This paper provides a methodological framework for decision making process to ensure its traceability generally in the context of telemedicine and particularly in the act of teleexpertise. This act permits to medical professionals and/or health professionals to collaborate in order to take suitable decisions for a patient diagnosis or treatment. The main problem dealing with teleexpertise is the following: How to ensure the traceability of the decisions making process? This problem is solved in this paper through a conceptualisation of a rigorous framework coupling semantic modelling and explicit reasoning which permits to fully support the analysis and rationale for decisions made. The logical semantic underlying this framework is the argumentative logic to provide adequate management of information with traceability of the reasoning including options and constraints. Thus our proposal will permit to formally ensure the traceability of reasoning in telemedicine and particularly in teleexpertise in order to favour the quality of telemedicine's procedure checking. This traceability is to guarantee equitable access to the benefits of the collective knowledge and experience and to provide remote collaborative practices with a sufficient safety margin to guard against the legal requirements. An illustrative case study is provided by the modelling of a decision making process applied to teleexpertise for chronic diseases such as diabetes mellitus type 2.
Current medical information systems are too complex to be meaningfully exploited. Hence there is a need to develop new strategies for maximising the exploitation of medical data to the benefit of medical professionals. It is against this backdrop that we want to propose a tangible contribution by providing a tool which combines conceptual graphs and Dung׳s argumentation system in order to assist medical professionals in their decision making process. The proposed tool allows medical professionals to easily manipulate and visualise queries and answers for making decisions during the practice of teleexpertise. The knowledge modelling is made using an open application programming interface (API) called CoGui, which offers the means for building structured knowledge bases with the dedicated functionalities of graph-based reasoning via retrieved data from different institutions (hospitals, national security centre, and nursing homes). The tool that we have described in this study supports a formal traceable structure of the reasoning with acceptable arguments to elucidate some ethical problems that occur very often in the telemedicine domain.
International audienceTelemedicine consists of the use of information and communication technologies (ICTs) in the practice of medicine. The massive digitalisation of the society is changing the behaviour of ordinary people even in medical sectors. The impact of digitisation is also having impacts on teleexpertise, where a medical professional can remotely ask some advices through the use of ICTs to provide treatment to a patient in critical conditions in remote environment. However, sometimes the outcome of such advice obtained remotely can lead to medical errors. In these situations, it is important to determine whether the causes of the errors could have been avoidable or not for the purposes of establishing the truth and assuring justice for the victims of medical errors. The proposed work fits this perspective with the objective to formalise elements of argumentation in collaborative medical organisations using telemedicine. In other words, a technique that extends the Dung's argumentation framework in order to bring out the errors committed following a remote medical procedure has been proposed. The proposed technique is underpinned by graphical reasoning. The reasoning is represented through a directed graph in which the extended nodes specify the arguments with their source(s) and the identification of errors is done according to the Makeham's and Tempos taxonomies. To illustrate the functioning of the proposed technique or solution, an example of the practice of teleexpertise (between two French hospitals) that leads to litigation is presented
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.