PRIVACY-PROTECTING ANALYTIC AND DATA-SHARING METHODS

 

Our research focuses on developing and applying cutting-edge analytic and data-sharing methods that integrate epidemiology, biostatistics, data science, and informatics to improve the validity, feasibility, and efficiency of multi-center studies, particularly in distributed data network studies that leverage routinely collected electronic health data.

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Many of these methods support robust multivariable-adjusted statistical analysis without the need to share individual-level data, thereby providing better protection for patient privacy and confidentiality in multi-database studies.

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Our guiding principles are:

 

Sending analysis to the data

 

Getting more (info) by asking for less (data)

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