Contextual Anonymization for Secondary Use of Big Data in Biomedical Research: Proposal for an Anonymization Matrix.

ABSTRACT: BACKGROUND:The current law on anonymization sets the same standard across all situations, which poses a problem for biomedical research. OBJECTIVE:We propose a matrix for setting different standards, which is responsive to context and public expectations. METHODS:The law and ethics applicable to anonymization were reviewed in a scoping study. Social science on public attitudes and research on technical methods of anonymization were applied to formulate a matrix. RESULTS:The matrix adjusts anonymization standards according to the sensitivity of the data and the safety of the place, people, and projects involved. CONCLUSIONS:The matrix offers a tool with context-specific standards for anonymization in data research.

SUBMITTER: Rumbold J 

PROVIDER: S-EPMC6284146 | biostudies-literature | 2018 Nov

REPOSITORIES: biostudies-literature