Document Detail

De-identifying an EHR Database - Anonymity, Correctness and Readability of the Medical Record.
MedLine Citation:
PMID:  21893869     Owner:  NLM     Status:  In-Data-Review    
Electronic health records (EHR) contain a large amount of structured data and free text. Exploring and sharing clinical data can improve healthcare and facilitate the development of medical software. However, revealing confidential information is against ethical principles and laws. We de-identified a Danish EHR database with 437,164 patients. The goal was to generate a version with real medical records, but related to artificial persons. We developed a de-identification algorithm that uses lists of named entities, simple language analysis, and special rules. Our algorithm consists of 3 steps: collect lists of identifiers from the database and external resources, define a replacement for each identifier, and replace identifiers in structured data and free text. Some patient records could not be safely de-identified, so the de-identified database has 323,122 patient records with an acceptable degree of anonymity, readability and correctness (F-measure of 95%). The algorithm has to be adjusted for each culture, language and database.
Kostas Pantazos; Soren Lauesen; Soren Lippert
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Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  Studies in health technology and informatics     Volume:  169     ISSN:  0926-9630     ISO Abbreviation:  Stud Health Technol Inform     Publication Date:  2011  
Date Detail:
Created Date:  2011-09-06     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  9214582     Medline TA:  Stud Health Technol Inform     Country:  Netherlands    
Other Details:
Languages:  eng     Pagination:  862-6     Citation Subset:  T    
Software Development Group, IT-University of Copenhagen, Denmark.
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