Using High-Quality Synthetic Data to Support Rapid Innovation: VHA Innovation | MDClone

The Veterans Health Administration, serving 9 million veterans across 1,298 facilities, had patient data fragmented across systems, making it hard for non-technical staff to use for research while maintaining privacy compliance. MDClone's synthetic-data engine aggregated the fragmented data into a longitudinal, de-identified database for self-service exploration without IT or lengthy IRB reviews. VHA used it to build ML models predicting and reducing heart-failure readmissions, and to analyze Veterans Crisis Line data as part of an initiative to "reduce Veteran suicide by at least 10%," while also validating vendor technologies (e.g., with Equideum) under an "any question, any person, any time" access model.

MDClone is a healthcare synthetic-data platform that converts real EHR data into privacy-safe synthetic datasets for self-service research and analytics.

This sits in the Design & Stress-Test stage of the AI use-case lifecycle: Named examples from the tools pharma teams use to scope, prototype and benchmark an AI use case before committing to build it — data-catalog, sandbox and evaluation platforms.