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Scalable, Standard based Interoperability Framewor.. (SALUS)
Scalable, Standard based Interoperability Framework for Sustainable Pro-active Post Market Safety Studies
(SALUS)
Date du début: 1 févr. 2012,
Date de fin: 30 avr. 2015
PROJET
TERMINÉ
Pre-approval clinical trials cannot possibly ensure that a drug will not have disastrous side effects once it arrives on the market. Post-approval safety data gathering was put in place to address this problem, but as implemented, it has not proven to be as effective as hoped. This is due to the fact that, current post market safety studies largely depend on the submission of spontaneous case reports where underreporting is a major problem. The need for a proactive approach is apparent, where safety data from multiple sources are actively monitored, linked and analyzed. Effective integration and utilization of electronic health records (EHR) can help to improve post-market safety activities on a proactive basis. There are prototype studies to monitor EHRs for simplifying ADE reporting, and also for signal detection by screening multiple EHRs, however these tools are directly built on top of EHR/EMR systems through proprietary interfaces. It is apparent that the promise of proactive, continuous monitoring of multiple sources cannot be achieved through such proprietary integrations. To facilitate wide scale proactive post market safety studies, there is a need for a new capacity enabling accessing the data locked in multiple different heterogonous EHR systems. In SALUS project, we aim to provide a standard-based interoperability framework that will enable execution of safety studies for mining and analyzing real-time patient data in communication with disparate heterogeneous EHR systems. SALUS will provide:\tFunctional interoperability profiles enabling exchange of EHRs\tSemantic interoperability solutions enabling meaningful interpretation of the exchanged EHRs\tSecurity and Privacy mechanisms ensuring EHRs are shared in an ethical and safe way\tA novel framework for open-ended temporal pattern discovery for safety studies on top of EHR Systems\tImplementation of high potential use cases enabling secondary use of EHRs for post market safety studies
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