Data sharing and information exchange are playing critical roles in biomedical data science to improve quality of care, accelerate discovery, and promote meaningful secondary use of clinical data. But privacy is a big concern to the public. Existing distributed data analysis methods do not address the security and privacy issues in exchanging intermediary statistics and they cannot handle dynamic database updates very well. This project aims at designing and implementing differentially-private decentralized methods for dynamic data dissemination and analysis. We plan to use genomic and clinical data from both public domain and local institutions (UCSD and Emory) to carefully evaluate the feasibility and efficiency of our proposed new methods.

Public Health Relevance

A big challenge in biomedical information sharing is to maintain privacy, as inappropriate data handling can put patient's and their family members' sensitive personal information at risk. We will develop a privacy-preserving decentralized framework for dynamic data dissemination and analysis to support cross-institutional collaboration.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
5R01GM118609-02
Application #
9406496
Study Section
Biomedical Computing and Health Informatics Study Section (BCHI)
Program Officer
Gregurick, Susan
Project Start
2017-01-01
Project End
2020-12-31
Budget Start
2018-01-01
Budget End
2018-12-31
Support Year
2
Fiscal Year
2018
Total Cost
Indirect Cost
Name
University of California San Diego
Department
Internal Medicine/Medicine
Type
Schools of Medicine
DUNS #
804355790
City
La Jolla
State
CA
Country
United States
Zip Code
92093
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