Accelerating Patient-Centered Outcomes Research through Synthetic Health Data Generation

Real world health data are critical for Patient-Centered Outcomes Research (PCOR). However, it’s often difficult, expensive, and time consuming for researchers to access real-world clinical health data because of privacy concerns, security restrictions, and usage issues. Although PCOR researchers, health information technology developers, and informaticists often depend on anonymized or de-identified clinical health data for testing theories, data models, algorithms, and prototype innovations, re-identification of anonymized data remains a possible security risk. Synthetic health data can provide a no-risk data source to complement research and support testing needs until real clinical health data are available.

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