OHDSI on Azure GitHub repository is designed to ease deployment of tools provided by the Observational Health Data Sciences and Informatics (OHDSI, pronounced "Odyssey") community on to Azure. We are guided by our Hypothesis and core objectives.
Hypothesis - “OHDSI on Azure will empower IT department and operations teams to support researchers, thus increasing researchers' motivation to act on new ideas”
- Decreased deployment challenges
- Increased access to funding
- Simplified adoption strategy
OHDSI on Azure is a set of scripts and templates designed to automate the deployment of the solution in the Microsoft Azure cloud using Bicep & PaaS services. It is designed to facilitate standardized scalable deployments within customer managed Azure subscriptions. Provide best practices for running OHDSI on Azure. Ease the burden of management and cost monitoring of research projects.
OHDSI on Azure has taken a container-based approach to operating OHDSI tools. Therefore, OHDSI on Azure does its best to not host code developed by the OHDSI community. Our deployment templates pull containers from Docker Hub.
We invite you and your organization to participate in the continued feature expansion of OHDSI on Azure.
This repository assumes the end user is familiar with the OHDSI community, OMOP, Azure, and Bicep.
Some of the OHDSI projects included:
- Common Data Model (CDM), including Vocabulary
- Atlas - OSS tool used to conduct analyses on standardized observational data converted to the OMOP Common Data Model V5
- WebApi - contains all OHDSI RESTful services that can be called from OHDSI applications
- Achilles - provides descriptive statistics on an OMOP CDM database
- ETL-Synthea - Conversion from Synthea CSV to OMOP CDM
- You can host your CDM in Azure PostgreSQL. You can load your cdm and vocabularies into Azure Storage Container as cs.gz files, and pass as a paramater in your custom deployment.
This setup is based on the CDM v5.4.0 and supports both PostgreSQL and Azure Synapse.
To get started, click on deploy to Azure button. To get more detailed instructions, please refer to the Deployment Guide.
This solution comes with a prebuilt synthetic CDM of 1,000 patients. If you wish to create your own (maybe larger) synthetic dataset you can follow a similar process described here.
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.
When you submit a pull request, a CLA bot will automatically determine whether you need to provide a CLA and decorate the PR appropriately (e.g., status check, comment). Simply follow the instructions provided by the bot. You will only need to do this once across all repos using our CLA.
This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact [email protected] with any additional questions or comments.
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