FHIR R4 Patient Bundle (JSON)
A sample HL7 FHIR R4 bundle with a Patient plus vital-sign Observations, an Encounter, and a Condition — a realistic healthcare-interoperability fixture for testing FHIR parsers and mappers. Synthetic data, not a real person.
{
"resourceType": "Bundle",
"id": "novus-example-bundle",
"type": "collection",
"entry": [
{
"resource": {
"resourceType": "Patient",
"id": "patient-001",
"name": [
{
"use": "official",
"family": "Lovelace",
"given": [
"Ada"
]
}
],
"gender": "female",
"birthDate": "1985-12-10",
"address": [
{
"city": "London",
"country": "GB"
}
]
}
},
{
"resource": {
"resourceType": "Observation",
"id": "obs-weight",
"status": "final",
"category": [
{
"coding": [
{
"code": "vital-signs"
}
]
}
],
"code": {
"coding": [
{
"system": "http://loinc.org",
"code": "29463-7",
"display": "Body weight"
}
]Specifications
- Standard
- HL7 FHIR R4
- Bundle Type
- collection
- Resources
- Patient, Observation×2, Encounter, Condition
- Domain
- healthcare
What is a .json file?
JSON (JavaScript Object Notation) is a lightweight, text-based data-interchange format representing objects, arrays, strings, numbers, booleans, and null. It is language-independent, human-readable, and the dominant format for web APIs and configuration. It requires a single well-formed root value.
How to use this file
Use an example JSON file to test parsers and serializers, schema validation, Unicode and number-precision handling, and API request or response processing.
How to use this file for testing
“FHIR R4 Patient Bundle (JSON)” is a deterministic Novus Examples fixture for Data import, Conversion testing. Realistic faker-generated datasets with documented schemas for testing import and ETL flows.
Documented properties for this file: JSON · 3,451 bytes. Compare results against paired or grouped companions on this page when present (clean↔damaged, searchable↔scanned, or format twins) so scores stay reproducible across runs.
Download the file once, keep the path stable in CI or local scripts, and treat the spec table as the contract: dimensions, seeds, field lists, and roles are intentional. Corrupt or invalid samples are labelled as such — expect parsers to fail loudly rather than silently accept them.
Data fixtures document their exact quirks — delimiters, encodings, null handling, schema, and row counts — in the spec table. Point your parser or importer at the file and assert it handles the documented edge cases; clean and deliberately-messy siblings make before/after diffs straightforward.
Code examples
import json
with open("fhir-patient-bundle.json") as f:
data = json.load(f)
print(type(data), len(data))Related files
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