Abstract
After graduation, physicians receive further training in a medical domain like anesthesiology. There are 57 medical specialties in Germany in total. The high cost pressures of hospitals and the changing view of the medical profession regarding the work-life balance have led to recruitment problems and low employee satisfaction in many places. A promising approach to counter this problem is objective and structured training planning. This research project mainly deals with medical residents’ strategic and tactical-operative training scheduling. In addition to relieving the medical staff currently responsible for the planning process, this research project increases the predictability of structured training. This allows hospitals to increase the quality of their training and, consequently, their attractiveness to other hospitals. In addition, supervisors from different departments can better assess residents’ knowledge and thus keep the level of service, which is particularly important in hospitals, permanently high even when changing residents. From the residents’ point of view, a well-structured training schedule enables a high degree of information. Therefore, residents are no longer surprised by a short-term change of department and have a direct insight into their training progress. A real-world case study evaluates the mathematical formulations and the solution approaches.
| Original language | English |
|---|---|
| Title of host publication | Operations Research Proceedings 2022 |
| Subtitle of host publication | Selected Papers of the Annual International Conference of the German Operations Research Society (GOR), Karlsruhe, Germany, September 6-9, 2022 |
| Editors | Oliver Grothe, Stefan Nickel, Steffen Rebennack, Oliver Stein |
| Place of Publication | Cham |
| Publisher | Springer |
| Chapter | 5 |
| Pages | 35-41 |
| Number of pages | 7 |
| ISBN (Electronic) | 9783031249075 |
| ISBN (Print) | 9783031249068 |
| DOIs | |
| Publication status | Published - 2023 |
Publication series
| Name | Lecture Notes in Operations Research |
|---|---|
| Publisher | Springer, Cham |
Funding
This research project is funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) and Grant no. 405488489.
| Funders | Funder number |
|---|---|
| Deutsche Forschungsgemeinschaft | 405488489 |
| Deutsche Forschungsgemeinschaft |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- OR in health services
- Mixed integer programming
- Real-world application
- Stochastic optimization
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