Reality check

The recent implementation of the Electronic Health Record (EHR) in France is part of a more general process of digitizing information flows, as the world enters the fourth industrial revolution in a phenomenon known as Industry 4.0. Behind this concept lies the concern to allow Man to remain permanently in control of his destiny, despite an increasingly interconnected world (Internet of Things, cooperative robots, augmented reality, etc.). Accordingly, the implementation of EHR must guarantee the respect for the private life of each citizen. From this perspective, healthcare professionals will therefore have to constantly ensure the protection of medical confidentiality during Electronic Data Interchange (EDI). This paper summarises the current state of the use of EHR in France. Based on a survey conducted by the European Commission to assess the deployment of digitalisation in the health sector in EU countries, this article aims to highlight the opportunities and perspectives that Industry 4.0 could bring to the health sector in France. However, this study also identifies a number of limits related to the application of such a system, the first of which is cyber threat or transhumanism. To this end, a SWOT matrix identifies the strengths and weaknesses related to the implementation of the French EHR.

pdf/electronic-health-record-in-the-era-of-industry-4-0-the-4ue58delja.pdf

Electronic health record in the era of industry 4.0: the French example

Nowadays, the development of machine learning algorithms and big data frameworks make the processing of data a major asset in different sectors. Indeed, this technology allows us to carry out in-depth analyzes of large masses of data and thus generate very useful results for decision-making. Among the sectors where this technology is used is that of health in which analysis and prevention are essential to improve the quality of health care. Our research focuses on improving the application of this technology in the health field. In this paper we will present big data aspects, give some implementations and discuss different big data architectures in healthcare sector.

Processing and Analyzing Health Data in a Big Data Context: Aspects and Implementations

The delineation of organs at risk is the basis of radiotherapy oncologists’ work. Indeed, the knowledge of this delineation enables to better identify the target volumes and to optimize dose distribution, involving the prognosis of the patients but also their future. The learning of this delineation must continue throughout the clinician's career. Some contour changes have appeared with better imaging, some volumes are now required due to development of knowledge of side effects. In addition, the increasing survival time of patients requires to be more systematic and precise in the delineations, both to avoid complications until now exceptional but also because re-irradiations are becoming more and more frequent. We present the update of the recommendations of the French Society for Radiation Oncology (SFRO) on new findings or adaptations to volumes at risk.

Delineation of organs at risk.

Resume Les nombreuses avancees dans les systemes informatiques (collection de donnees, bases de donnees, stockage), les possibilites diagnostiques et therapeutiques sont responsables d’une augmentation et d’une diversification des donnees disponibles. Les big data offrent les capacites, dans le domaine de la sante, d’accelerer les decouvertes et d’optimiser la prise en charge des patients en combinant un nombre de donnees presque infini par la creation de modeles therapeutiques. En radiotherapie, le developpement des big data est attrayant car les donnees a traiter sont tres nombreuses et heterogenes (demographiques, radiomiques, genomiques, radiogenomiques, etc.). La prediction de l’efficacite et de la tolerance du traitement par irradiation serait alors optimisee. Avec ces nouveaux concepts, encore au stade preliminaire, il apparait possible de developper une medecine de haute precision et personnalisee, toujours plus securisee et fiable.

Les big data, généralités et intégration en radiothérapie

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Les big data, généralités et intégration en radiothérapie