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For example, given prior knowledge of a few attendance dates it is easy to identify someone's data in a pseudonymized dataset by selecting only those people with that pattern of dates. This is an example of an inference attack. The weakness of pre-GDPR pseudonymized data to inference attacks is commonly overlooked.
De-identification is the process used to prevent someone's personal identity from being revealed. For example, data produced during human subject research might be de-identified to preserve the privacy of research participants. Biological data may be de-identified in order to comply with HIPAA regulations that define and stipulate patient ...
The two researchers de-anonymized some of the data by comparing it with non-anonymous IMDb (Internet Movie Database) users' movie ratings. Very little information from the database, it was found, was needed to identify the subscriber. [3] In the resulting research paper, there were startling revelations of how easy it is to re-identify Netflix ...
Names; All geographical identifiers smaller than a state, except for the initial three digits of a zip code if, according to the current publicly available data from the U.S. Bureau of the Census: the geographic unit formed by combining all zip codes with the same three initial digits contains more than 20,000 people; the initial three digits of a zip code for all such geographic units ...
The Clinical Care Classification (CCC) System is a standardized, coded nursing terminology that identifies the discrete elements of nursing practice. The CCC provides a unique framework and coding structure. Used for documenting the plan of care; following the nursing process in all health care settings. [1]
Planning & delivery of care; Evaluation of results for each patient & adjustment of the care plan; Evaluation of overall program effectiveness & adjustment of the program [4] In the context of a health insurer or health plan it is defined as: [5] A method of managing the provision of health care to members with high-cost medical conditions.
The Emergency Severity Index (ESI) is a five-level emergency department triage algorithm, initially developed in 1998 by emergency physicians Richard Wurez and David Eitel. [1] It was previously maintained by the Agency for Healthcare Research and Quality (AHRQ) but is currently maintained by the Emergency Nurses Association (ENA).
Level 3 Security (L3S) is referred to as the most in-depth and highest security level technology for securing identities and identity documents. This focuses around the protection of the one True Identity of each individual and thereby, automatically protecting the related identity documents (conversely, in L1S and L2S schemas, the focus is to ...