Abstract
A health record database contains structured data fields that identify the patient, such as patient ID, patient
name, e-mail and phone number. These data are fairly easy to de-identify, that is, replace with other
identifiers. However, these data also occur in fields with doctors’ free-text notes written in an abbreviated
style that cannot be analyzed grammatically. If we replace a word that looks like a name, but isn’t, we degrade
readability and medical correctness. If we fail to replace it when we should, we degrade confidentiality. We de-identified an existing Danish electronic health record database, ending up with 323,122 patient health records. We had to invent many methods for de-identifying potential identifiers in the free-text notes. The de-identified health records should be used with caution for statistical purposes because we removed health records that were so special that they couldn’t be de-identified. Furthermore, we distorted geography by replacing zip codes with random zip codes.
name, e-mail and phone number. These data are fairly easy to de-identify, that is, replace with other
identifiers. However, these data also occur in fields with doctors’ free-text notes written in an abbreviated
style that cannot be analyzed grammatically. If we replace a word that looks like a name, but isn’t, we degrade
readability and medical correctness. If we fail to replace it when we should, we degrade confidentiality. We de-identified an existing Danish electronic health record database, ending up with 323,122 patient health records. We had to invent many methods for de-identifying potential identifiers in the free-text notes. The de-identified health records should be used with caution for statistical purposes because we removed health records that were so special that they couldn’t be de-identified. Furthermore, we distorted geography by replacing zip codes with random zip codes.
Original language | English |
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Journal | Health Informatics Journal |
Pages (from-to) | 1-13 |
Number of pages | 13 |
ISSN | 1460-4582 |
DOIs | |
Publication status | Published - 1 Jan 2016 |
Keywords
- anonymi
- consistency
- de-identification
- electronic health record
- readability