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Transforming Estonian health data to the Observational Medical Outcomes Partnership (OMOP) Common Data Model: lessons learned.

Marek OjaSirli TammKerli MoosesMaarja PajusaluHarry-Anton TalvikAnne OttMarianna LahtMaria MalkMarcus LõoJohannes HolmMarkus HaugHendrik ŠuvalovDage SärgJaak ViloSven LaurRaivo KoldeSulev Reisberg
Published in: JAMIA open (2023)
For a representative 10% random sample, we successfully transferred complete records from 3 national health databases to OMOP CDM and created a reusable transformation process. Our work helps future researchers to transform linked databases into OMOP CDM more efficiently, ultimately leading to better real-world evidence.
Keyphrases
  • big data
  • healthcare
  • electronic health record
  • public health
  • cross sectional
  • mental health
  • machine learning
  • current status
  • type diabetes
  • health information
  • adipose tissue
  • weight loss
  • neural network
  • glycemic control