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Healthcare Claim (FHIR SAMPLE JSON)

Synthetic FHIR Claim resource for healthcare billing parser tests — not a real patient.

Preview — first 21 linesjson
{
  "resourceType": "Claim",
  "id": "CLM-SAMPLE-001",
  "status": "active",
  "patient": {
    "reference": "Patient/PAT-SAMPLE-001"
  },
  "item": [
    {
      "productOrService": {
        "coding": [
          {
            "code": "99213",
            "display": "Office visit SAMPLE"
          }
        ]
      }
    }
  ]
}

Specifications

Format
FHIR Claim
Domain
healthcare
Seed
42042

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

“Healthcare Claim (FHIR SAMPLE JSON)” is a deterministic Novus Examples fixture for Data import, JSON parsing. Realistic faker-generated datasets with documented schemas for testing import and ETL flows.

Documented properties for this file: seed 42042 · FHIR Claim. 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("claim-sample.json") as f:
    data = json.load(f)
print(type(data), len(data))

Generated by generation/data_wave_f.py. Free for any use, no attribution required — license.