Open Data Training Video: A proposed data de-identification framework for clinical research

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Description:
Objective(s): 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. We provide an instructional video to describe a standardized de-identification framework that can be adapted and refined based on specific context and risks.

Data Description: Training video, presentation slides.

Related Resources: The data de-identification algorithm, dataset, and data dictionary that correspond with this training video are available through the Smart Triage sub-Dataverse.
NOTE for restricted files: If you are not yet a CoLab member, please complete our membership application survey to gain access to restricted files within 2 business days.
Some files may remain restricted to CoLab members. These files are deemed more sensitive by the file owner and are meant to be shared on a case-by-case basis. Please contact the CoLab coordinator on this page under "collaborate with the pediatric sepsis colab."
Auteur(s) :
Mawji, Alishah

Mawji, Alishah

University of British Columbia
, Longstaff, Holly

Longstaff, Holly

University of British Columbia
, Trawin, Jessica

Trawin, Jessica

University of British Columbia
, Komugisha, Clare

Komugisha, Clare

University of British Columbia
, Novakowski, Stefanie K.

Novakowski, Stefanie K.

University of British Columbia
, Wiens, Matt

Wiens, Matt

University of British Columbia
, Akech, Samuel

Akech, Samuel

KEMRI - Wellcome Trust Programme
, Tagoola, Abner

Tagoola, Abner

Jinja Regional Referral Hospital
, Kissoon, Niranjan

Kissoon, Niranjan

University of British Columbia
et Ansermino, Mark J.

Ansermino, Mark J.

University of British Columbia
Contributor(s):
CoLab Coordinator et Pallot , Katija
Dépôt source:
UBC Dataverse
Series:
Pediatric Sepsis Data CoLab // Open Data Resources
Éditeur(s):
Borealis
Accès:
Public
License:
CC BY-NC-SA 4.0
URL:
https://doi.org/10.5683/SP3/7XYZVC
Date de publication:
2023-03-15
Sujets (en):
Medicine, Health and Life Sciences
Mots-clés (en):
Algorithms, Infant, Sepsis, Child, Infection, Data science, Data management, Medical informatics, Data curation, Big data, Common data elements, Data aggregation, Pediatric, et LCSH
Identificateur:
https://doi.org/10.5683/SP3/7XYZVC

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Référence bibliographique

Citation selon les normes APA:
Open Data Training Video: A proposed data de-identification framework for clinical research. (2023). [Data set]. UBC Dataverse. https://doi.org/10.5683/SP3/7XYZVC
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