Three Ways OpenMRS is Improving OpenMRS Analytics

At OMRS18, over 150 people brainstormed ideas about how we might make reporting easier. Ideas ranged from standarding reporting requirements to analytics tools to intuitive data pipelines to exporting data to other applications.

Earlier this year, several contributors began turning these ideas into reality. Here are three areas where our community is working on together to create community solutions to reporting headaches:

The promise of OpenMRS ETL. In April, our chief architect Burke Mamlin, outlined the promise of a shared, OpenMRS ETL solution for advanced reporting/analytics. After a series of ETL Lightning Talks and Talk discussions in May, the community launched the Analytics Engine Squad. This squad is working together to build an analytics engine that will improve the use of OMRS data for indicator reporting, reduce technical team member overtime, and make it easy to drill down to individual patient records. 

The Future of FHIR in OpenMRS. The ability to represent OpenMRS Data in a FHIR-format means that OpenMRS implementers will be in a position to potentially use any of the new tools and pipelines capable of consuming FHIR-formatted data that are behind developed in the digital solution space. The FHIR Squad has already released a new version of the FHIR2 module, which provides a flexible and extensible mapping from the OpenMRS data model to FHIR v4 resource.

Patient level indicator reporting (PLIR). More and more countries are exploring standards-based health information exchange solutions. In alignment with the Analytics Engine Squad and the FHIR Squad, OpenMRS has begun work on a proof of concept that will extract data from OpenMRS and make it available to a FHIR server – and to a Clinical Quality Language (CQL) Engine capable of calculating indicators.

The OpenMRS community supports these squads with community management, product management, technical architecture and development expertise, and quality assurance.

Everyone is welcome! More details on when and where can be found on our Analytics Engine, FHIR, and PLIR project pages. 

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