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Active Semantic Electronic Medical Record
A. Sheth1, S. Agrawal2, J. Lathem1, N. Oldham2, H. Wingate2, P. Yadav2, and K. Gallagher2
1LSDIS Lab, University of Georgia Athens, 30602 Georgia
amit@cs.uga.edu
lathem@cs.uga.edu
2Athens Heart Center Athens, 30606 Georgia
subodh@athensheartcenter.com
noldham@athensheartcenter.com
ppyadav@athensheartcenter.com
kgallagher@athensheartcenter.com
Abstract. The healthcare industry is rapidly advancing towards the widespread use of electronic medical records systems to manage the increasingly large amount of patient data and reduce medical errors. In addition to patient data there is a large amount of data describing procedures, treatments, diagnoses, drugs, insurance plans, coverage, formularies and the relationships between these data sets. While practices have benefited from the use of EMRs, infusing these essential programs with rich domain knowledge and rules can greatly enhance their performance and ability to support clinical decisions. Active Semantic Electronic Medical Record (ASEMR) application discussed here uses Semantic Web technologies to reduce medical errors, improve physician efficiency with accurate completion of patient charts, improve patient safety and satisfaction in medical practice, and improve billing due to more accurate coding. This results in practice efficiency and growth by enabling physicians to see more patients with improved care. ASEMR has been deployed and in daily use for managing all patient records at the Athens Heart Center since December 2005. This showcases an application of Semantic Web in health care, especially small clinics.
Keywords: Ontology, Rules, Electronic Medical Record (EMR), Electronic Health Record, Clinical Decision Support, RDQL, Web Services, Semantic Annotation, Active Semantic Document.
LNCS 4273, p. 913 ff.
lncs@springer.com
© Springer-Verlag Berlin Heidelberg 2006