Privacy-Preserving Analytic and Data-Sharing Methods for Clinical and Patient-Powered Data Networks [Methods Study], California, Colorado, and Washington, 2014-2018

Sometimes a study can get better results using data from different sites. In these cases, researchers may want to share patient data, including personal and private information such as dates of birth and addresses. However, researchers may not want to share data across sites because of worries about patient privacy. Some statistical methods can change patients' sensitive individual data into summary data that hides individuals' personal information. These privacy-protecting methods, or PPMs, make it safe to share data across sites. But researchers don't know if PPMs produce accurate results.
In this study, the research team compared combinations of PPMs with methods that use patients' individual data.
To access the methods, software, and R package, please visit the distributed GitHub.