A Hybrid Simulation and the RAWEC Model for Performance Evaluation of Pharmacy Service Strategies

Abstract

Outpatient pharmacy operations frequently experience inefficiencies due to unpredictable demand, limited resources, and patient behaviors such as queue jockeying, resulting in extended wait times and reduced performance. This research introduces a hybrid framework that combines Discrete-Event Simulation (DES) with Multi-Criteria Decision-Making (MCDM) to assess and prioritize improvement strategies for complex systems. A discrete-event simulation model was created to replicate a multi-server pharmacy, incorporating realistic factors such as time-dependent patient arrivals, variable service durations, and explicit jockeying behavior. The model produced performance data for five strategies: base case, single queue, self-service kiosks, dynamic staffing, and restricted jockeying. The output metrics, including waiting time, queue length, staff utilization, throughput, and jockeying frequency, were organized into a decision matrix. The Ranking of Alternatives with Weights of Criterion (RAWEC) method, a contemporary multi-criteria decision-making technique utilizing a reward–punishment mechanism grounded in average performance, was subsequently employed to rank the strategies according to varying managerial weightings (patient-centric versus efficiency-centric). The findings indicate that the single queue strategy (A1) emerged as the optimal choice, attaining the highest rank in both patient-centric and efficiency-centric managerial frameworks. This suggests that the implementation of a single-line system is advantageous for both patient experience and operational efficiency, thereby removing the perceived trade-off between these objectives in this particular instance. The hybrid DES–RAWEC approach offers managers a robust, data-driven instrument for formulating strategic decisions that reconcile competing objectives within complex service environments, such as healthcare pharmacies.