Data De-Identification Process

How the Research data de-identification (removal of research participant’s/patients identifiers) is performed in research field via independent 3^rd party (Data Management Unit) so that the research data/images can be shared in de-identified manner to internal & international collaborators by following the HBRA/PDPA guidelines/appropriate data governing policies & guidelines.

How the de-identification process in SERI-SNEC was set-up?

The de-identification process and the workflow implemented in SNEC-SERI helps to render the research data non-identifiable to maintain the privacy and confidentiality of the patient’s/research participants.

Key Takeaways

• What are the key patient identifiers to be de-identified?
• Research consent – criteria for data de-identification
• The de-identification process/workflow
• Assigning of anonymised de-identification code to research data/images

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Bio

Sangeetha Nagarajan, Data Management | Singapore Eye Research Institute | Singapore

Sangeetha has built and leading the Data Management Unit in Singapore Eye Research Institute. Her key focus is to provide the best data management service to deliver the highest quality data with integrity for all clinical/research projects by following the best clinical data management practices/HBRA & PDPA guidelines.
She had conceptualized, developed and implemented electronic data capture systems and data de-identification process for SNEC-SERI; She is an active contributor in SingHealth to develop Research data governance policies/guidelines/ work processes. Her team work has been endorsed by MOH for following best data management practices according to PDPA guidelines. She had received Excellent Service and Performance Awards from SNEC/SERI. She has experience over 15 years of clinical/research data management emphasis in Ophthalmology. She is passionate and enthusiastic about technology and how it can be implemented to build efficiencies into the clinical research process by adopting digital transformation.