The NWO visitors grant will enable us to host Dr. Mariel Lavieri for a period of two months in the Netherlands, at University of Twente, and VU Amsterdam. Dr. Lavieri is one of the leading researchers in the field of Healthcare Operations Research. For most of the visit she will be hosted by the Center for Healthcare Operations Improvement & Research (CHOIR) at University of Twente. Dr. Lavieris research experience and interest are a perfect fit with our ongoing work. During her visit, she will contribute to several ongoing research projects, engage with healthcare practitioners, give several presentations, mentor PhD students and a young assistant professor (A.G. Leeftink, UT), and initiate research and education collaboration between University of Twente and University of Michigan.

Strategic deployment of resources in advance for emergency preparedness is a challenging problem due to inherent uncertainties. A novel approach is proposed, leveraging mathematical optimization and data analytics methods. It is applied to Dutch out-of-hospital cardiac arrest and defibrillator data to reduce response time and increase survival in an emergency.

If hospitals in the 21st century do not rethink the way they organize healthcare delivery, they cannot maintain the current quality of care and service, nor contain the ever-increasing costs. In recent years, healthcare operations management is gaining momentum through improved availability of process and workflow data, and development and application of advanced operations research techniques. This project aims to break through the silo-ed organization of hospital departments, by developing mathematical (operations research) solutions for integral planning and control of care chains. Embedded in decision support software, developed by consortium partner Rhythm BV, and validated and tested in a Dutch hospital (Sint Maartenskliniek), they allow hospitals to improve quality and timeliness of care while containing costs. The project will be embedded in CHOIR (Center for Healthcare Operations Improvement and Research), University of Twente, one of the leading Healthcare OR/OM groups, renowned for theoretically strong research combined with true engagement in healthcare. The project will also take place in Sint Maartenskliniek, which will provide an ideal research and test bed environment for integral capacity management research. Consortium partner Rhythm BV specializes in bringing research into practice through consulting activities, decision support tool development, and in-company training. Existing (pre)prototype planning solutions for the integral planning of (surgical) care chains in hospitals were developed by CHOIR in recent years in collaboration with practice. In this project, we wish to bring the mathematical foundations of these (pre)prototype solutions to the next level, to be able to integrate the sub-solutions for single departments in a unifying prototype system that spans the entire care chain. Finally, we aim to validate and put the system into practice in a first use case at the Sint Maartenskliniek and show that this system may also be implemented at other hospitals.

Assessing the academic capabilities of students should play a key role in both stimulating their learning process (formative assessment - FA) and in the accurate evaluation of their knowledge and capabilities in relation to a topic (summative assessment - SA). Therefore, based on the principle of constructive alignment, any form of assessment needs to be carefully designed to match the learning outcomes of a course, needs to be delivered in an appropriate format (paper-based vs. computer-based), and needs to be scored in a suitable manner. However, this is a challenging task, due to the substantial amount of time teachers need to spend on grading open questions. From our experience, this results in using less appropriate assessment methods (e.g.: Multiple Choice questions) or in less time spent by teachers on innovating their courses (e.g.: implementation of FA). Inspired by recent developments in academia and practice, we propose to investigate the application of machine learning (ML) technology for supporting grading of open questions, for both SA and FA. Our expected results include the design of a method supporting grading of open questions with ML, an investigation into the most suitable ML algorithms for small samples of tests, and insight into how ML can be applied in FA to make its usage more appealing to teachers. Additionally, as the most innovative aspect, we propose to investigate the feasibility of a state-of-the-art version of FA (assessment as learning), focused on student self-assessment with the help of short-form open question quizzes assessed with ML techniques.

Dit project ontwikkelt de Logistics Data Space (LDS), waarmee logistieke bedrijven kunnen deelnemen in digitale ecosystemen voor efficiënte samenwerking en nieuwe diensten. LDS bestaat uit een Connector Store met connectoren voor data-uitwisseling tussen heterogene ICT omgevingen, en een Interoperability Simulator voor het verkennen van samenwerkingsmogelijkheden voorafgaand aan de implementatie.