Preserving medical correctness, readability and consistency in de-identified health records.

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.

De-identifying an EHR database - anonymity, correctness and readability of the medical record.

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.

The Danish National Health Informatics Strategy.

The central vision for the future information systems in the Danish health care sector is one of a generally accepted, common information model enabling comprehensive digital reuse of shared clinical data. A generic 'Basic-EHR-structure' has been developed for this purpose by the National Board of Health from a through analysis of the production of clinical information. The strategy contributes to the achievement of the national political goals for the health care sector and describes four important steps to be made by the health care IT systems in order to reach full interoperability and digital reusability of clinical information. Some important initiatives of the strategy are a national terminology server, coordinated implementation of EHRs, and the Public Health Information Portal.

[The Good Medical Department. Results from a national survey of quality in 1998]. / Den gode medicinske afdeling. Resultater fra en national undersøgelse af kvalitet i 1998.

INTRODUCTION: This cross-sectional study describes quality related data from 39 medical wards in Denmark. MATERIAL AND METHODS: The study is based on a review of 1517 medical records and a short patient interview. The medical departments took part voluntarily in the study, which was initiated by the Danish Society for Internal Medicine. RESULTS: A total of 23 quality-related indicators related to the planning of the treatment, documentation in patient records, and care were registered. The day before the data collection was an inactive inpatient day for 22.8 +/- 1.1% of patients. Allergy was insufficiently documented in the medical record for 18.8 +/- 1.0% of patients. Weight was not documented in 48.8 +/- 1.3% of patients. Considerations about anticoagulation treatment of atrial fibrillation were not documented in 50.1 +/- 3.6% of patients with atrial fibrillation. DISCUSSION: This study indicates that it is possible on a voluntary basis to collect and distribute quality-related data. The survey has recently been repeated with a modified data registration sheet.