Indirect identifiers: Overview, definition, and example
What are indirect identifiers?
Indirect identifiers refer to pieces of information that, on their own, may not directly identify an individual but can be used in combination with other data to potentially reveal their identity. These identifiers typically include demographic, geographic, or behavioral information such as age, gender, zip code, or purchasing history. While these pieces of data may not directly point to a specific person, when combined with other information, they can narrow down the pool of possible individuals or, in some cases, uniquely identify a person. Indirect identifiers are often used in data privacy and security contexts to assess the risk of re-identification of anonymous or de-identified data.
For example, knowing a person’s birth date and city of residence might not directly identify them, but when combined with other data, such as their occupation or a social media profile, it could.
Why are indirect identifiers important?
Indirect identifiers are important because they represent a potential privacy risk, especially in data protection and anonymization efforts. Even if a piece of information does not directly identify an individual, it can still be used to infer identity when combined with other data. Understanding and managing indirect identifiers is essential for maintaining privacy and ensuring compliance with data protection regulations, such as the General Data Protection Regulation (GDPR) and the Health Insurance Portability and Accountability Act (HIPAA). Effective handling of indirect identifiers helps prevent privacy breaches and the unauthorized re-identification of individuals from anonymized datasets.
Understanding indirect identifiers through an example
Imagine a company collects data about its customers, including their age, gender, and postal code. On their own, these data points may not specifically identify a customer, as many people can share the same age, gender, and live in the same postal code. However, if this data is combined with other information—such as purchasing habits or social media activity—it may be possible to identify the customer. In this case, the age, gender, and postal code serve as indirect identifiers that could contribute to identifying the individual.
In another example, a hospital collects data on patient medical conditions, treatments, and zip codes. While the zip code alone is not enough to identify a specific patient, if it is combined with other medical details, it may narrow down the population to a smaller group, potentially leading to the identification of a specific individual. This is why indirect identifiers need to be handled with care when dealing with personal or sensitive information.
An example of an indirect identifiers clause
Here’s how a clause related to indirect identifiers might appear in a data privacy or contract agreement:
“The Parties agree to ensure that any indirect identifiers, including but not limited to age, location, and demographic information, shall be anonymized or aggregated in a manner that prevents the re-identification of individuals. The Parties will implement reasonable measures to protect against the misuse of indirect identifiers in accordance with applicable data privacy regulations.”
Conclusion
Indirect identifiers are crucial in the context of data privacy and security. While they may not directly identify an individual, they can contribute to identifying someone when combined with other data. Managing indirect identifiers effectively helps prevent privacy risks, ensuring compliance with data protection laws and safeguarding personal information. Being aware of the potential for re-identification is essential for organizations that handle sensitive or personal data.
This article contains general legal information and does not contain legal advice. Cobrief is not a law firm or a substitute for an attorney or law firm. The law is complex and changes often. For legal advice, please ask a lawyer.