JMIR Publications

ABSTRACT

Background:

Patient monitoring software generates a large amount of data that can be reused for clinical audits and scientific research. The Observational Health Data Sciences and Informatics (OHDSI) consortium developed the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) to standardize electronic health record (EHR) data and promote large-scale observational and longitudinal research. Primary care data have not previously been mapped and integrated into the OMOP CDM.

Objective:

To transform primary care data into the OMOP CDM.

Methods:

We extracted primary care data from the EHRs at a multidisciplinary healthcare center in Wattrelos (France). We performed structural mapping between the design of our local primary care database and the OMOP CDM tables and fields. Local French vocabularies concepts were mapped to OHDSI standard vocabularies. To validate the implementation of primary care data into the OMOP CDM, we applied a set of queries. A practical application was achieved through the development of a dashboard.

Results:

Data from 18,395 patients were implemented into the OMOP CDM, corresponding to 592,226 consultations over a period of 20 years. 18 OMOP CDM tables were implemented. 17 local vocabularies were identified as being related to primary care and corresponded to the patient characteristics (sex, location, year of birth, and race), units of measurement, biometric measures, laboratory test results, medical histories, drug prescriptions. During semantic mapping, 10,221 primary care concepts were mapped to standard OHDSI concepts. Five queries were used to validate the OMOP CDM by comparing the results obtained after completion of the transformations with the results obtained in the source software. Lastly, a prototype dashboard was developed to visualize the activity of the health center, the laboratory test results, and the drug prescription data.

Conclusions:

Primary care data have been implemented into the OMOP CDM format. Data concerning demographics, units, measurements, and primary care consultation steps were already available in OHDSI vocabularies. Laboratory test results and drug prescription data were mapped to available vocabularies and structured in the final model. A dashboard application provides healthcare professionals with feedback on their practice.