Filter By “Privacy, Security & Ethics”

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Inside Privacy Hub’s HIPAA Expert Determination Team: Fran Lane, Senior Data Scientist and Privacy Expert

Senior Data Scientist and Privacy Expert, Fran Lane, discusses her journey and the future of health data privacy. Get the inside track on HIPAA Expert Determination.

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Patient Privacy in the Age of Large Language Models

Explore privacy challenges of using large language models in healthcare research. Learn how to extract valuable insights while addressing bias, regulations, and public trust concerns.

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Inside Privacy Hub’s HIPAA Expert Determination Team: Patrick Baier, HIPAA Privacy Expert

HIPAA Privacy Expert, Patrick Baier, discusses his journey and the future of health data privacy. Get the inside track on HIPAA Expert Determination.

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Inside Privacy Hub’s HIPAA Expert Determination Team: Anca Ionescu, Senior Data Scientist

Privacy expert, Anca Ionescu, discusses her journey and the future of health data privacy. Get the inside track on HIPAA Expert Determination.

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What is Privacy-Preserving Record Linkage (PPRL) and Why Does It Matter?

PPRL, often known as tokenization or data linkage, protects patient privacy, enhances accuracy, and enables diverse insights. Learn how it benefits government agencies and researchers.

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Referential Data in Datavant Match

Referential data is exactly what it sounds like: a large body of data to which we can refer in the process of matching, a bridge between otherwise disjointed datasets.

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Top 5 Trends in the Healthcare Data Ecosystem

Explore the dynamic trends shaping the healthcare data landscape. From disease-specific clinical data to privacy-preserving collaborations, uncover the evolving ecosystem.

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Synthetic Data in Healthcare | Datavant

Synthetic data has the potential to be a critical technology in healthcare, as it enables representative patient data with inherent privacy protection. See more.

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Establishing a framework for privacy-preserving record linkage among electronic health record and administrative claims databases within PCORnet

The aim of this study was to determine whether a secure, privacy-preserving record linkage (PPRL) methodology can be implemented in a scalable manner for use in a large national clinical research network.

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