The Observational Health Data Science and Informatics (OHDSI) is an international collaboration that enables researchers to conduct observational studies around the globe based on standardized data and methods that was founded in 2014 [1]. OHDSI provides a common data model (OMOP CDM) including Standardized Vocabularies for data standardization and harmonization. The OHDSI community also developed guidelines and a rich open-source software framework and tools for data transfer (ETL) and analytics. The OHDSI community is a fast growing community already present in more than 19 countries and with more than 2500 collaborators worldwide [2]. In 2021, an OHDSI Germany Workgroup was initiated, led by Ines Reinecke and Michele Zoch from Technische Universität Dresden, Carl Gustav Carus Faculty of Medicine, Institute for Medical Informatics and Biometry (IMB) in cooperation with the OHDSI Community. Its goal is to foster the adoption of OHDSI in Germany, e.g. by providing tools for the use of the core dataset of the German Medical Informatics Initiative (MII) in OMOP. As such, German data holders will be enabled to not only use the OHDSI ecosystem for analysis, but also to participate in international studies and projects (e.g. European Health Data Evidence Network (EHDEN)).This workshop aims to answer the following question: How can we use inpatient data from university hospitals (core dataset of MII) to participate in international, retrospective observational studies? First, it will introduce into OHDSI Germany, the ongoing projects with the European Medicines Agency (EMA) and the MII consortium Medical Informatics in Research and Medicine (MIRACUM). Second, the audience will be introduced to best practices using the OHDSI tools and methods framework by means of a interactive demo session so that the participants learn more about Atlas. An overview of the future roadmap of OHDSI Germany including work done so far and next steps will be discussed. Possibilities to join the journey become a member of the OHDSI Germany chapter will close the session. The agenda is shown in the table below and is subject to change:
13:00 – 13:15 Uhr Key Note
TOP 1 Introduction
13:15 – 13:30 Uhr Background: Reasons for Founding the group What is OHDSI Germany?
TOP 2 Our Work with OHDSI and OMOP
13:30 – 13:45 Uhr MIRACUM, MII und OMOP
13:45 – 14:15 Uhr Vorstellung relevanter Studien und Netzwerke
TOP 3 Interaktive Demo
14:30 – 15:00 Uhr Einführung in ATLAS – Kohorten Definitionen
15:00 – 15:30 Uhr Vokabularen und deren Herausforderungen
TOP 4 Roadmap of OHDSI Germany
15:30 – 15:45 Uhr Wie geht es weiter?
15:50 – 15:55 Uhr Join the Journey – become a member!
Speaker:
Ines Reinecke (ines.reinecke@tu-dresden.de) Institute of Medical Informatics and Biometry at Carl Gustav Carus Faculty of Medicine at Technische Universität Dresden, Germany
Christian Reich Observational Health Data Science and Informatics (OHDSI), New York, NY, USA
Nikolai Grewe IQVIA Germany – The Human Data Science Company, Frankfurt, Germany
Michéle Zoch (michele.zoch@tu-dresden.de) Institute of Medical Informatics and Biometry at Carl Gustav Carus Faculty of Medicine at Technische Universität Dresden, Germany
Michael Kallfelz Odysseus Data Services GmbH, Berlin, Germany
References:
[1] Hripcsak G, Ryan PB, Duke JD, Shah NH, Park RW, Huser V, et al. Characterizing treatment pathways at scale using the OHDSI network. Proc Natl Acad Sci. 2016;113(27):7329.
[2] Observational Health Data Sciences and Informatics (OHDSI). The Book of OHDSI [Internet]. Independently published; 2019 [cited 2020 Feb 10]. Available from: https://ohdsi.github.io/TheBookOfOhdsi/.