Amida is pleased to announce the third release of its Data Reconciliation Engine (DRE). The DRE is a Blue Button-branded software component that supports the aims of the Blue Button Initiative, a nationwide public-private effort that enables patients and consumers to gain easy access to their own health information. The Blue Button Initiative has evolved into a nationwide public-private effort that offers more than half of all Americans access to health information from diverse sources.

The DRE is the first production-ready, format-agnostic open source health record interface in the health IT market. The third release extends the kinds of formats that the DRE can ingest, and now includes HL7 labs ingestion via MLLP, patient identification and matching (for HL7 data), and updates to use refactored Blue Button libraries

“In our continuing efforts to improve patient access, we are happy to announce that the DRE can ingest even more formats,” said Amida’s CEO Peter L. Levin. Levin is the former chief technology officer at the Department of Veterans Affairs, where he spearheaded the Blue Button Initiative.

Amida developed the DRE to help place patients at the center of their health information. The DRE enables data holders like clinicians, insurers, pharmacies, and diagnostic laboratories to share patient records, regardless of the source or provenance of the information, and under patients’ complete control. They have posted a 90-second video overview of the DRE here: http://bit.ly/amida-dre-video.

"Innovation continues to be driven by the open source ecosystem,” said Jim Whitehurst, president and CEO of Red Hat, the industry leader in open source software. "As we see more businesses move away from closed systems and embrace open source, we're finding they value the operational flexibility that open source provides. I applaud Amida on their work on the DRE and their effort to bring innovation to the healthcare industry through open systems."

The DRE compiles information from multiple sources into a universal Master Health Record that patients can securely store anywhere they like. It allows patients and their authorized health service providers to identify and correct errors, as well as manually reconcile partial matches via a simple web interface. The component is built in Node.js and can be integrated into any stack; the reference implementation uses MongoDB document store.