In:
PLOS Digital Health, Public Library of Science (PLoS), Vol. 1, No. 8 ( 2022-8-24), p. e0000027-
Kurzfassung:
Data sharing has enormous potential to accelerate and improve the accuracy of research, strengthen collaborations, and restore trust in the clinical research enterprise. Nevertheless, there remains reluctancy to openly share raw data sets, in part due to concerns regarding research participant confidentiality and privacy. Statistical data de-identification is an approach that can be used to preserve privacy and facilitate open data sharing. We have proposed a standardized framework for the de-identification of data generated from cohort studies in children in a low-and-middle income country. We applied a standardized de-identification framework to a data sets comprised of 241 health related variables collected from a cohort of 1750 children with acute infections from Jinja Regional Referral Hospital in Eastern Uganda. Variables were labeled as direct and quasi-identifiers based on conditions of replicability, distinguishability, and knowability with consensus from two independent evaluators. Direct identifiers were removed from the data sets, while a statistical risk-based de-identification approach using the k-anonymity model was applied to quasi-identifiers. Qualitative assessment of the level of privacy invasion associated with data set disclosure was used to determine an acceptable re-identification risk threshold, and corresponding k-anonymity requirement. A de-identification model using generalization, followed by suppression was applied using a logical stepwise approach to achieve k-anonymity. The utility of the de-identified data was demonstrated using a typical clinical regression example. The de-identified data sets was published on the Pediatric Sepsis Data CoLaboratory Dataverse which provides moderated data access. Researchers are faced with many challenges when providing access to clinical data. We provide a standardized de-identification framework that can be adapted and refined based on specific context and risks. This process will be combined with moderated access to foster coordination and collaboration in the clinical research community.
Materialart:
Online-Ressource
ISSN:
2767-3170
DOI:
10.1371/journal.pdig.0000027
DOI:
10.1371/journal.pdig.0000027.g001
DOI:
10.1371/journal.pdig.0000027.g002
DOI:
10.1371/journal.pdig.0000027.g003
DOI:
10.1371/journal.pdig.0000027.t001
DOI:
10.1371/journal.pdig.0000027.t002
DOI:
10.1371/journal.pdig.0000027.t003
DOI:
10.1371/journal.pdig.0000027.t004
DOI:
10.1371/journal.pdig.0000027.t005
DOI:
10.1371/journal.pdig.0000027.t006
DOI:
10.1371/journal.pdig.0000027.t007
DOI:
10.1371/journal.pdig.0000027.t008
DOI:
10.1371/journal.pdig.0000027.t009
DOI:
10.1371/journal.pdig.0000027.s001
DOI:
10.1371/journal.pdig.0000027.s002
DOI:
10.1371/journal.pdig.0000027.s003
DOI:
10.1371/journal.pdig.0000027.s004
DOI:
10.1371/journal.pdig.0000027.s005
DOI:
10.1371/journal.pdig.0000027.r001
DOI:
10.1371/journal.pdig.0000027.r002
DOI:
10.1371/journal.pdig.0000027.r003
Sprache:
Englisch
Verlag:
Public Library of Science (PLoS)
Publikationsdatum:
2022
ZDB Id:
3106944-7
Permalink