To date, the possibility of doing research on quality-of-care assessment in emergency medicine has clashed against sustainability problems. The vast number of patients visiting an ED and the staff shortage that often afflicts these departments make ad hoc data collections unattainable. The only way to fill the gap between the need for clinical research and the availability of robust data is to directly extract such data from the EDs electronic health records (EHRs), avoiding dedicated data collection. Achieving this goal would enable distributed clinical research, which is now too much restricted to academic centres, and allow to leverage of clinical information to address a multitude of research questions. Nonetheless, obtaining consistent data from EHRs is a complex task. While a small part of the data registered in EHRs is structured (such as lab test results and vital parameters), most of the useful information on patients' conditions is variably contained in free text (e.g. presence of signs and symptoms, suspected and confirmed diagnosis, anamnesis, etc.). Moreover, as a proactive follow-up of ED patients is unfeasible, relying on the existing data sources is also necessary to measure the outcome of the patients at the most appropriate time interval for the research question of interest. This proposal has three main aims: 1) to develop new technical solutions to extract reliable clinical information from structured and unstructured data contained in different electronic patient files; 2) to FAIRify (i.e. making data Findable, Accessible, Interoperable, and Re-usable) the established databases for clinicians, researchers, health policymakers and citizens while respecting the European and national legislations; 3) to pilot the exploitation of the established databases in two relevant use cases: i) assessment of ED propensity to hospitalise a patient, and ii) development of a dashboard to be used by citizens and policymakers to improve the quality of care in ED.