Multi-Objective Patient Appointment Scheduling Framework (MO-PASS): a data-table input simulation-optimization approach

Appointment scheduling is one of the critical factors for improving patient satisfaction with healthcare services. A practical and robust appointment scheduling solution allows clinics to efficiently utilize medical devices, equipment, and other resources. This study introduces a Multi-Objective Patient Appointment Scheduling (MO-PASS) framework to enhance clinic operations and quality of care. The proposed framework integrates three modules: (1) Optimization (using MATLAB), (2) Data-Exchange (MS Excel), and (3) Simulation (Simio). To implement MO-PASS, the Multi-Objective Particle Swarm Optimization (MOPSO) algorithm is coded in MATLAB, and a Simio API is developed, which exchanges simulated scenarios with MOPSO via Excel. The efficiency of the proposed framework is evaluated in a breast cancer clinic with multiple physicians and patient types. Two objective functions are defined for evaluating the solutions of the AS problem: (1) minimizing the total service time and (2) maximizing the number of (admitted) patients with zero overtime. Finally, the performance of MO-PASS is tested against three heuristic approaches with respect to objective functions. The computational experiment results show that the proposed MO-PASS outperforms the existing heuristic benchmarks. Also, the framework is accompanied by all the necessary details to make it practical and easy to implement.