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pathling-python

Query and transform FHIR data with the Pathling Python API in Spark.

133|23|Updated Mar 23, 2020
Search Tags:#python#data analytics#spark#terminology#fhir#pathling
One-click install
npx skills add https://github.com/aehrc/pathling --skill pathling-python
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: pathling-python
Source: https://github.com/aehrc/pathling/tree/main/.claude/skills/pathling-python
Command: npx skills add https://github.com/aehrc/pathling --skill pathling-python

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill simplifies complex health data analytics by providing a Pythonic interface for querying and transforming FHIR data, and performing advanced terminology operations.

Core Features & Use Cases

  • FHIR Data Ingestion: Read FHIR data from NDJSON, Bundles, or Delta tables into Spark DataFrames.
  • SQL on FHIR Views: Create SQL-friendly tabular views from FHIR resources.
  • Terminology Services: Perform value set membership tests, concept translations, and subsumption checks using FHIR terminology servers.
  • Use Case: Analyze patient demographics and conditions by querying FHIR resources, then enrich the data by checking if diagnosis codes belong to specific SNOMED CT value sets.

Quick Start

Use the pathling-python skill to create a PathlingContext and read FHIR data from the '/path/to/fhir/data' directory.

Frequently Asked Questions about pathling-python

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I query FHIR data in Python and Spark?▼

You can query FHIR data in Python and Spark by using the Pathling Python API to ingest NDJSON, Bundles, or Delta tables into Spark DataFrames and create SQL-friendly tabular views for analysis.

How do I check if diagnosis codes belong to a SNOMED CT value set?▼

You can check diagnosis code membership in SNOMED CT value sets by applying terminology functions like member_of within a Spark environment using a FHIR terminology server.

What are the best ways to perform terminology translations on FHIR resources?▼

Performing terminology translations on FHIR resources is best handled using the translate function, which leverages FHIR terminology servers to map concept codes between different code systems.

Can I use SQL on FHIR to analyze patient demographics and conditions?▼

Yes, you can use SQL on FHIR to analyze patient demographics and conditions by creating tabular views from FHIR resources and querying them directly within your Spark environment.

How do subsumption checks work for FHIR concepts in a Spark DataFrame?▼

Subsumption checks for FHIR concepts in a Spark DataFrame work by utilizing the subsumes function to evaluate hierarchical relationships between codes via a connected FHIR terminology server.

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