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K-Anonymity in Health Metrics

Meaning

K-Anonymity in Health Metrics is a foundational privacy model applied to health datasets, stipulating that for any combination of non-direct identifying attributes, known as quasi-identifiers, each record must be statistically indistinguishable from at least k-1 other records within the dataset. When rigorously applied to sensitive hormonal metrics, this model ensures that if an adversary knows a patient’s age range and generalized zip code, they cannot isolate that patient’s specific sensitive data, such as their precise serum DHEA-S level, from a cohort of at least k individuals. Achieving a sufficiently large k value is a crucial, auditable step for protecting confidentiality in shared research data.