Randomized controlled trials (RCTs) are the gold standard in medicine for investigating causal relationships in health research. However, RCTs are often difficult to conduct and, in some cases, even unethical for certain research questions. Even when feasible, participant selection is highly restrictive, limiting the generalizability of results.
Where RCTs reach their limits, carefully conducted analyses of observational data can provide valuable insights into causal relationships. While causal inference methodologies have advanced significantly across various scientific disciplines in recent years, their application in applied health research remains limited. The growing availability of health data from electronic health records and routine clinical data in Germany presents a timely and pressing opportunity to continue advancing the application of causal inference methods in health research.
The Einstein Circle, led by Jess Rohmann, researcher at the Institute of Public Health and the Berlin Institute of Health’s QUEST Center for Responsible Research at Charité – Universitätsmedizin, brings together 20 experts from epidemiology, statistics, medical informatics, mathematics, medicine, and bioethics to address this challenge. The Circle members seek to identify barriers, define collaborative research projects, and promote the responsible (re)use of observational health data. In addition, Circle members are interested in enhancing the integration of causal inference into Bachelor's, Master's, and PhD training programs. They also aim to engage researchers from other Berlin institutions to broaden the impact of causal inference in health research.
Circle members: Felix Balzer, Vanessa Didelez, Matthieu Domenech de Cellès, Meghan Forrest, Toivo Glatz, Chisato Ito, Stefan Konigorski, Felicitas Kühne, Tobias Kurth, Jeremy Labrecque, Anthony Matthews, Marco Piccininni, Sophie Piper, Fabian Prasser, Jess Rohmann, Mats Stensrud, Daniel Strech, Peter Tennant, Vanessa Voelskow, Anabelle Wong