Summary of article from Health IT Analytics, by Shania Kennedy:
Healthcare data, while valuable for improved outcomes, faces challenges including data quality, patient privacy, and HIPAA compliance. Synthetic data, artificially generated information that mimics real-world data (RWD), offers a promising solution by maintaining statistical properties of RWD without containing personally identifiable information. Synthetic data provides privacy preservation, prevents data re-identification, and supports algorithm training. However, it also presents challenges, including potential data quality issues, bias, and AI model collapse. While synthetic data generators need improvement and standardized quality assessment, they are being increasingly utilized for various healthcare projects.