Protecting Privacy and Facilitating Shared Access of Clinical and Genetic Data of Special Populations
Project Number7R01HL136835-05
Former Number5R01HL136835-04
Contact PI/Project LeaderOHNO-MACHADO, LUCILA
Awardee OrganizationYALE UNIVERSITY
Description
Abstract Text
PROJECT SUMMARY
The Strong Heart Study (SHS) is a multi-center, longitudinal resource designed to better understand
cardiovascular disease in American Indians, identify significant risk factors, promote new research and deliver
better health care. To achieve these goals, SHS data should be accessible to interested and qualified
researchers, while no harm is done to the study participants who contribute their data. Thus private information
in the data and the identity of the participants should be protected, and SHS tribal sovereignty and agreements
that include tribal review and approval of all SHS data use requests should be respected. Our study aims to
address these issues using advanced technologies and scientific computing toolkits to enable shared, but
protected, data access, as well as to understand the data sharing preferences of SHS participants. The first
aim is to develop an innovative, secure data-centric service to protect computation on SHS data according to
governance practices that are acceptable to participating SHS tribes, SHS investigators, and the NIH.
Specifically, we will build a system for secure analysis on protected data through a virtual private network, in
which only approved operations and outputs are permitted. The proposed framework will allow researchers to
easily and securely perform specific statistical analysis on SHS data and meta-analyses. The second aim is to
develop novel federated computing models to support the SHS Coordinating Center and Genetics Center to
analyze data in a distributed manner. The methods for achieving the second aim rely on new, practical
federated data analysis technology. For example, in the case of vertically partitioned data, different data from
the same SHS participants may be stored at different sites, such as genomic data and phenotype data that are
currently stored at the SHS Genetics Center and the SHS Coordinating Center, respectively. The third aim is to
understand the data sharing expectations and preferences of SHS participants to inform the implementation of
the data sharing models. This aim will be carried out through qualitative and quantitative methods, which
include the use of individual interviews and surveys of SHS participants.
Public Health Relevance Statement
PROJECT NARRATIVE
The proposed project aims to protect privacy and facilitate shared access of clinical and genetic data of special
populations. Specifically, UCSD investigators will work closely with Strong Heart Study (SHS) investigators to
investigate the implementation of a shared access model so that the data may be accessed, analyzed, and
results can be obtained at differently approved and summarized levels by different qualified investigators
without actually sharing the original participant-level data.
NIH Spending Category
No NIH Spending Category available.
Project Terms
AccelerationAddressAgreementAlgorithmsAmerican IndiansBiomedical ResearchCalibrationCardiovascular DiseasesCardiovascular systemChronic DiseaseClinicalClinical DataCodeCollaborationsCommunicationCommunitiesDataData AnalysesData ProtectionDiagnosticDisparity populationEmploymentEthicsEvaluationEventFactor AnalysisFeedbackFundingGeneticGenetic studyGenomeGenotypeGoalsGrainHealth SciencesHealthcareHeartIncidenceIndividualInsuranceInterviewIntuitionMeasuresMeta-AnalysisMethodsModelingMultivariate AnalysisNational Heart, Lung, and Blood InstituteOklahomaOutcomeOutcomes ResearchOutputParticipantPersonsPhenotypePoliciesPopulation GroupPrevalencePrivacyPrivatizationProceduresProcessQualifyingResearchResearch InstituteResearch PersonnelResourcesRiskRisk FactorsSecureServicesSiteSpecial PopulationStatistical Data InterpretationStructureSurveysSurvival AnalysisSystemSystems AnalysisTechnologyTexasTimeTribesUnderserved PopulationUnited States National Institutes of HealthUniversitiesVisualizationWorkanalytical methoddata accessdata de-identificationdata sharingdemographicsdesignexpectationfederated computingfederated dataformative assessmentgenomic dataimprovedinnovationinterestnoveloperationphenotypic datapreferenceprivacy preservationprivacy protectionscientific computingsocial implicationvirtualweb interfaceweb services
No Sub Projects information available for 7R01HL136835-05
Publications
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Outcomes
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