CARE-FLOWThe project’s objective is to develop and evaluate healthcare software products and algorithms that improve the streamlining of patient flows and capacities in the border region between the Netherlands and Germany, ensuring access to and efficiency of healthcare.

Sequential decision-makingThe SRI focuses on establishing a community of researchers with different mathematical backgrounds to advance the development of new solution methods for sequential decision-making problems and prove performance guarantees of those methods, with a special focus on problems that exhibit real-world characteristics such as those found in finance, agriculture, and healthcare. The initiative seeks to address gaps in research and collaboration. It emphasizes methodological development with regard to uncertainty, large-scale systems, and non-stationarity, e.g., due to multiple agents, aiming to bridge theoretical advancements and practical implementations.

Patient transfers during pandemicsThe project aims to improve inter-regional patient transfers during pandemics by developing predictive and optimization models to ensure efficient and equitable care allocation across regions. Combining data-driven approaches like statistical methods, queueing theory, and simulation with interdisciplinary collaboration, the initiative addresses the challenges of both infectious and non-infectious care during crises. Strategic partnerships with hospitals and national coordination bodies ensure practical implementation.

EU Horizon Project RAPIDERAPIDE aims to develop, validate, and demonstrate a portfolio of powerful tools that enable healthcare systems to increase the robustness of decisions, the resilience of healthcare professionals and patients, and the flexibility in the modalities of care delivery, thereby maintaining access to regular care during health emergencies.

Nursing home demand predictionThis project focuses on developing models to predict demand for nursing home care originating from hospitals on different time scales (long-term, mid-term, and short-term). Those hospital predictions will be made available to nearby nursing homes in order to support their capacity and staff planning. By accurately predicting demand and aligning resources accordingly, the project seeks to reduce bed-blocking, improve patient outcomes, and enhance the efficiency of staff planning in nursing homes and hospitals.

Monitoring and prediction of seismicityIn a synergetic collaboration between the Department of Applied Mathematics at the University of Twente and the Department of Earth Sciences at Utrecht University, we develop state-of-the-art tools to comprehensively address the extraction-seismicity causality in the Groningen area due to gas extraction.

State estimation for spatio-temporal point processesThe overall goal is to develop a spatio-temporal point process model and propose tools for state estimation that can be used to identify areas and time slots at increased risk, e.g., for property crimes such as bicycle thefts and domestic burglaries. This enables the authorities to use resources, such as patrol capacity, intelligently and to launch public awareness campaigns where and when they are most needed.

Risk management for fire servicesThe Dutch fire and rescue services are developing an interest in the use of Business Intelligence for their operations in order to improve safety, have tighter financial control, and better risk management. To this end, a rich database of incidents has been created. In this project (NWO Applied and Engineering Sciences Open Technology Programme 18004), we develop advanced probabilistic models and a rigorous statistical toolbox to obtain operationally usable predictions and quantify uncertainty.

Optimal Logistic Design of Multidisciplinary CareDriven by public opinion, increased health expenditures, an ageing population, and long waiting lists, a flood of changes in the healthcare system has been set in motion to try to make the Dutch hospitals more efficient. In this research, we will investigate how the capacity planning and control in a multidisciplinary care pathway should be organized, such that timely treatment for all patients can be ensured while an efficient care pathway is maintained.