Decision-making system for medical research and care of patients.
- Develop new means of collection of standardized structured data both for the patient record computerized in support of patients in primary care or hospital and for the constitution of cohorts and clinical trials.
- Propose new models of clinical data warehouses and flat forms of integration of health data complex multi-scale.
- Develop new methods including graphics and new consultation tools, visualization, synthesis and exploitation of clinical or epidemiological data and medical knowledge.
- Develop decision-making aid for research and support of patients, able to rely on electronic records data and knowledge bases are easy to maintain.
In the context of clinical trials and epidemiological research, issues relate to :
- biological research which, under the constitution of databases and bio banks, must incorporate a significant amount of phenotypic data and \" omics \" to develop and validate assumptions by comparing individual anonymous data models in silico;
- clinical research that designs and implements implementing national and international clinical trials to test new diagnostic and therapeutic options. The challenge is to optimize the recruitment of patients, collection and treatment of clinical data and the detection of adverse events, research in epidemiology and public health that is based on the constitution of cohorts to identify determinants of health and develop health policies.
Facing these challenges, researchers are confronted with difficulties of collection and exploitation of health information which become increasingly heterogeneous in their nature (genomic, physiological, biological, clinical, social), their format (text, numeric values, signals, 2D images and 3D, genomic sequences, etc) and their dispersion in several information systems (hospital groups and offices of general practitioners and specialists). To make possible their treatment and exploitation, these multimodal and complex information must be acquired so structured and coded to be integrated either centrally in warehouses of data, either Federated via integration platforms. Finally, the volume of information makes it difficult to a synthetic vision of these, automatic summaries must be carried out to make them easier to interpret
In the context of the care, the issues relate to :
- the coordination of care with the improvement of the care of patients both in terms of safety by better detection of high-risk situations and in terms of therapeutic strategy by taking into account reasoned scientific knowledge of the time
- the assessment of the quality of the practices characterized by hospital or primary care quality indicators
These challenges practitioners face a growing complexity of their task. This is related to the high incidence of chronic disease (type 2 diabetes, hypertension, Dyslipidemia, cancers...) that can evolve on several decades, advances in biology and imaging offering the physician the choice of diagnostic procedures which often ignore performance, the therapeutic advances that lead to difficult to control without dedicated tools for treatment and follow-up strategies. The consultation of the electronic patient records that contain numerous and heterogeneous data becomes laborious. Summaries should be performed to help the doctor understand easily the medical history of the patient, its evolution, its major risks. Diagnostic and therapeutic decision support tools, interoperable with the patient record, easy to maintain and well integrated into the environment of the physician's work must be developed to optimize the support of patients.
Researchers and practitioners must constantly update their knowledge in a critical way and to do access various heterogeneous sources that may be scientific articles journals literature, guides to good practice clinics, meta-analyses, databases \" omics \", models physiological multi-scale in silico and whose identification and consultation takes time.