IDEAL: The Intelligent Digital Guideline Editor - Application of causal inference for evidence generation using emulated clinical trials

The "Intelligent Digital Guideline Editor" (IDEAL) project is developing a methodology to use routine data for clinical questions through machine learning and statistical methods. The insights gained will be integrated into guidelines via a digital editor. The goal is to make guideline updates more efficient and promote digitalization in medicine.

From left to right: Maria Frielinghaus, Sandrine Müller, Eike Voss © Shanice Allerheiligen / U Bremen Research Alliance

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The Intelligent Digital Guideline Editor (IDEAL) is a research project of the Fraunhofer Institute for Digital Medicine MEVIS, the Leibniz Institute for Prevention Research and Epidemiology - BIPS and the Applied Statistics Group of the University of Bremen. The project focuses on the development of a methodology to generate evidence for clinical questions by applying machine learning algorithms, causal inference and adaptive statistical methods to routine data and to rapidly integrate this evidence into existing guidelines using a digital guideline editor.

In the future, these developments could potentially contribute to a more efficient adaptation of clinical guidelines by using existing routine data better than before to generate evidence or to plan and conduct necessary clinical studies in a more targeted manner. This would be an important building block for advancing the digitalization of the conventional, analogue guideline development process. The project aims to build a bridge between advanced methods and technologies and clinical application. Ultimately, patients should also benefit, especially groups that are rarely included in clinical trials.

"Patients and clinicians would probably profit from the results of our research and other similar projects. It's a win-win situation for both groups. By ensuring that we update guidelines regularly, we contribute to the many measures taken to improve health care."
- Sandrine Müller