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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.
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.
Our guiding principles are:
Sending analysis to the data
Getting more (info) by asking for less (data)
An introductory video about data sharing in multi-database studies
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