During the development and networking phase of the Medical Informatics Initiative (MII) from 2018 to 2022, clinical and methodological use cases within the four consortia proved the functionality of the Data Integration Centers. Using projects from different application areas in healthcare, the use cases demonstrated the possibilities of digital services and infrastructures in the healthcare sector.
Intensive care units generate large amounts of data every day, offering enormous potential for artificial intelligence applications. The Use Case ASIC demonstrates this in the treatment of patients with acute respiratory distress syndrome (ARDS), a disease that still kills around 40 percent of all patients today. Under the leadership of the University Hospital Aachen, a smartphone app has been developed in cooperation with seven other university hospitals as an early warning system for potential ARDS. The ASIC App evaluates data collected during the treatment of patients in the intensive care unit. If ARDS is suspected, intensive care physicians are alerted by a mobile device in their coat pocket.
Project duration: 01.01.2018 to 31.12.2023
More information about ASIC can be found here.
The Use Case HELP of the SMITH Consortium addresses the guideline-based and recommended use of antibiotics for early, targeted control of bacterial infections. The HELP manual is a step-by-step guide to the diagnosis and responsible use of antibiotics for staphylococcal bloodstream infections. In this way, infectious disease consultation can be optimized and antibiotic resistance can be avoided. The use of the HELP manual was tested in a study from 2020 to 2022 at the university hospitals in Aachen, Essen, Halle and Leipzig under the leadership of the University Hospital Jena.
Project duration: 01.01.2018 to 30.06.2023
More information and results about HELP can be found here.
The PheP methodological use case developed innovative data analysis methods to automatically extract medical information from electronic patient records. The project supported the creation and enrichment of data and demonstrated how these data can be used in clinical projects. One of the methods used was phenotyping. Phenotyping can be used to infer other characteristics of patients, such as height, weight, gender, or age. In addition, PheP established methods for distributed analysis and created the prerequisites for natural language processing (NLP) methods. As a follow-up project, the cross-consortium Use Case GeMTeX builds on the experience gained in PheP.
Project duration: 01.01.2018 to 31.05.2023
Further information and results of PheP can be found here.