Literature DB >> 19745233

ReMINE: an ontology-based risk management platform.

Michele Carenini1.   

Abstract

The ReMINE project aims at building a high performance prediction, detection and monitoring platform for managing Risks against Patient Safety (RAPS). The project will contribute to the optimization of RAPS management process in a healthcare system through the development of a platform allowing the (semantically based) fast and secure extraction of RAPS-related data and their correlation across several domains. In this respect the REMINE platform will promote early RAPS detection and mitigation by supporting the process of RAPS management both when a RAPS is foreseen, and the objective is the determination of the best set of preventive actions; and when a RAPS is detected, and the objective is the determination of the best possible reaction, the reliable distribution of the related action list to all involved parties, and the monitoring of the reaction effectiveness. These capabilities will be achieved by means of the establishment of an associated methodology and a framework/platform for integrated RAPS prediction/detection, analysis and mitigation. The overall platform structure assumes the presence of an "info-broker patient safety framework" connected with the Hospital Information System, which will support the process of collecting, aggregating, mining and assessing related data, distributing alerts, and suggesting actions to mitigate (or avoid) RAPS effects or occurrence. The underlying ontological system will support the semantic correlation of data with the hospital processes.

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Mesh:

Year:  2009        PMID: 19745233

Source DB:  PubMed          Journal:  Stud Health Technol Inform        ISSN: 0926-9630


  2 in total

1.  Modeling patient safety incidents knowledge with the Categorial Structure method.

Authors:  Julien Souvignet; Cédric Bousquet; Pierre Lewalle; Béatrice Trombert-Paviot; Jean Marie Rodrigues
Journal:  AMIA Annu Symp Proc       Date:  2011-10-22

2.  A realism-based approach to an ontological representation of symbiotic interactions.

Authors:  Matthew Diller; Evan Johnson; Amanda Hicks; William R Hogan
Journal:  BMC Med Inform Decis Mak       Date:  2020-10-08       Impact factor: 2.796

  2 in total

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