Pseudonymization and anonymization of data: what you need to know

Pseudonymization and anonymization of data are among the most common measures. They enable hospitals, for example, to share data with service providers or make data accessible for medical research, while protecting patient safety. Let's take a look at the difference.

The General Data Protection RegulationGDPR) recommends, depending on the sensitivity of health data, that security measures be implemented. 

Pseudonymization and anonymization of data are among the most common measures.

These enable hospitals, for example, to share data with service providers or make data accessible for medical research, while protecting patient safety.

But what exactly is meant by pseudonymization and anonymization of data? That's what we're going to decipher in this article on these data security measures.

What is data anonymization (or encryption)?

Take blood test results, for example. Deleting directly identifying information, such as names, social security numbers and addresses, is not enough to guarantee complete anonymization. Elements such as age, sex, date of birth or geographical information can still be re-identified using external data.

To be effective, anonymization must be irreversible, preventing any possibility of restoring identifying information.

This involves the use of various techniques: counters, random number generators, hash functions, etc.

Once the data has been processed, it cannot be returned to its original state.

This is one of the most important consequences of, and a major difference from, pseudonymization. While this process desensitizes confidential data by transforming it, it is still usable.

The resulting database can be used for medical research, in particular to identify correlations. People's data are thus no longer subject to the GDPR, nor to the Data retention retention period. The personal nature of the data has been lost. In the event of a data breach, the impact is less, as is the potential penalty.

Use and challenges of data anonymization in medical health research

📋 In the context of medical research, data anonymization is an essential step in preserving the integrity of information while making it impossible to identify the individuals concerned. However, this complex process requires careful assessment by a legal expert to ensure strict compliance with GDPR requirements.

Ultimately, the anonymization of healthcare data has become a major challenge, requiring a rigorous approach and appropriate precautions to guarantee the protection of sensitive information while complying with confidentiality standards.

This practice is also known as hashing or encryption . A private company may use it, for example, to allow patient data to be "re-used" for medical research, particularly if there are gaps in patient consent.

Definition: what is pseudonymization of personal data?

🔥 Data pseudonymization is a personal data processing process designed to prevent direct identification. Unlike anonymization, pseudonymization does not completely remove the possibility of identification, but makes this task considerably more complex.

This process relies on the use of a secure correspondence table, recording the relationship between direct identifiers and pseudonyms. pseudonyms will be created. This is part of good practice in securing personal data.

For example, pseudonymization occurs when personal data must be shared outside a hospital. This is particularly the case for decision-support tools used by doctors (diagnosis, treatment, etc.). The data leaves the hospital to be processed, then returns to the hospital.

This is a key issue for collaboration, while preserving the protection and security of personal data. In this way, the usefulness of the data is preserved, as it is returned to its original form. The stakes are high. The aim is to ensure the protection of personal information, while avoiding hashing or encryption, which does not allow you to go back and retrieve the original data.

Pseudonymization helps reduce the risks associated with data processing by restricting access to direct identifiers and guaranteeing the confidentiality of sensitive information. This is why pseudonymization is so important for protecting privacy and securing health data and personal identity.

According to the CNIL (National Commission for Information Technology and Civil Liberties), " Data anonymization solutions are essential today for many players wishing to make the most of the information they hold. ".

However, it is important not to confuse anonymization with pseudonymization. Pseudonymization is not an anonymization method. The pseudonymization process is reversible, unlike anonymization, which is not.

Discover the specific issues and important actions to take in the GDPR practical guide dedicated to the healthcare sector

In September 2024, cegedim santé was convicted of "only" pseudonymizing data and not anonymizing patient data collected within its software. As the risk of being able to re-identify patients was too great, the company was fined €800,000. To date, this decision has set a precedent on the subject.