ECGKit / FHIR-Analytics-Pipelines

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FHIR Analytics Pipelines

FHIR Analytics Pipelines is an open source project with the goal to help build components and pipelines for rectangularizing and moving FHIR data from Azure FHIR servers namely Azure Healthcare APIs FHIR Server, Azure API for FHIR, and FHIR server for Azure to Azure Data Lake and thereby make it available for analytics with Azure Synapse, Power BI, and Azure Machine Learning.

This OSS project currently has the following two solutions:

  1. FHIR to Synapse sync agent: This is an Azure function that extracts data from a FHIR server using FHIR Resource APIs, converts it to hierarchial Parquet files, and writes it to Azure Data Lake in near real time. This also contains a script to create external tables and views in Synapse Serverless SQL pool pointing to the Parquet files.

    This solution enables you to query against the entire FHIR data with tools such as Synapse Studio, SSMS, and Power BI. You can also access the Parquet files directly from a Synapse Spark pool. You should consider this solution if you want to access all of your FHIR data in near real time, and want to defer custom transformation to downstream systems.

  2. FHIR to CDM Pipeline Generator: It is a tool to generate an ADF pipeline for moving a snapshot of data from a FHIR server using $export API to a CDM folder in Azure Data Lake Storage Gen 2 in csv format. The tools requires a user-created configuration file containing instructions to project and flatten FHIR Resources and fields into tables. You can also follow the instructions for creating a downstream pipeline in Synapse workspace to move data from CDM folder to Synapse dedicated SQL pool.

    This solution enables you to transform the data into tabular format as it gets written to CDM folder. You should consider this solution if you want to transform FHIR data into a custom schema as it is extracted from the FHIR server.

Contributing

This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit https://cla.opensource.microsoft.com.

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This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact opencode@microsoft.com with any additional questions or comments.

Trademarks

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