cancer within the DESIREE project. In AMIA Annual Symposium Proceedings (pp. 1527-1536)
Seroussi, Brigitte ; Guézennec, Gilles ; Lamy, Jean-Baptiste ; Muro, Naiara ; Larburu, Nekane ; Sekar, Boomadevi ; Prebet, Coralie ; Bouaud, Jacques. / Reconciliation of Multiple Guidelines for Decision Support: A case study on the multidisciplinary management of breast cancer within the DESIREE project. AMIA Annual Symposium Proceedings . 2017. pp. 1527-1536
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Seroussi, B, Guézennec, G, Lamy, J-B, Muro, N, Larburu, N, Sekar, B, Prebet, C & Bouaud, J 2017, Reconciliation of Multiple Guidelines for Decision Support: A case study on the multidisciplinary management of breast cancer within the DESIREE project. in AMIA Annual Symposium Proceedings . pp. 1527-1536, AMIA Annual Symposium 2017 , United States, 4/11/17.

Reconciliation of Multiple Guidelines for Decision Support: A case study on the multidisciplinary management of breast cancer within the DESIREE project. / Seroussi, Brigitte; Guézennec, Gilles; Lamy, Jean-Baptiste; Muro, Naiara; Larburu, Nekane; Sekar, Boomadevi; Prebet, Coralie; Bouaud, Jacques.

AMIA Annual Symposium Proceedings . 2017. p. 1527-1536.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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AU - Muro, Naiara

AU - Larburu, Nekane

AU - Sekar, Boomadevi

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AU - Bouaud, Jacques

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AB - Breast cancer is the most common cancer among women. DESIREE is a European project which aims at developing web-based services for the management of primary breast cancer by multidisciplinary breast units (BUs). We describe the guideline-based decision support system (GL-DSS) of the project. Various breast cancer clinical practice guidelines (CPGs) have been selected to be concurrently applied to provide state-of-the-art patient-specific recommendations. The aim is to reconcile CPG recommendations with the objective of complementarity to enlarge the number of clinical situations covered by the GL-DSS. Input and output data exchange with the GL-DSS is performed using FHIR. We used a knowledge model of the domain as an ontology on which relies the reasoning process performed by rules that encode the selected CPGs. Semantic web tools were used, notably the Euler/EYE inference engine, to implement the GL-DSS. "Rainbow boxes" are a synthetic tabular display used to visualize the inferred recommendations.

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Seroussi B, Guézennec G, Lamy J-B, Muro N, Larburu N, Sekar B et al. Reconciliation of Multiple Guidelines for Decision Support: A case study on the multidisciplinary management of breast cancer within the DESIREE project. In AMIA Annual Symposium Proceedings . 2017. p. 1527-1536