fhir-synth

What problem does it solve?

This Skill addresses the need for creating realistic synthetic healthcare data efficiently, enabling testing, analysis, and development without compromising patient privacy.

Core Features & Use Cases

• Data Generation from Prompts: Converts natural language descriptions into synthetic FHIR-compliant datasets, including patients, conditions, and observations.
• Programmatic Workflow: Supports complex scenarios such as batch generation, version selection (R4B or STU3), and adding follow-up encounters.
• Use Case: A healthcare developer needs to simulate a patient population with specific attributes to test an EMR system or run analysis, and can generate such data instantly by describing the scenario in plain English.

Quick Start

Describe your synthetic data needs, such as "generate 10 diabetic patients," and the system will produce the data accordingly.