Integrating Model-Based Systems Engineering With Lean Management to Optimize Patient Flow in a Hospital Endoscopy Center: A Simulation-Based Retrospective Case Study in China

Background: Endoscopy centers worldwide are experiencing increasing demand for cancer screening, leading to prolonged patient wait times, staff burnout, and overcrowded environments. Traditional quality improvement methods, such as Lean management, often struggle to maintain consistency across documents, visualize complex workflows, and predict outcomes before implementation. Model-Based Systems Engineering (MBSE), a graphical, model-driven approach widely used in aerospace, may offer advantages for optimizing healthcare processes; however, the application of MBSE in this setting remains unexplored. This simulation-based retrospective study uses data from the post-pandemic recovery period (2022), when many healthcare systems were operating under maximum strain, to evaluate an optimization framework that integrates MBSE with the value-based healthcare paradigm. The findings represent simulated projections rather than results from an implemented intervention; thus, prospective validation through pilot implementation is recommended before widespread adoption. Objective: To apply MBSE integrated with Lean management to optimize patient flow in a hospital endoscopy center and to evaluate the potential impact on total patient visit time, waiting time, staff overtime, and patient density using discrete-event simulation. Methods: We conducted a simulation-based, single-center retrospective case study at the endoscopy center of a tertiary hospital in Jinan, China. All pre-optimization data were collected from May to December 2022. Following the MagicGrid MBSE methodology, we modeled the current (“as-is”) patient journey using SysML diagrams. Lean tools including value stream mapping, root cause analysis (RCA), and a 531-scoring system were applied to identify waste and generate system requirements. An optimized (“to-be”) model was developed across six subsystems and simulated in AnyLogic using discrete-event simulation with 20 Monte Carlo iterations. The model was validated using historical data fitting (2019–2022) and sensitivity analysis. A second scenario with additional equipment investment was also evaluated. A third conservative scenario (50% implementation effectiveness) was added to reflect realistic implementation conditions. The primary outcomes were total patient visit time, waiting time, staff overtime, and patient density, reported with 95% confidence intervals (CIs). Results: The first optimization scenario projected mean total patient visit time from 69.1 minutes (historical baseline) to 53.7 minutes (95% CI: 52.9–54.5), a simulated reduction of 22.3%; waiting time from 19.5 minutes to 10.8 minutes (95% CI: 10.3–11.3), a simulated reduction of 44.7%; patient density from 20.2 to 15.1 per 1000 m2 (95% CI: 14.6–15.6), a simulated reduction of 25.2%; and projected elimination of staff overtime (from 88.2 to 0 minutes/day). The second scenario further projected reducing visit time to 48.5 minutes (95% CI: 47.8–49.2) and enabling 6 additional patients per day, with a projected five-year net profit of CNY 5.49 million (USD 0.823 million) under the specified assumptions. Scenario 3 (conservative, 50% realization) projected a total visit time of 61.4 minutes (95% CI: 60.5–62.3), an 11.0% reduction; waiting time of 15.6 minutes (95% CI: 14.8–16.4), a 20.0% reduction; and staff overtime of 22.1 minutes (95% CI: 18.5–25.7), a 75% reduction. Model validation showed that simulation output fell within ±5% of historical data for baseline conditions, and additional validation metrics, including queue behavior, peak crowding, daily throughput, and overtime distribution, confirmed model credibility. Conclusion: This simulation-based study shows that integrating MBSE with Lean management can substantially improve endoscopy center efficiency within the value-based healthcare framework. The MBSE + Lean approach offers a consistent, visual, and simulation-supported methodology that addresses key limitations of document-based management. However, the findings are simulated projections rather than implementation outcomes; therefore, prospective validation through a pilot implementation is recommended before widespread adoption. The conservative scenario suggests that meaningful improvements are achievable even with partial implementation.