Application of systems modeling language (SysML) and discrete event simulation to address patient waiting time issues in healthcare

A robust health care system is crucial to reducing patient stress and contributing to economic growth. The future of the health care industry depends upon a reliable and efficient system to deal with the increasing number of patients. However, in today's healthcare system, patients face negative experiences as a result of long wait times. Now the pressing question is how to develop an effective healthcare system? To address this issue, this study uses Systems Modeling Language (SysML) coupled with a simulation approach to assess the performance of the healthcare system, identify the problem, and offer recommended alternatives. To elaborate, a systemic magic-grid methodology will be used to model and analyze the blood laboratory by using four pillars (structural, behavioral, requirement, and parametric) of SysML. To represent these pillars, a set of SysML diagrams will be used to visualize the layered system architecture, interactions, and activity between its different components. Furthermore, Discrete Event Simulation (DES) is utilized through Flexsim simulation software for the analysis of the parametric aspect of the system of interest. A blood laboratory within an outpatient clinic located at southern US State is considered a testing bed. The detailed architecture of the system of interest is studied, and required data are collected for modeling and simulation. The simulation results indicate that the combination of 50% Type I routes and 50% Type II routes resulted in the shortest wait times in the system of 22 min, the shortest wait times in the phlebotomist queue of 2 min, and the highest system throughput of 11369 patients per nine months. This article will provide a reference point for practitioners who want to apply the SysML approach to address health sector-related issues. More importantly, with this comprehensive approach, stakeholders of the blood laboratory system can utilize the hospital infrastructure in a more effective and optimized manner.