We propose that blockchain technology complemented by secure computation methods can foster implementation of a learning healthcare system (LHCS) by minimizing upfront patient-facing compromises with unsurpassed data security and privacy, and by optimizing the system’s fulfillment of its obligations to respect patients through transparency, engagement, and accountability. We demonstrate how a blockchain-enabled LHCS could foster patient willingness to contribute to learning by providing desired security and control over health data. In addition, secure computation methods could enable meta-analysis without exposing individual-level data, thus allowing the system to protect patients’ privacy while simultaneously learning from their data. The transparency and immutability of blockchain ledgers would also support the public’s trust in the system by allowing patients to audit and oversee which of their data are used, how they are used, and by whom. Furthermore, blockchain communities are community-governed peer-to-peer networks in which sharing builds mutually beneficial value, offering a model for engaging patients as LHCS stakeholders. Smart contracts could be used to ensure accountability of the system by embedding feedback mechanisms by which patients directly and automatically realize benefits of sharing their data.

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.