All our research activities are carried out in close cooperation with the practical world, in particular with players in the healthcare sector, and are funded and supported by various public institutions. This ensures that our research results are applied in practice as quickly as possible. This enables our models and simulations to be validated in real life. Furthermore, the regular active exchange with practitioners from different fields, especially with medical professionals, promotes the understanding of the business and mathematical problems with the medical application area.
The Chair of Health Care Operations/Health Information Management is pursuing several projects related to the Covid-19 pandemic, analysing various issues in collaboration with high-level practice partners using a variety of methodological approaches.
The research project "Resident scheduling in teaching hospitals with the use of quantitative methods" deals with the strategic and tactical-operational planning of medical residents.
In the research project "Modeling physician scheduling for high-cost areas in hospitals", we consider an integrated approach to combining physician shift scheduling and the scheduling of operations on a tactical-operational level.
CARE REGIO is a joint research project funded by the Bavarian State Ministry for Health and Care. It aims to noticeably relieve the burden on caregivers, family caregivers, and those in need of care, which is to be achieved with the help of a long-term application of technical-digital systems.
PROGNOSIS "Epidemic-related hospital resource requirements - modeling incidence, bed occupancy, staff scheduling, and supply chains" is a collaborative project funded by the German Federal Ministry of Education and Research with the aim of predicting the burden of hospital due to serious infectious diseases.
KISIK – “AI-based forecasting and optimization methods in assistance systems for effective and efficient management of intensive care capacity in German hospitals” is a joint research project with the goal of developing AI-based algorithms for decision support in the management of intensive care capacity.