STREAMLINING OUTPATIENT CLINIC PERFORMANCE: SIMULATION MODELING FOR INCOMPLETE DATA HANDLING

The study focuses on addressing the challenge of handling missing or incomplete data points in complex and dynamic healthcare systems during data collection. Its objective is to tackle the issue of processing missing data in real-life system simulation and propose improvement conditions that would optimize and reduce the patients’ waiting time. The study develops a customized model based on hospital requirements and effectively tackles the issue of incomplete data using OptQuest, which evaluates statistical outputs from the simulation and identifies optimal parameters for model distribution. To validate and verify the model, historical data from an outpatient clinic are used, specifically aiming to reduce patient waiting time. A comparison is made between the optimized simulation model and the existing data for verification purposes. The results obtained by simulation modeling demonstrate significant improvements in all key performance indicators compared to the existing system analysis, highlighting potential reductions in waiting time of patients.