A stochastic appointment scheduling system on multiple resources with dynamic call-in sequence and patient no-shows for an outpatient clinic

• Published in: European journal of operational research 2014-12, Vol.239 (2), p.427-436
• Main Authors: Tsai, Pei-Fang Jennifer, Teng, Guei-Yu
• Format: Article
• Language: English
• Subjects: Appointment scheduling; Assignment problem; Dynamical systems; Dynamics; Estimating techniques; Health services utilization; Mathematical models; OR in health services; Outpatient care facilities; Overbooking; Patient no-shows; Patients; Physical therapy; Quality of service; Schedules; Scheduling; Stochastic models; Stochastic processes; Stochasticity; Studies; Therapy
• ISSN: 0377-2217; 1872-6860
• DOI: 10.1016/j.ejor.2014.04.032

•We study an outpatient appointment scheduling problem with dynamic call-in and patient no-shows.•A stochastic approach is used to find best block for the current patient to minimize total costs.•The model is available for both single and multiple resources.•Two methods are proposed to estimate the cost of overflow patients waiting for multiple resources.•Numerical results show that this approach outperforms traditional rule-based systems. This research focuses on the stochastic assignment system motivated by outpatient clinics, especially the physical therapy in rehabilitation service. The aim of this research is to develop a stochastic overbooking model to enhance the service quality as well as to increase the utilization of multiple resources, like therapy equipment in a physical therapy room, with the consideration of patients’ call-in sequence. The schedule for a single-service period includes a fixed number of blocks of equal length. When patients call, they are assigned to an appointment time for that block, and an existing appointment is not allowed to be changed. In each visit, a patient might require more than one resource and a probability of no-show. Two estimation methods were proposed for the expected waiting and overtime cost with multiple resources: Convolution Estimation Method and Joint Cumulative Estimation Method for the upper and lower bound value; respectively. A numerical example based on a physical therapy room was used to show that this stochastic model was able to schedule patients for better profitability compared with traditional appointment systems based on four prioritization rules. The workload in each appointment slot was more balanced albeit more patients were assigned to the first slot to fill up the empty room.