CALM-QE – Medical Informatics Use Case

13. July 2023Press Releases

Note: The following English translation is intended solely to assist reader understanding and is not legally binding. Please see the original German text for the official version.

CALM-QE – Medical Informatics Use Case “COPD and asthma: Longitudinal and cross-sectoral real-world data for machine learning application for quality improvement and knowledge acquisition”.

Innovative IT solutions can make a decisive contribution to improving patient care. Countless amounts of data are collected every day in hospitals, doctors’ surgeries and in research. However, this data is currently still underutilized, as the data formats and IT systems of clinics are often not compatible.

This is where the BMBF comes in with the multi-phase funding concept of the Medical Informatics Initiative (MII). It lays the central foundations for digitized health data to be made accessible across locations and used for research. In the current funding phase, the focus is on expanding the structures created in all university hospitals and their collaboration. The institutions are to network even more closely with each other and with other funding programs and health research initiatives. The concrete added value of digitalization in health research for patients, medical staff and science is demonstrated in particular by the cross-institutional clinical use cases.

The joint use case project CALM-QE investigates chronic obstructive pulmonary disease (COPD) and bronchial asthma (BA), both of which are among the most common non-communicable lung diseases with significant socio-economic impact. The development, severity and exacerbations of these diseases are the result of complex interactions between genes and the environment. The main challenge in the field of COPD and BA is to translate the treatable trait approach to individual patients. Therefore, the aim of CALM-QE is to develop, train and test predictive models for important clinical outcomes based on multidimensional real-world datasets.

The long-term goal of the MII is to create a more efficient, digitally networked healthcare system that supports medical staff, researchers and patients in detecting diseases better and earlier and finding the best possible treatment for each individual.

Please find further information here: https://www.gesundheitsforschung-bmbf.de/de/calm-qe-medizininformatik-use-case-copd-und-asthma-longitudinale-und-sektorubergreifende-16644.php