generating-synthea-data

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:

# Requires Java 11+. Clone and build once.
git clone https://github.com/synthetichealth/synthea && cd synthea
./gradlew build -x test

# Generate 50 patients in Massachusetts as FHIR R4 + C-CDA + CSV.
./run_synthea -p 50 Massachusetts \
  --exporter.fhir.export=true \
  --exporter.ccda.export=true \
  --exporter.csv.export=true \
  --exporter.baseDirectory=./output

# Reproducible runs: fix the seed so fixtures are stable across CI.
./run_synthea -s 12345 -p 20 --exporter.baseDirectory=./fixtures

Output lands under output/fhir/, output/ccda/, and output/csv/. Feed the FHIR bundles to parsing-... skills, or hand narrative straight to OpenMed:

import json, openmed

bundle = json.load(open("output/fhir/Patient_xyz.json"))
for entry in bundle.get("entry", []):
    res = entry.get("resource", {})
    div = (res.get("text") or {}).get("div", "")     # narrative XHTML
    if div.strip():
        deid = openmed.deidentify(div, method="replace", policy="hipaa_safe_harbor")
        result = openmed.analyze_text(deid.text, output_format="dict")