If your research involves the exchange or linkage of privacy-sensitive data with (one or more) third parties, always follow the guideline for secure data linkage. To make sure you work in the best way possible a number of tools have been developed.
Secure Data Linkage Toolkit:
- Privacy Assessment tools
- Decision Tree
- NL Data Linkage Form
- Standardized linking procedures incl. Best Practice examples
- Trusted Third Party (TTP) (explanation by ELSI Helpdesk)
For more information, please also read ‘Data delen en koppelen’ at the ELSI helpdesk’.
Frequently Asked Questions
Is there a checklist for data sharing?
A Dutch checklist for sharing data has been developed by Radboud UMC.
What are the required pre-conditions for data sharing?
The captured data from one or more sources are made available in a research environment.
The research environment is well defined in terms of:
- ownership and governance;
- infrastructure and architecture (e.g., a distributed virtual research environment).
and argued with respect to:
- fit for purpose;
- level of data sensitivity;
- level of completeness;
- level of security.
What are the Levels of Data Sensitivity?
Level 5 - Extremely sensitive information about individually identifiable people
Level 4 - Very sensitive information about individually identifiable people
Level 3 - Sensitive information about individually identifiable people
Level 2 - Benign information about individually identifiable people
Level 1 - De-identified research information about people and other non-confidential research information
What determines successful data linkage from a research perspective?
The success in linkage is determined by a number of factors (described in detail in Biolink):
- Choice in linking variables: name and address, sex, date of birth
- Choice of algorithm: either looking for deterministic (exact matching) variables or probabilistic (similar) variables.
- Amount of data overlap
- Amount of errors in the dataset
What are real-life examples of data linkage?
- The paper ‘Record linkage for health studies: three demonstration projects’ describes three data linking projects:
- The Netherlands Twin Register (NTR) linked with the Achmea Health Database (AHD).
- The KOALA cohort with a number of pharmacies in the database of the Stichting Farmaceutische Kengetallen (SFK).
- The population register (Basisregistratie Personen, BRP, formerly the Gemeentelijke Basisadministratie) and employment register (ER, in Dutch: Werknemersbestand).
- The paper ‘Using record linkage to construct a population-‐based cancer patient cohort with multiple disease outcomes’ describes methods and experiences of the Netherlands Cancer Institute in the construction of a population-based breast cancer survivor cohort linked with cardiovascular disease and mortality registries.