De-identification of unstructured paper-based health records for privacy-preserving secondary use

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.

• Computer security
• health records
• named entity recognition
• natural language processing
• privacy

Acknowledgements

We thank our business partners XiTrust Secure Technologies and Xylem Technologies for supporting the implementation of the case studies carried out within the MEDSEC project. The research was funded by BRIDGE (#824884), FFG – Austrian Research Promotion Agency, and supported by COMET K1, FFG - Austrian Research Promotion Agency.