Customized GRASP for rehabilitation therapy scheduling with appointment priorities and accounting for therapist satisfaction

Sebastian Kling (), Sebastian Kraul () and Jens O. Brunner ()
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Sebastian Kling: University of Augsburg
Sebastian Kraul: Vrije Universiteit Amsterdam
Jens O. Brunner: University of Augsburg

OR Spectrum: Quantitative Approaches in Management, 2024, vol. 46, issue 3, No 6, 872 pages

Abstract: Abstract Physical therapy in acute care hospitals plays an important role in the rehabilitation of patients. Nevertheless, the profession must deal with staff shortages caused by a lack of potential employees and absenteeism which are results of high physical and mental workloads. The therapist shortage negatively affects the total number of daily appointments the department can fulfill. For appointments that can be successfully scheduled, continuity of care with the same therapist cannot be guaranteed for individual patients. Lack of continuity of care negatively influences the therapist's satisfaction. Therapist preferences for individual appointments in general cannot always be guaranteed when designing schedules, which also hurts satisfaction. This paper develops a multi-criteria model for the daily therapy appointment-scheduling problem. The primary objective is to minimize the total sum of priority violations for unscheduled appointments. To improve therapist satisfaction, we consider therapist preferences including continuity of care as a secondary objective. Here, our integer programming formulation aims to minimize the total sum of preference violations for scheduled appointments. We are dealing with an operational planning problem with a daily planning horizon. The operational objective is to achieve therapist schedules in at most two hours. The therapists’ schedules together need to include several hundred appointments for a planning day. Due to intractability, the developed integer program cannot provide schedules for such problem sizes. Therefore, we develop a customized Greedy Randomized Adaptive Search Procedure (GRASP) with six innovative local search operations to improve an initially constructed solution. We test the heuristic algorithm on realistic data instances. The metaheuristic provides high-quality schedules for various problem sizes in short runtimes, i.e., within minutes. Comparisons with the optimal solutions for small problem instances show very good results of the GRASP with a similar number of scheduled appointments and good adherence to continuity of care and therapist preference requirements.

Keywords: Appointment scheduling; Therapist planning; Rehabilitation Department in Hospitals; GRASP heuristic; Integer programming (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s00291-023-00742-y

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