Time: Friday, 06/Sept/2024: 10:45am - 12:15pm Session Chair: Stefanie Ebel |
Location: Wirtschaftswissenschaften 0514 Room Location at NavigaTUM |
Structural insights about roommate suitability in the patient-to-room assignment problem
RWTH Aachen University, Germany
Assigning patients to rooms is a fundamental task in hospitals and, especially, within wards. This so-called patient-to-room assignment problem (PRA) has gained more and more attention in the last few years and many heuristics have been proposed with a large variety of different practical constraints reflecting different settings in hospitals. Classical objectives are avoiding patient transfers between rooms, respecting single-room requests, or choosing patients of similar age as roommates.
Apart from age difference, there are many other potential criteria for determining the roommate suitability. In this talk, we take a look at the mathematical structure of different suitability criteria and compare different strategies for integrating them into algorithms for PRA.
A Granular Approach to Optimal and Fair Patient Placement in Hospital Emergency Departments
1University of Massachusetts Chan Medical School, Worcester, MA, USA; 2Babson College, Wellesley, MA, USA; 3Massachusetts Institute of Technology, Cambridge, MA, USA; 4McKinsey & Co, USA
This work, in collaboration with a large hospital system in Massachusetts, USA, tackles the patient prioritization and placement aspects of emergency department operations with the goal of improving throughput and wait times in an equitable way. We present a novel predictive-prescriptive framework, operationalize it through an interpretable metamodel, and demonstrate increased fairness in patient prioritization.
The value of flexibility in integrated surgery and staff scheduling on a daily planning level applying a column generation heuristic
Universität Augsburg, Germany
Two of the most important, expensive and scarce resources in hospitals are physicians and operating rooms. Therefore, effective and efficient scheduling of these resources is among the most relevant planning tasks within hospitals. The decisions to be made on the daily planning level regard the sequencing of patients’ surgeries and the assignment of appropriate staff to surgeries. Since there are several interdependencies between surgery schedules and physician rosters, it is a meaningful approach to consider both planning problems within one integrated optimization problem. We provide MIP models for a column generation algorithm that solves both scheduling problems within one simultaneous solution approach to create schedules for surgeries as well as for operating room staff. We use test data based on a real-world dataset to provide meaningful insights. The algorithm leads to optimal solutions in more than 75% of all test cases and solves the problem efficiently within a desirable amount of time. We further evaluate our algorithm with respect to different aspects of flexibility in the context of surgery and staff scheduling and generate key insights about their interdependencies.