Abstract
The linked open data (LOD) initiative – an initiative taken by governments around the world to open up and link the vast repositories of data they hold across agencies and departments – features particular potential in the health care sector. The real value of linked open data comes from its interpretation, analysis and linking up which, in the healthcare sector, is expected to result in improved quality of care and lower healthcare costs. In particular, emergency healthcare quality is expected to improve by making healthcare data, which is related to emergency healthcare, available to authorized users at the point of care (suitably anonymized for security reasons) and by providing researchers with access to large volumes of data. In addition, the analysis of emergency healthcare LOD can provide insights on a variety of factors contributing to emergency medical services (EMS) usage and to EMS failures so that to formulate sustained emergency healthcare policies and enable effective and efficient decision making that results in improving emergency case morbidity and mortality indices. This paper addresses the general problem of LOD usage in emergency healthcare delivery and describes a LOD-based cloud service that seeks to automatically export appropriate emergency healthcare data of interest from a variety of sources, semantically annotate this data and enriching it through the creation of links with other, relevant, data. To this end the service is designed to interact with EMS information systems, electronic medical records (EMRs) and personal health records (PHRs).
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Poulymenopoulou, M., Malamateniou, F., Vassilacopoulos, G. (2015). A LOD-Based Service for Extracting Linked Open Emergency Healthcare Data. In: Ortuño, F., Rojas, I. (eds) Bioinformatics and Biomedical Engineering. IWBBIO 2015. Lecture Notes in Computer Science(), vol 9044. Springer, Cham. https://doi.org/10.1007/978-3-319-16480-9_9
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DOI: https://doi.org/10.1007/978-3-319-16480-9_9
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-16479-3
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