Multivariable confounding adjustment in distributed data networks without sharing of patient‐level data

It is increasingly necessary to analyze data from multiple sources when conducting public health safety surveillance or comparative effectiveness research. However, security, privacy, proprietary, and legal concerns often reduce data holders' willingness to share highly granular information. We describe and compare two approaches that do not require sharing of patient‐level information to adjust for confounding in multi‐site studies.

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