The professorship introduces itself
In research and teaching, the professorship deals with the planning and analysis of service processes in the healthcare sector. The modeling, analysis and optimization of practical problems using quantitative methods in the areas of business analytics and operations management are at the forefront of its activities. The research work is carried out in close cooperation with practitioners.
Our research profile
Central research questions deal with process, resource, quality and information management. Our research activities are divided into the following two research areas.
Resource Planning In this research area, we deal with the optimal short, medium and long-term allocation of resources within medical processes. This includes duty and resource planning in the medical and nursing service as well as training planning for prospective specialists. In addition, there are issues relating to operating room planning, including the upstream emergency department, downstream intensive care capacities and the underlying appointment allocation.
Data Science and Decision Making In the research area of Data Science and Decision Making, the Chair of Data Science attempts to use methods and machine learning processes, primarily but not exclusively in the healthcare sector, to analyze existing data and derive appropriate recommendations for action. This data originates, for example, from hospital information systems and, depending on the application, can include occupancy and treatment data or even working times and procedure durations.
Main research areas
- Resource planning
- Personnel resource planning
- Operating room planning
- Patient flow optimization
- Appointment scheduling systems
- Medical decision support
- AI in healthcare
- Home Care
List of Publications
Flexible shift scheduling of healthcare workers using branch and price
Flexible shift scheduling of healthcare workers using branch and price
Scarce, scarcer, scarcest: Sensitivity-flexible AI-based planning of elective surgeries for efficient and effective intensive care resource management
Scarce, scarcer, scarcest: Sensitivity-flexible AI-based planning of elective surgeries for efficient and effective intensive care resource management
Analyzing the accuracy of variable returns to scale data envelopment analysis models
Analyzing the accuracy of variable returns to scale data envelopment analysis models
Airborne pollen grain detection from partially labelled data utilising semi-supervised learning
Airborne pollen grain detection from partially labelled data utilising semi-supervised learning
Machine Learning–Supported Prediction of Dual Variables for the Cutting Stock Problem with an Application in Stabilized Column Generation
Machine Learning–Supported Prediction of Dual Variables for the Cutting Stock Problem with an Application in Stabilized Column Generation
Simulation of the mortality after different ex ante (secondary) and ex post (tertiary) triage methods in people with disabilities and pre-existing diseases
Simulation of the mortality after different ex ante (secondary) and ex post (tertiary) triage methods in people with disabilities and pre-existing diseases
Simulation der Letalität nach verschiedenen Ex-ante- und Ex-post-Triage-Verfahren bei Menschen mit Behinderungen und Vorerkrankungen
Simulation der Letalität nach verschiedenen Ex-ante- und Ex-post-Triage-Verfahren bei Menschen mit Behinderungen und Vorerkrankungen
Covid-19 triage in the emergency department 2.0
Covid-19 triage in the emergency department 2.0
Stable annual scheduling of medical residents using prioritized multiple training schedules to combat operational uncertainty
Stable annual scheduling of medical residents using prioritized multiple training schedules to combat operational uncertainty
Optimized planning of nursing curricula in dual vocational schools focusing on the German health care system
Optimized planning of nursing curricula in dual vocational schools focusing on the German health care system
„Triagegesetz“ – Regelung mit fatalen Folgen
„Triagegesetz“ – Regelung mit fatalen Folgen
Digitale Personaleinsatzplanung in ambulanten und stationären anästhesiologischen Versorgungseinrichtungen: Ergebnisse einer Online-Umfrage
Digitale Personaleinsatzplanung in ambulanten und stationären anästhesiologischen Versorgungseinrichtungen: Ergebnisse einer Online-Umfrage
Alumni
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Alumni - Wissenschaft
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Alumni - Praxis
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Contact the professorship
Opening hours
Postal address
Prof. Dr. Jens O. Brunner
University of Siegen
School of Economic Disciplines III,
Business Information Systems and Business Law
Professorship of Management Science
US-D 425
Kohlbettstr. 15
57072 Siegen
Visitor address
Prof. Dr. Jens O. Brunner
Professorship of Management Science
US-D 425
Kohlbettstr. 15
57072 Siegen
Secretariat
Please contact Prof. Dr. Jens O. Brunner.