EMIF is delighted that some of our partners presented at the OHDSI Symposium, 2016 in Washington DC, USA on Friday 23rd September 2016.

EMIF is delighted that some of our partners presented at the OHDSI Symposium, 2016 in Washington DC, USA on Friday 23rd September 2016.

Monday, 26 September 2016 @ 13:56

EMIF is delighted that some of our partners presented at the OHDSI Symposium, 2016 in Washington DC, USA on Friday 23rd September 2016.

Peter Rijnbeek, Associate Professor, Erasmus MC, Rotterdam, The Netherlands, and colleagues across Europe presented a poster, entitled, "Implementation of the OMOP CDM and OHDSI tools in the European Medical Information Framework (EMIF)".

The abstract of the poster is as follows:

The European Medical Information Framework (EMIF) project’s main objective is to develop a sustainable platform that enables data discovery and unprecedented use of data sources of a wide variety of types, including electronic health records (EHR) in both primary and hospital care. EMIF adopted the OMOP Common Data Model (CDM) and is currently actively mapping nine EHR databases. EMIF aims to incorporate the OHDSI tools to support data discovery and querying. This work describes the current status and initial findings.

The poster can be viewed here.

Another group, led by The Hyve, The Netherlands and Aarhus University Hospital, Denmark, presented a poster, entitled, "Automatic Mapping of Drug Concepts the RxNorm Vocabulary".

The abstract/background for the poster is as follows:

Mapping source concepts to the standard concepts in the OMOP vocabularies is one of the most time-consuming tasks during the transformation to the OMOP Common Data Model. Drug mapping is in particular challenging, because different components have to be mapped: ingredient, dose form and strength.

As part of the European Medical Information Framework (EMIF) project, Danish population health data are mapped to the OMOP CDM, including the local drug codes. The Hyve assists in creating a script to automatically map a set of 4754 drugs to the RxNorm vocabulary. The input data contains ATC codes, dosage forms, numerical strengths and strength units.The mapping procedure presented here is based on the drug mapping for the Japan Medical Data Center Claims Database.

The poster can be viewed here.

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