MedProSim: A Process Mining-Based Simulation Tool for Identifying the Causes of Waiting Times in Outpatient Departments

This study aims to reduce outpatient waiting times by introducing a two-phased framework that diagnoses existing delays in an "as-is" phase and proposes operational improvement through targeted simulation in a "to-be" phase. The framework is designed to identify delay sources within patient interactions and enable data-driven adjustments to optimize patient flow. In the diagnosis phase, waiting times are categorized based on distinct patient interactions to provide a detailed analysis of delay sources. Key indicators, specifically patient arrival density, consultation interval variability, and prolonged consultation time ratio, are identified, and a dotted chart analysis is utilized to visualize delay patterns. Subsequently, scenarios targeting each indicator are developed and tested with MedProSim, a custom-built simulation tool that allows administrators to simulate potential changes prior to actual implementation. A case study conducted in the rheumatology and pulmonology departments of a Korean tertiary hospital highlights department-specific delay sources and demonstrates the effectiveness of targeted interventions. In pulmonology, patterns in patient arrival, consultation intervals, and extended consultation times are identified as significant contributors to delays. Simulated interventions, such as scheduling adjustments and grouping strategies, effectively reduced waiting times, validating the potential of the framework to improve patient flow. This study provides a structured framework with distinctive definitions of waiting times and multiple performance indicators, enabling administrators to make informed, data-driven adjustments to hospital operations.