Privacy-by-Design Environments for Large-Scale Health Research and Federated Learning from Data

Peng Zhang; Maged N Kamel Boulos

doi:10.3390/ijerph191911876

Privacy-by-Design Environments for Large-Scale Health Research and Federated Learning from Data

Int J Environ Res Public Health. 2022 Sep 20;19(19):11876. doi: 10.3390/ijerph191911876.

Authors

Peng Zhang¹, Maged N Kamel Boulos²

Affiliations

¹ Data Science Institute & Department of Computer Science, Vanderbilt University, Nashville, TN 37240, USA.
² Faculdade de Medicina, Universidade de Lisboa, 1649-028 Lisbon, Portugal.

Abstract

This article offers a brief overview of 'privacy-by-design (or data-protection-by-design) research environments', namely Trusted Research Environments (TREs, most commonly used in the United Kingdom) and Personal Health Trains (PHTs, most commonly used in mainland Europe). These secure environments are designed to enable the safe analysis of multiple, linked (and often big) data sources, including sensitive personal data and data owned by, and distributed across, different institutions. They take data protection and privacy requirements into account from the very start (conception phase, during system design) rather than as an afterthought or 'patch' implemented at a later stage on top of an existing environment. TREs and PHTs are becoming increasingly important for conducting large-scale privacy-preserving health research and for enabling federated learning and discoveries from big healthcare datasets. The paper also presents select examples of successful TRE and PHT implementations and of large-scale studies that used them.

Keywords: personal health trains; privacy by design; trusted research environments.

Publication types

Review
Research Support, Non-U.S. Gov't

MeSH terms

Computer Security*
Delivery of Health Care
Europe
Information Storage and Retrieval
Privacy*

Grants and funding

This research was funded by the European Union’s Horizon 2020 programme under grant agreement no 952377 for the ‘Informatics and Statistical Tools for Advancement of Research Success’ project.