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Sharing Anonymized and Functionally Effective (SAFE) ...
appliedclinicaltrialsonline.com
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Recipient Trust: An assessment of the data release context also requires that one consider the degree to which recipients of data are known, trusted, and subject to enforceable terms of use that deter or prevent actions that would increase the likelihood of re-identification. Enforceability refers to the sponsor’s ability to impose financial and/or reputational consequences, through legal action, loss of funding, or otherwise, for non-compliance (eg, through a legally enforceable data sharing contract). “To standardize and achieve a common, defensible rating, these contextual factors need to be evaluated consistently.” Evaluating use
Recipient Trust: An assessment of the data release context also requires that one consider the degree to which recipients of data are known, trusted, and subject to enforceable terms of use that deter or prevent actions that would increase the likelihood of re-identification. Enforceability refers to the sponsor’s ability to impose financial and/or reputational consequences, through legal action, loss of funding, or otherwise, for non-compliance (eg, through a legally enforceable data sharing contract). “To standardize and achieve a common, defensible rating, these contextual factors need to be evaluated consistently.” Evaluating use
In summary, the proposed data transformation rating is from 0 to 5, where 0 is the raw data and the scale from 1 to 5 reflects varying degrees of data transformation proportional to the type of use and contextual controls in place to protect data from re-identification opportunities. Consistently evaluating the uses of anonymized data and the anonymization context can speed and standardize anonymization processes applied across sponsors and enforce a common baseline for privacy while maximizing data utility and analytic benefits. Figure 6 summarizes the data transformation ratings from 0 to 5. “Once data are transformed as part of the anonymization process, sponsors should retain reports detailing the anonymization approach taken and associated justifications for auditability.” To illustrate the concept of the SAFE Data Standard, we applied the data tolerances from level 1 to 5 to simulate the transformation impacts on indirectly identifying data from a clinical study. (See Figure 7 below.) For clarity, directly identifying information or unique identifiers are masked or removed (for instance, such subject IDs are replaced with pseudonyms and site IDs are removed) and non-identifying information, such as a blood glucose reading (which can change frequently), is preserved during the anonymization process.