Computer research applied to health – ERIAS

With the rapid development of Information Technology (IT), the availability of numeric data in various domains is increasing. Yet, it is possible to obtain from them meaningful facts that can lead to new knowledge. In the public health domain in particular, great is the opportunity to speed up and facilitate research activities. Moreover, the availability of additional data enables the enlargement of the scope of data to exploit (e.g., a better representability of the studied population or a supplementary data dimension available for a population). Thereby, facilitating secondary use of different kinds of data is a promising approach from the public health perspective.

However, in addition to being available, data have to be adapted for secondary use purpose. Automating the tasks required for such adaptations is raising new challenges. Indeed, IT-based approaches need to take into account the specificities of health-related data for being successful. The major issues raised by such data are: (i) the inherent incertitude that they may hold but also (ii) their temporal facet as well as (iii) the implicit meaning they convey, which often depends on common knowledge shared by physicians that may not be explicitly expressed. These specificities combined with the complexity of conducted research in the meantime require specific approaches. They can benefit from the long tradition of health professionals to classify things for describing the biomedical domain although the rapid evolution of knowledge in this field constitutes an additional challenge. Overcoming these issues needs a pluridisciplinary approach, involving both medical and computer science skills.

Data of Interest

Electronic health records

Electronic health records (EHRs) are recognized as a major source of information for research purpose. Even when research data are acquired by hand, EHRs are often used. Indeed, a possible workflow is to manually review patient’s EHRs in order to enter data within databases specifically structured for research purpose. As a result, enabling direct reuse of EHRs in order to automatically feed research databases is an essential issue and is the subject of numerous studies for several years. Secondary use of EHRs is not a straightforward task. Indeed, when reusing data in EHRs, multiple challenges are to be addressed including semantic and syntactic data normalization, phenotype identification and data quality evaluation.

Web-based data

The Web constitutes nowadays a new channel of information. On the one hand, the context of modern healthcare practice requires to access to recent findings as reported in the scientific literature. On the other hand, data that are being generated in the context of social networks may be a useful resource which contains real-time data and may complement those from databases provided by official bodies or fed by EHRs. However, although valuable, these data are unstructured and expressed in natural language, sometimes in a poor, informal or degraded vocabulary (online health related forums for instance). With the objective to make use of such data for being able to address use-cases for which no other data can be exploited, ERIAS provides methods and tools in order to tackle Web-based data. For instance, in the pharmacovigilance domain, the identification of adverse-drug events as well as drug misuses may benefit from the exploitation of such data.