Validating Medical Codes in AI-Generated Synthea Modules

Synthea's 85 disease modules fail to reflect real-world medical diversity—synthetic cohorts show zero prevalence for common conditions affecting millions. When LLMs auto-generate custom disease modules, they hallucinate plausible but invalid medical codes (SNOMED-CT, LOINC, RxNorm), corrupting synthetic datasets. This workflow leverages public FHIR terminology servers to validate codes before generation, ensuring synthetic healthcare data maintains clinical accuracy.