Detecting Crises Earlier: AI for Situational Awareness in the German Healthcare System
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Detecting Crises Earlier: AI for Situational Awareness in the German Healthcare System


The COVID-19 pandemic demonstrated how difficult it can be to maintain an overview of the current health situation without adequate digital infrastructure. This is where the team behind AtheneKI comes in. The system is designed to bring together large volumes of information, simulate crisis scenarios, and thereby help identify emerging problems earlier and support better decision-making.

“Data in the healthcare system tends to be associated with concerns and fears in Germany. But the absence of data about the current situation is itself a threat,” says Prof. Dr. Folker Meyer. He works at the Institute for Artificial Intelligence in Medicine (IKIM) and holds the Chair of Medical Informatics with a focus on Medical Data Science at the University of Duisburg-Essen. “We are not concerned with personal data. Instead, we are interested in data from hospitals and pharmacies, as well as wastewater and weather data.”

At IKIM, researchers are developing the project’s core data science methods. They bring together information from different sources, standardize the data, and develop AI-supported methods that can identify trends and unusual changes and flag them at an early stage.

“Germany currently lacks an infrastructure for providing digital, timely information about the health situation and the state of the healthcare system across the country. AtheneKI is building this infrastructure,” says Prof. Dr. Folker Meyer. “At IKIM, we are creating the data foundation without the need for burdensome reporting requirements.” The resulting insights can support professional and political decision-makers as well as representatives of hospitals and public health authorities.

The consortium is coordinated by the Bundeswehr Medical Academy. An overview of the participating partners is available on the project website (German only).

Regions: Europe, Germany
Keywords: Health, Medical, Policy, Applied science, Artificial Intelligence, Policy - applied science

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