Completed Projects

Privacy-Preserving Analytic and Data-Sharing Methods for Clinical and Patient-Powered Data Networks
 
Funding source: Patient-Centered Outcomes Research Institute (ME-1403-11305) [Link]
Study period: 2015-2018
Principal Investigator: Darren Toh
Objectives: Assess privacy-preserving analytic and data-sharing methods that leverage confounder summary scores for multi-center patient-centered outcomes research studies with horizontally partitioned data, a data environment in which different databases include information about different individuals.
Utilizing Data from Various Data Partners in a Distributed Manner
 
Funding source: Office of the Assistant Secretary for Planning and Evaluation & Food and Drug Administration (HHS22301006T) [Link]
Study period: 2015-2018
Principal Investigator: Darren Toh
Objectives: Develop the capability of conducting automatable and secure distributed regression analysis in distributed networks with horizontally partitioned data, a data environment where information about an individual is available in two or more data sources.
PCORnet Bariatric Study
 
Funding source: Patient-Centered Outcomes Research Institute (OBS-1505-30683) [Link]
Study period: 2016-2018
Lead Principal Investigator: David Arterburn
Co-Investigator: Darren Toh
Objectives: Estimate the 1-, 3-, and 5-year benefits and risks of the three most common bariatric procedures within PCORnet Clinical Data Research Networks.
PCORnet Antibiotics and Childhood Growth Study
 
Funding source: Patient-Centered Outcomes Research Institute (OBS-1505-30699) [Link]
Study period: 2016-2018
Lead Principal Investigator: Jason Block
Co-Investigator: Darren Toh, Jessica Young
Objectives: Assess the effects of antibiotic use in the first two years of life on growth trajectories, BMI, and obesity in mid-childhood.
Privacy-Preserving Distributed Analysis of Biomedical Big Data
 
Funding source: National Institutes of Health (U01EB023683) [Link 1][Link 2]
Study period: 2016-2020
Principal Investigator: Darren Toh 
Objectives: Develop a new capability to perform distributed regression in vertically partitioned data, a data environment where information about an individual is available in two or more data sources. 
Replicating Randomized-Controlled Trials with Real-World Data
 
Funding source: OptumLabs
Study period: 2019-2020
Principal Investigators: Darren Toh, Xiaojuan Li 
Objectives: Replicate two randomized controlled trials using the electronic health data available in the OptumLabs Data Warehouse. 
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Department of Population Medicine

Harvard Medical School and Harvard Pilgrim Health Care Institute

401 Park Drive, Suite 401 East, Boston, MA 02215