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
Scarce, scarcer, scarcest: performance-flexible AI-based planning of elective surgeries for efficient and effective intensive care capacity management
Scarce, scarcer, scarcest: performance-flexible AI-based planning of elective surgeries for efficient and effective intensive care capacity management
Can Machine Learning Methods Improve the Prediction of Postoperative ICU Requirements? Real-World Evidence and Practical Implications
Can Machine Learning Methods Improve the Prediction of Postoperative ICU Requirements? Real-World Evidence and Practical Implications
A roadmap for integrating fairness in personnel planning and scheduling in hospitals
A roadmap for integrating fairness in personnel planning and scheduling in hospitals
Clinical Benefits of a Randomized Allergy App Intervention in Grass Pollen Sufferers: A Controlled Trial
Clinical Benefits of a Randomized Allergy App Intervention in Grass Pollen Sufferers: A Controlled Trial
Management accountants’ roles and management controls in hospitals at times of strain — Experiences during the Corona pandemic
Management accountants’ roles and management controls in hospitals at times of strain — Experiences during the Corona pandemic
Task assignments with rotations and flexible shift starts to improve demand coverage and staff satisfaction in healthcare
Task assignments with rotations and flexible shift starts to improve demand coverage and staff satisfaction in healthcare
Prediction of Postoperative ICU Requirements: Closing the Translational Gap with a Real-World Clinical Benchmark for Artificial Intelligence Approaches
Prediction of Postoperative ICU Requirements: Closing the Translational Gap with a Real-World Clinical Benchmark for Artificial Intelligence Approaches
Customized GRASP for rehabilitation therapy scheduling with appointment priorities and accounting for therapist satisfaction
Customized GRASP for rehabilitation therapy scheduling with appointment priorities and accounting for therapist satisfaction
Flexible shift scheduling of healthcare workers using column generation
Flexible shift scheduling of healthcare workers using column generation
The AI ethics of digital COVID-19 diagnosis and their legal, medical, technological, and operational managerial implications
The AI ethics of digital COVID-19 diagnosis and their legal, medical, technological, and operational managerial implications
Managing the patient portfolio using mathematical programming
Managing the patient portfolio using mathematical programming
Optimizing physician schedules with resilient break assignments
Optimizing physician schedules with resilient break assignments
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.