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.

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Abstract:Several information visualization toolkits and tools have been developed to facilitate users work. However, evaluation studies for these toolkits and tools from a user perspective have been overlooked. In this paper, we evaluate 13 information visualization toolkits and tools developed in the last 10 years from a user perspective. For each user type (novice, savvy and expert), we investigated the toolkits and tools using 5 dimensions. This study shows that tools for savvy users-users with basic programming skills and domain knowledgeare lacking, and these users should be supported with more tools to construct advanced visualizations. We outline our approach to how savvy users can be engaged more in the development process and construct advanced visualizations. Information visualization community should focus more on moving the boundary of constructing advanced visualizations from expert users towards savvy users.