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  • Guy Tsafnat

FHIR and OMOP collaboration and what it means

A few weeks ago OHDSI and HL7 announced a collaboration to unify their common data models. (Full disclosure, one of the leaders of this collaboration is our very own Grahame Grieve). You will recall that the FHIR and OMOP standards (or common data models) serve different purposes. However, there is no reason for their data models to be different although this doesn't mean it will be easy to do.

The collaoration recognizes the unmet need and the increasing desire to user real world data to improve patient care. A cause that Evidentli is very passionate about. We are looking forward to unification of these two data standards which, for the many health systems that use FHIR, means data will be one step closer to being research-ready. Of course, having the data in OMOP is just the start of using real-world data for improvement of care. Ethical managemnt of such data is critical and of course, self-serve clinical analytics are reuiered to overcome the evidence shortage at scale and to rapidly translate real world data into better care.




Further reading: HL7, OHDSI to Collaborate on Single Common Data Model


#research #automation #interoperability #realworlddata #rwd #standards #omop #fhir #realworldevidence #rwe #ethicalAI

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