Personalized medicine infrastructure using the open-source OMOP common data model including an Electronic Health Record interface

Ismail Gögenur, Zealand University Hospital
Grant amount: 13,283,466

One of the main targets of Personalized Medicine is to refine the stratification of a single patient aiming to provide improved diagnosis, prognosis, and treatment for the specific individual. This can be achieved by including not only a detailed account of the patient’s health record, but also similar data from population-wide databases and clinical projects. These multiple data sources can be collected in a single and common data model to serve as a powerful platform. The model will include the necessary data science domains such as machine learning and aid the clinician in the decision-making process. To facilitate the implementation, real-time data from the electronic health report of the patient is needed. We will, in collaboration with data scientists and medical and biological professionals, establish the necessary infrastructure to promote this model in a clinical use case and finally, expand it within other medical fields.

Project participants
Professor Ismail Gögenur
Zealand University Hospital, Department of Surgery

Director Peter Løngreen
Technical University of Denmark, Danish National Life Science Supercomputing Center

Scientific Lead Christine O. Rasmussen
Technical University of Denmark, Danish National Life Science Supercomputing Center

Professor, Lead Scientist Thomas Litman
University of Copenhagen / LEO Pharma

Associate Professor Christina Ellervik
University of Copenhagen, Department of Clinical Science / Harvard Medical School

Associate Professor Peter Rijnbeek
Erasmus University Medical Center, Department of Medical Informatics