What is the Origin of Re-Identification Potential?

This concept arose from computational science and privacy research, demonstrating empirically that even with the removal of direct identifiers, a small number of demographic or unique physiological attributes can be sufficient to uniquely pinpoint an individual within a large dataset. The term quantifies the inherent vulnerability of anonymized data to a linkage attack.

What is the Mechanism of Re-Identification Potential?

The potential for re-identification is rigorously assessed by measuring the statistical uniqueness of the combination of quasi-identifiers—such as age, gender, geographic location, and specific hormonal ranges—within a given dataset. Techniques to effectively reduce this risk include generalization, where precise values are replaced with broader ranges, or suppression, where highly unique data points are entirely removed, thereby lowering the probability of a successful linkage attack.

Re-Identification Potential ∞ Area

Re-Identification Potential

Meaning

Re-Identification Potential refers to the measurable statistical and technical risk that a seemingly anonymous or de-identified set of health data, including comprehensive hormonal or metabolic profiles, could be successfully linked back to the specific individual from whom it originated. This risk is significantly amplified when complex, unique data points, such such as a rare genetic variant or a highly specific combination of clinical markers, are present, allowing for correlation with publicly available information. Understanding and actively mitigating this potential is a critical ethical and technical challenge in securely sharing clinical data for research purposes.