Researchers tested 11 generative architectures across nine healthcare datasets to evaluate synthetic tabular data quality. The study establishes a rigorous protocol for measuring fidelity, privacy, and utility. These benchmarks expose gaps in how current models preserve complex statistical dependencies. Practitioners can now use these metrics to validate synthetic data before clinical deployment.