10.20381/ruor-5857
Hu, Jun
Privacy-Preserving Data Integration in Public Health Surveillance
Université d'Ottawa / University of Ottawa
2011
Privacy
Security
Data Integration
Business to Business
B2B
Record Linkage
De-identification
Public Health Surveillance
Identity Linking
Université d'Ottawa / University of Ottawa
Université d'Ottawa / University of Ottawa
2011-05-16
2012-05-16
2011
2011
en
Thesis
http://hdl.handle.net/10393/19994
With widespread use of the Internet, data is often shared between organizations in B2B health care networks. Integrating data across all sources in a health care network would be useful to public health surveillance and provide a complete view of how the overall network is performing. Because of the lack of standardization for a common data model across organizations, matching identities between different locations in order to link and aggregate records is difficult. Moreover, privacy legislation controls the use of personal information, and health care data is very sensitive in nature so the protection of data privacy and prevention of personal health information leaks is more important than ever. Throughout the process of integrating data sets from different organizations, consent (explicitly or implicitly) and/or permission to use must be in place, data sets must be de-identified, and identity must be protected. Furthermore, one must ensure that combining data sets from different data sources into a single consolidated data set does not create data that may be potentially re-identified even when only summary data records are created. In this thesis, we propose new privacy preserving data integration protocols for public health surveillance, identify a set of privacy preserving data integration patterns, and propose a supporting framework that combines a methodology and architecture with which to implement these protocols in practice. Our work is validated with two real world case studies that were developed in partnership with two different public health surveillance organizations.