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J Med Syst (2016) 40: 83DOI 10.1007/s10916-016-0431-7
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Image De-Identification Methods for Clinical Research in the XDS Environment
K. Y. E. Aryanto1 & G. van Kernebeek2 & B. Berendsen3 &
M. Oudkerk1 & P. M. A. van Ooijen1
Received: 16 July 2014 /Accepted: 7 January 2016 /Published online: 26 January 2016 # The Author(s) 2016. This article is published with open access at Springerlink.com
Abstract To investigate possible de-identification methodologies within the Cross-Enterprise Document Sharing for imaging (XDS-I) environment in order to provide strengthened support for image data exchange as part of clinical research projects. De-identification, using anonymization or pseudonymization, is the most common method to perform information removal within DICOM data. However, it is not a standard part of the XDS-I profiles. Different methodologies were observed to define how and where de-identification should take place within an XDS environment used for scientific research. De-identification service can be placed in three locations within the XDS-I framework: 1) within the Document Source, 2) between the Document Source and Document Consumer, and 3) within the Document Consumer. First method has a potential advantage with respect to the exposure of the images to outside systems but has drawbacks with respect to additional hardware and configuration requirements. Second and third method have big concern in exposing original documents
with all identifiable data being intact after leaving the Document Source. De-identification within the Document Source has more advantages compared to the other methods. On the contrary, it is less recommended to perform de-identification within the Document Consumer since it has the highest risk of the exposure of patients identity due to the fact that images are exposed without de-identification during the transfers.
Keywords XDS . XDS-I . Cross-enterprise document sharing . De-identification . Clinical Research . Patient data privacy
Introduction
Medical imaging informatics has brought up numerous advantages and offers social, economic, clinical, and technical benefits for patient care. It plays an important role as it enables the establishment of an affordable yet high quality level of healthcare. Furthermore, the presence of imaging informatics in clinical trials and research promotes standardization in order to...