Development↦Data Management↦Database Development↦Data Coding and Anonymisation
What is it? Why is it important?
Data Coding and Anonymisation are processes by which study Participant Identifiers (PI) (e.g. first and last name, address, date of birth) are removed or encrypted in order to comply with privacy protection laws (e.g. data protection act).
Participant Identifiers (PI) include:
- Evident identifiers: such as name, date of birth, or personal address
- Less obvious identifiers: may lead to the identification of a participant when used in conjunction with other data (e.g. date of visits, rare diseases or conditions, marital status, number of children, religion, race)
Coded Data
Data is considered coded if, without access to a key (e.g. participant-identification-log) or source data, a link between health-related personal data (study data) / biological material and a specific person is not possible - without disproportionate effort.
Data Anonymisation
The association between a specific person and its health-related personal data (study data) and/or biological material is done in such a way that an identification can only be re-established with disproportionate efforts.
What do I need to do?
As a Site-INV:
For Coded Data:
- Identify study data that qualify as PIs
- Replace PIs with an individualised study ID-code. The code is subsequently used in the study (e.g. e-CRF)
- Create a document that provides a match between the study ID-Code and PIs (e.g. participant-identification-log)
- Store the ID-Code separately from the study data and biological material
- Define the location and who retains the ID-Code (e.g. person or organisational unit), and ensure neither are involved in the study
For Data Anonymisation
- Methods used are documented and based on the current state of the art
- Data which, individually or in combination, may allow for the re-identification must be deleted or modified
Coding and anonymisation are documented procedures to be submitted to the Ethics Committee (EC) for approval. Include any residual risks of re-identification.
More
Consult with the data manager (CDMS) on how to best implement coding/anonymisation procedures in the study database.
Example on how to create participant ID-Codes
- When managing multiple studies, define a prefix to easily identify the study (e.g. TGF)
- In multicentre studies, define a different code for each study site (e.g. S1, S2, S3, ....)
- Add participant inlusion number (e.g. 01, 02, 03, …)
- Separate ID-digits using a symbol (e.g. dash (-) or underscore (_))
- Example participant ID-Code: Study_Site_Participant = TGF-2-05
A coding system can also be predefined in the CDMS of the study.
Encrypted data is information that is rendered unreadable to anyone except to a defined group of individuals. The process includes to:
- Pass the data through a cipher, or a secret disguised way of writing (e.g. an algorithm that encodes data according to a key)
- Only individuals that possess the key on how to decrypt the data can read its content
Where can I get help?
Your local CTU↧ can support you with experienced staff regarding this topic
Basel, Departement Klinische Forschung, CTU, dkf.unibas.ch
Lugano, Clinical Trials Unit, CTU-EOC, www.ctueoc.ch
Bern, Clinical Trials Unit, CTU, www.ctu.unibe.ch
Geneva, Clinical Research Center, CRC, crc.hug.ch
Lausanne, Clinical Research Center, CRC, www.chuv.ch
St. Gallen, Clinical Trials Unit, CTU, www.kssg.ch
Zürich, Clinical Trials Center, CTC, www.usz.ch
External Links
Swissethics –see in particular
- Topics /Other Topics / Coding of trial subjects accepted by swissethics
FADP – Federal Act on Data Protection
GCDMP – see in particular
- Chapter “Data Privacy”
SCTO Regulatory Affairs – see in particular
- RAW Issue 1, April 2019, Essential information on data protection
References
ICH GCP E6(R2) – see in particular guidelines
- 2.11 Confidentiality of records
- 4.9 Records and reports
- 5.5 Trial management, data handling, and record-keeping
Swiss Law
HRA – see in particular articles
- Art. 3 Definition of coded and anonymised health related data and biological material
- Art. 56 Transparency and data protection
HRO – see in particular articles
- Art. 4 paragraph 1 letter d Data security and data protection
- Art. 25 Anonymisation of health-related personal data and biological material
- Art. 26 Coding of health-related personal data and biological material
ClinO – see in particular article
- Art. 6 paragraph 1 letter c Data security and data protection
ClinO-MD – see in particular article
- Art. 5 paragraph 1 letter d Data security and data protection