Retrieval And Visualization in ELectronic health records – RAVEL

The development of Electronic Healthcare Records (EHR) Datawarehouses and the Personal Health Record leads to a new paradigm in the way the healthcare professionals (as well as patients) interact with medical data.
These data, whether structured or full text, are both numerous, accurate, diverse, and immediately accessible at the patient bedside.
Because of this profusion of information, the healthcare professionals may face difficulties for making diagnostic and therapeutic decision and patients may misunderstand their health status.

They need to have effective tools to locate in real time relevant elements of the patient’s EHR and visualize them according to synthetic and intuitive presentation models.

The RAVEL project aims at achieving this goal by performing a high profile industrial research and development programme on the EHR considering the following areas:
(i) Semantic indexing,
(ii) Information retrieval
(iii) Data visualization.

The consortium includes both researchers specialized on these topics, persons involved in the implementation of Hospitals Information Systems (HIS) and market leaders private companies.

The scientific research program of the project focuses on the improvement of the state of the art on the three mentioned areas. To do so, the research works will attempt to meet the requirements to be defined by business use cases with the medical staff of two University Hospitals. The RAVEL project will lead to the implementation of a prototype sufficiently generic and loosely coupled to data sources in order to be transposed into different university HIS. This prototype will be evaluated in situations of actual use.

Many benefits are expected from the RAVEL project. From the medical point of view, it will be the improvement of the decision making of the healthcare professionals and therefore the quality of patients care. From the societal point of view, the methods and tools developed will allow the patients to better take possession of their medical data in order to be proactive in their approach to healthcare. From the scientific point of view, the RAVEL project is a unique opportunity to develop Natural

Language Processing (NLP) methods, approaches for the semantic integration of heterogeneous data, retrieval and multimodal representation methods applied to medical data. Finally, from the industrial point of view, the innovations resulting from the project will allow a significant functional and technological leap in a market increasingly competitive.