A Decision Support System for Nurse Rostering Using Stints and Integer Programming

Harold Tiemessen (), Samuel Kolb (), Reinhard Bürgy (), Adrian Stämpfli () and Vanessa Toscan ()
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Harold Tiemessen: Eastern Switzerland University of Applied Sciences
Samuel Kolb: POLYPOINT AG
Reinhard Bürgy: POLYPOINT AG
Adrian Stämpfli: Eastern Switzerland University of Applied Sciences
Vanessa Toscan: Eastern Switzerland University of Applied Sciences

A chapter in Operations Research Proceedings 2024, 2025, pp 393-398 from Springer

Abstract: Abstract Offering a healthy work-life-balance to its employees is a big challenge for healthcare institutions. This is particular true for employees that work in shifts, like nurses. Negative effects of shift work can be reduced by implementing a participation process that offers employees opportunities to shape their working schedule. We present a Decision Support System (DSS) that allows nurses to enter their working time preferences in an app. Heart of the DSS is a Mixed Integer Linear Programming model that uses stints (predefined sequences of shifts and rest days) as decision variables. Stints allow easy formulation of complex working time regulations and working time preferences. We use a construction heuristic to create a large set of potentially promising and useful stints for each nurse. This automatically generated stint set might be extended by shift patterns proposed by the nurse. We have tested our DSS in real-life settings in multiple hospitals and nursing homes in Switzerland and Liechtenstein. Using our DSS, the shift planners find better rosters in shorter time. Planners usually only need to make minor adjustments (typically due to undocumented or soft information) before rosters are released. The participatory approach led to great acceptance among nurses, planners, and healthcare institutions.

Keywords: Decision Support Systems; Nurse Rostering; Mathematical Programming (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/978-3-031-92575-7_56

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