Pyre: Python Analytics for FHIR-based Healthcare Data

Pyre is a specialized analytics package designed for healthcare data in Python. It exclusively works with the FHIR (Fast Healthcare Interoperability Resources) format, simplifying the process of loading FHIR resources into Pandas DataFrames.

Key Features:

Load FHIR Resources Efficiently: Pyre streamlines the process of importing various FHIR resources (like Patient, Encounter, Observation) into individual Pandas DataFrames.
NDJSON Support: Pyre leverages the NDJSON format (as recommended by Bulk FHIR) for input. Simply store your FHIR resources in .ndjson files within the inputs directory, and Pyre will handle the rest.
Built-in Analytics Functions: Pyre offers a suite of built-in analytics functions tailored for common Population Health criteria. Plus, the community is encouraged to contribute with more!

Requirements:

Ensure you have the necessary packages installed:

pip install pandas ndjson

Getting Started:

To initiate Pyre, run: python pyre.py

Loading Additional Data:

To add more data to Pyre:

Copy your .ndjson file(s) into the data directory.
Ensure your file adheres to the naming convention corresponding to the FHIR resource (e.g., Patient.ndjson, Encounter.ndjson).
Remember, only the NDJSON format is supported. Each line in your NDJSON file should represent a distinct FHIR resource. Avoid mixing multiple resources within a single file.

Contribute: