De-identification of unstructured paper-based health records for privacy-preserving secondary use.
Identifieur interne : 000104 ( Main/Exploration ); précédent : 000103; suivant : 000105De-identification of unstructured paper-based health records for privacy-preserving secondary use.
Auteurs : Stefan Fenz [Autriche] ; Johannes Heurix ; Thomas Neubauer ; Antonio RellaSource :
- Journal of medical engineering & technology [ 1464-522X ] ; 2014.
English descriptors
- KwdEn :
- MESH :
Abstract
Abstract Whenever personal data is processed, privacy is a serious issue. Especially in the document-centric e-health area, the patients' privacy must be preserved in order to prevent any negative repercussions for the patient. Clinical research, for example, demands structured health records to carry out efficient clinical trials, whereas legislation (e.g. HIPAA) regulates that only de-identified health records may be used for research. However, unstructured and often paper-based data dominates information technology, especially in the healthcare sector. Existing approaches are geared towards data in English-language documents only and have not been designed to handle the recognition of erroneous personal data which is the result of the OCR-based digitization of paper-based health records.
DOI: 10.3109/03091902.2014.913080
PubMed: 24841844
Affiliations:
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Le document en format XML
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<affiliation wicri:level="3"><nlm:affiliation>Vienna University of Technology, Institute of Software Technology and Interactive Systems , Favoritenstrasse 9-11, 1040 Vienna , Austria.</nlm:affiliation>
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<wicri:regionArea>Vienna University of Technology, Institute of Software Technology and Interactive Systems , Favoritenstrasse 9-11, 1040 Vienna </wicri:regionArea>
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<series><title level="j">Journal of medical engineering & technology</title>
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<profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Artificial Intelligence</term>
<term>Confidentiality</term>
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<term>Image Processing, Computer-Assisted</term>
<term>Information Storage and Retrieval (methods)</term>
<term>Paper</term>
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<term>Confidentiality</term>
<term>Health Records, Personal</term>
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<front><div type="abstract" xml:lang="en">Abstract Whenever personal data is processed, privacy is a serious issue. Especially in the document-centric e-health area, the patients' privacy must be preserved in order to prevent any negative repercussions for the patient. Clinical research, for example, demands structured health records to carry out efficient clinical trials, whereas legislation (e.g. HIPAA) regulates that only de-identified health records may be used for research. However, unstructured and often paper-based data dominates information technology, especially in the healthcare sector. Existing approaches are geared towards data in English-language documents only and have not been designed to handle the recognition of erroneous personal data which is the result of the OCR-based digitization of paper-based health records.</div>
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<name sortKey="Rella, Antonio" sort="Rella, Antonio" uniqKey="Rella A" first="Antonio" last="Rella">Antonio Rella</name>
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