FHIR Query Validator helps developers and data engineers catch errors in FHIR search queries before they reach a server. Instead of debugging silent failures or unexpected empty result sets, you get clear, structured validation feedback at query construction time. The tool is designed for Python environments — including Jupyter notebooks — and can validate individual queries or entire batches in a single call.Documentation Index
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Why validate FHIR queries?
FHIR search queries follow a strict specification. A query likePatient?birthdate=yesterday fails silently on many FHIR servers — it simply returns no results rather than an error. Without validation, these issues are hard to trace and even harder to catch in automated pipelines.
FHIR Query Validator catches these problems early by checking:
- Resource type names — ensures the resource (e.g.,
Patient,Observation) is a valid FHIR R4 resource - Search parameter names — verifies that parameters like
family,birthdate, andcodeexist for the given resource - Parameter value formats — checks that dates, tokens, references, and other value types are well-formed
- Query string structure — detects malformed query strings before they’re sent
Who is this for?
Healthcare app developers
Validate queries at development time to prevent runtime failures in patient-facing applications.
Data engineers
Validate bulk query sets in ETL pipelines to ensure FHIR data extraction queries are correct.
Researchers & analysts
Use in Jupyter notebooks to interactively build and validate FHIR queries against clinical datasets.
QA & test automation
Integrate into test suites to assert that query strings generated by your application remain valid.
Key capabilities
| Feature | Description |
|---|---|
| Single query validation | Validate one query string and get a structured result |
| Batch validation | Validate a list of queries in one call |
| Structured error output | Errors and warnings are returned as structured objects, not plain strings |
| FHIR R4 coverage | Validates against HL7 FHIR R4 resource and search parameter definitions |
| Jupyter-friendly | Works in notebook environments for interactive query development |
Next steps
Installation
Set up FHIR Query Validator in your Python environment.
Quickstart
Validate your first FHIR query with a working code example.