ONC Blockchain Challenge Winner: MIT’s Experimental Learning Proposal

Blockchain Healthcare Review Industry

Data privacy

As part of the President’s Precision Medicine Initiative (PMI), in August the Office of the National Coordinator for Health Information Technology (ONC) and the National Institute of Standards and Technology (NIST) began their “Blockchain Challenge.” The ONC challenge solicited proposals on how blockchain may be utilized to improve healthcare IT and to enable a “new era of clinical care through research, technology, and policies that empower patients, researchers, and providers to work together toward the development of individualized care.”

ONC Blockchain Challenge Winner

Of the more than 70 proposals received, 15 were selected as finalists. Among those selected was Blockchain and Health IT: Algorithms, Privacy, and DataProject, a whitepaper by less succinctly named PharmOrchard of MIT’s Experimental Learning “MIT FinTech: Future Commerce.”

MIT’s proposal explored threats PMI data’s security, confidentiality, integrity and availability and presented he OPAL/Enigma project3 as a strategy towards mitigating those challenges. The OPAL/Enigma project3 creates a peer-to-peer network based on highly optimized multi-party computation and secret-sharing via a permissioned blockchain that records and controls access through smart contracts and digital identities. OPAL thereby enabling complete privacy in analyzing jointly stored data, increasing interoperability. In sum, the OPAL/Enigma project3 uses blockchain technology to resolve the tension between the creation of a secure environment for stakeholder Electronic Health Information (EHI) and the necessity of efficiency in sharing that sensitive information. And, as a secure infrastructure that doesn’t sacrifice the ability of exchangeability of data, OPAL would be a potential tool providing:

  • resolution of infrastructural matters, such as time and cost related to the analysis, storage and manipulation of health information;
  • a better framework for precision medicine trials;
  • the development of more comparative trials;
  • a more cost-effective development of drugs; and
  • the development of more effective treatments to patients.

The proposal focuses on the OPAL system as a platform for the creation of accessible (yet confidential) databases of patient information at scale, and the ability to utilize information for expansive and nuanced adaptive clinical medical trials. However, it also notes that the system would, on an individual level, allow for a more holistic treatment of patients via a shared medical history.