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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References
Abe, T., Ishimatsu, S., Tokuda, Y.: Descriptive analysis of patients’ EMS use related to severity in Tokyo: A population-based observational study. Plos One 8(3) (2013)
Poulymenopoulou, M., Malamateniou, F., Vassilacopoulos, G.: Emergency healthcare process automation using mobile computing and cloud services. Journal of Medical Systems 36(5), 3233–3241 (2012)
Knowlton, A., Weir, B., Hughes, B., Southerland, H., Schultz, C., Sarpatwari, R., Wissow, L., Links, J., Fields, J., McWilliams, J., Gaasch, W.: Patient demographic and health factors associated with frequent use of emergency medical services in a midsized city. Academic Emergency Medicine 20(11), 1101–1111 (2013)
Ortmann, J., Limbu, M., Wang, D., Kauppinen, T.: Crowdsourcing linked open data for disaster management. In: Terra Cognita 2011 Workshop at the ISWC (2011)
Chiolero, A., Santschi, V., Paccaud, F.: Public health surveillance with electronic medical records: At risk of surveillance bias and overdiagnosis. European Journal of Public Health 23(3), 350–351 (2013)
Kamateri, E., Kalampokis, E., Tambouris, E., Tarampanis, K.: The linked medical data access control framework. Journal of Biomedical Informatics 50, 213–225 (2014)
Janssen, M., Estevez, E., Janowski, T.: Interoperability in big, open, and linked data – organizational maturity, capabilities, and data portfolios. IEEE Computer Society (2014)
Heath, T., Bizer, C.: Linked Data: Evolving the Web into a Global Data Space (1st edition). Synthesis Lectures on the Semantic Web: Theory and Technology 1(1), 1–136 (2011)
Tilahum, B., Kauppinen, T., Kebler, C., Fritz, F.: Design and development of a linked open data-based health information representation and visualization system: Potentials and preliminary evaluation. Journal of Medical Internet Research (JMIR) Medical Informatics 2(2) (2014)
Pathak, J., Kiefer, R., Chute, C.: Using linked data for mining drug-drug interactions in electronic health records. Studies in Healthcare Technology and Information 192, 682–686 (2013)
Tian, L., Zhang, W., Bikakis, A., Wang, H., Yu, Y., Ni, Y., Cao, F.: MeDetect: A LOD-based system for collective entity annotation in biomedicine. In: Proceedings of the International Conferences on Web Intelligence and Intelligent Agent Technology, pp. 233–240. IEEE Computer Society (2013)
Ferguson, M.: Architecting a big data platform for analytics. Intelligent Business Strategies (2012), http://www.ndm.net/datawarehouse/pdf/Netezza%20-%20Architecting%20A%20Big%20Data%20Platform%20for%20Analytics.pdf
Poulymenopoulou, M., Malamateniou, F., Vassilacopoulos, G.: Document management mechanism for holistic emergency care. International Journal of Healthcare Information Systems and Informatics 9(2) (2014)
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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
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