29. Swap-Stability in Nurse-to-Patient Assignment considering personal preferences
Invited abstract in session TC-2: Integrated planning, stream Sessions.
Tuesday, 13:30-15:00Room: NTNU, Realfagbygget R8
Authors (first author is the speaker)
| 1. | Bianca Lauer
|
| RWTH Aachen University | |
| 2. | Christina Büsing
|
| Lehr- und Forschungsgebiet Kombinatorische Optimierung, RWTH Aachen University | |
| 3. | Gréanne Leeftink
|
| CHOIR, University of Twente |
Abstract
In hospitals, assigning available nurses to a ward's inpatients is performed whenever a change in nurses or patients occurs. Although nurse-to-patient assignment requires considering multiple complex factors it is carried out manually in most hospitals, which is often time consuming. Suggested assignments usually aim to distribute patient workload evenly among nurses and to ensure continuity of care where possible. Yet, in practice nurses often swap patients when the given assignment does not fulfil their personal preferences. To ensure that schedules are accepted by staff, nurses’ individual preferences need to be represented in the nurse-to-patient assignment.
In this talk, we present a mathematical model that considers a fair distribution of the workload between the nurses as well as incorporating personal preferences and stability constraints, ensuring that no pair of nurses would rather swap patients. Since the nurses' preferences are mostly unknown in practice, we use incomplete preferences in the form of a traffic light system. This enables us to group patients into three sets per nurse: those the nurse would like to care for, those they would rather not be assigned to and a usually larger group of patients they feel indifferent about. The model is evaluated in a computational study making use of real-world data.
Keywords
- Workforce planning and scheduling
- Decision support
- Healthcare management
Status: accepted
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