Collaboration Details

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Title of Collaborative Activity:

federated learning across Health Information Exchanges (HIE)

Description of Collaborative Activity:

In cooperation with the Nebraska Health Information Initiative (NEHII) and the National Cancer Institute (NCI), NIH launched a pilot program earlier this year that uses a machine learning concept known as federated learning that could leverage existing HIE data while ensuring privacy. Federated learning is a machine learning technique that shares an analytical model between different groups, allowing them to analyze their own data – and share those results – without needing to share the actual raw data. The pilot aimed to expand clinical insights regarding COVID-19 using the existing ways health data are stored and protected in the US. In our pilot, each organization connected to a central cloud ecosystem known as the Multi-state Federated Architecture for Shared Analytics, better known as MuFASA.

Type of Collaborative Activity:

Committee, Advisory Group, or Work Group

Year the Collaborative Activity Originated:


NIH Participating Institutes/Centers/Office of the Director:


HHS Agency Collaborators on this Activity: