Challenge 8: OMOP Analytics

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Introduction

In the Healthcare data solutions in Fabric, OMOP Analytics capability within Fabric Lakehouse allows for the deployment of the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM), giving researchers within the OMOP community access to OneLake’s scale and harness AI in Microsoft Fabric. This setup supports standardized analytics for observational studies, enabling researchers to compare procedures and drug exposures and explore drug-condition correlations.

Below is the overview of the Healthcare data solutions in Fabric solution architecture:

Description

In this challenge, you will deploy Healthcare data solutions to your Microsoft Fabric workspace to access the Healthcare data foundations and OMOP analytics capabilities. Configure them to meet OMOP standards, use pre-built pipelines to process data exported from your FHIR service, transform it to OMOP, and implement the OMOP CDM within the Microsoft Fabric medallion architecture, which consists of the following three core layers:

(Optional) Once FHIR data is transformed to OMOP standards in the Gold Lakehouse, utilize pre-built Notebooks to construct statistical models, conduct population studies, and generate Power BI reports for comparative analysis of various interventions on patient health outcomes.

Prerequisites:

First, run FHIR ingestion pipeline to export your FHIR data (deployed in challenge 1) and store the raw JSON in the lake

Ingest raw data into delta tables in the Bronze (msft_bronze) Lakehouse

Flatten raw FHIR JSON files in Bronze (msft_bonze) Lakehouse and to ingest the resulting data into the Silver (msft_silver) Lakehouse

Transform resources in the Sliver Lakehouse into OMOP Common Data Model and persist in Gold (msft_gold_omop) Lakehouse

Success Criteria

To complete this challenge successfully, you should be able to:

Learning Resources