Abstract
Keeping up a high level of primary care services for a whole country or even a federal state is a very challenging task due to the demographic change and many other reasons, also for Germany. In the future it is expected that even more general practitioners (GP) are necessary to cover close to come healthcare. Therefore, an efficient use of resources and an optimized planning is crucial. Mathematical models and approaches can help facing the challenge by determining optimal locations for practices, shift schedules or appointment strategies, for example. To use these in practice, decision support systems (DSS) are necessary that link the input data to the approaches and display the results. The outline of such a decision support system for optimally locating GP practices is presented in this paper.
| Original language | English |
|---|---|
| Title of host publication | IESS 2017: Exploring Services Science |
| Number of pages | 13 |
| Publisher | Springer Verlag |
| Publication date | 2017 |
| Pages | 210-222 |
| ISBN (Print) | 978-3-319-56924-6 |
| ISBN (Electronic) | 978-3-319-56925-3 |
| DOIs | |
| Publication status | Published - 2017 |
| Event | 8th International Conference on Exploring Service Science - Rome, Italy Duration: 24.05.2017 → 26.05.2017 Conference number: 190679 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Research Areas and Centers
- Research Area: Center for Population Medicine and Public Health (ZBV)
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