185. Optimizing adaptive medical staff scheduling using recourse decisions amidst fluctuating patient demand
Contributed abstract in session ME-5: Workforce Planning, stream Regular talks.
Monday, 15:30-16:40Room: Room S6
Authors (first author is the speaker)
| 1. | Jan Schoenfelder
|
| LUMS, Lancaster University Leipzig | |
| 2. | Markus Schüller
|
| Universität Augsburg | |
| 3. | Jens Brunner
|
| Department of Technology, Management, and Economics, Technical University of Denmark |
Abstract
Scheduling medical staff during periods of fluctuating patient demand poses significant challenges, particularly during events like the COVID-19 pandemic. Current rostering practices, based on long-term expected patient load predictions, often lead to a limited ability to react to discrepancies between expected and actual patient emergences. In response to this challenge, we propose a Mixed-Integer Program (MIP) to optimize the allocation of flexible medical staff, ensuring appropriate patient care.
Our MIP framework consists of a two-stage optimization model. Firstly, it constructs the initial schedule based on forecasts of patient emergence and acuity levels provided by partners of the PROGNOSIS consortium. Secondly, it incorporates dynamic recourse decisions to adjust staffing levels in response to realized patient demand. Given the inherent uncertainty in patient demand, we evaluate scenario-based rosters using Sample-Average Approximation to provide insights into short-term adjustments in personnel scheduling.
With a temporal scope of one week, our approach addresses the immediate staffing needs of healthcare facilities, offering a practical solution for managing workload peaks and ensuring quality patient care during times of uncertainty.
Keywords
- Staffing and capacity planning
- Workforce planning and scheduling
Status: accepted
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