Agent skill · Testing & QA

generating-synthea-data

Generates synthetic but realistic patient records (FHIR R4 bundles, C-CDA documents, CSV) with MITRE Synthea for development, CI fixtures, demos, and leakage-gate test sets — zero real PHI. Use when you need safe, shareable test data for an OpenMed pipeline, reproducible fixtures for tests, or a held-out set for de-identification leakage gates, instead of touching real clinical data. Synthea output feeds the FHIR/C-CDA ingestion skills and openmed.eval. Trigger keywords: Synthea, synthetic data, fake patients, test fixtures, demo data, FHIR bundle generator, synthetic EHR, no PHI.

maziyarpanahigithub.com/maziyarpanahiGitHub ↗
claude-codeApache-2.0
Install
npx skills add maziyarpanahi/openmed --skill generating-synthea-data --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 1
SKILL.md size: 6 KB
Bundled scripts: none
Version: 1.0
Path: skills/generating-synthea-data/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 4,851
Language: Python
Read our review of the source →

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Generating Synthetic Patient Data with Synthea You cannot develop, test, or demo a clinical NLP pipeline on real PHI without a mountain of governance — and you shouldn't have to. **Synthea** (MITRE's Synthetic Patient Population Simulator) generates statistically realistic, fully synthetic patients: complete longitudinal records as FHIR R4 bundles, C-CDA documents, and flat CSV, with **zero real-PHI risk**. Use it for OpenMed dev fixtures, CI, demos, and — importantly — as **held-out test sets for de-identification leakage gates**, where you need known-synthetic "PHI" to measure recall. ## When to use - Building or demoing an OpenMed ingestion pipeline (FHIR, C-CDA) and need shareable input that is safe to commit and pass around. - Creating deterministic CI fixtures so tests don't depend on protected data. - Producing a leakage-gate test corpus: synthetic notes with *known* fake identifiers, so you can score whether `openmed.deidentify` removed them all. - Teaching/onboarding without a data-use agreement. ## Quick start Synthea is a Java tool. Generate a small population in multiple formats: ```bash # Requires Java 11+. Clone and build once. git clone https://github.com/synthetic

What's inside
Steps it walks through
  1. When to use
  2. Quick start
  3. Workflow
  4. Hand-off to / from OpenMed
  5. Edge cases & gotchas
  6. Standards & references
Commands it runs
Requires Java 11+. Clone and build once.
git clone https://github.com/synthetichealth/synthea && cd synthea
Generate 50 patients in Massachusetts as FHIR R4 + C-CDA + CSV.
Reproducible runs: fix the seed so fixtures are stable across CI.
More from openmed
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About this skill
What does the generating-synthea-data skill do?

Generates synthetic but realistic patient records (FHIR R4 bundles, C-CDA documents, CSV) with MITRE Synthea for development, CI fixtures, demos, and leakage-gate test sets — zero real PHI. Use when you need safe, shareable test data for an OpenMed pipeline, reproducible fixtures for tests, or a held-out set for de-identification leakage gates, instead of touching real clinical data. Synthea output feeds the FHIR/C-CDA ingestion skills and openmed.eval. Trigger keywords: Synthea, synthetic data, fake patients, test fixtures, demo data, FHIR bundle generator, synthetic EHR, no PHI.

How do I install it?

Run `npx skills add maziyarpanahi/openmed --skill generating-synthea-data --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From maziyarpanahi/openmed, a repository with 4,851 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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