MBSE Driven Simulation of a Mid-Size Emergency Department Operation
Abstract
Healthcare system in the United States faces multiple issues including quality, rising cost and outcome of the healthcare care delivery process. Systems engineering methodologies and tools have been proposed to address the complexity of healthcare delivery processes as well as the challenges facing the industry, including emergency departments. However, very few initiatives have considered such promising methodology to address the current limitations and improve the quality of care. The objective of this work is to develop and validate an innovative framework based on model-based systems engineering (MBSE) and discrete-event simulation (DES) to accurately model patient flow and predict resource utilization at a mid-size emergency department. MBSE framework is developed using OMG systems modeling language (SysML); which provides a better understanding of the system, supports multiple system views, and enhances the verification and validation process. Data protocols are implemented to define data inputs and requirements. Time studies are conducted inside the ED to collect patient and human resource processing time data to run the simulation. Two discrete-event simulation models were implemented to evaluate the key performance measures of the ED system. Results are validated by comparing the output behavior of the model to the output behavior of the ED system using different data sources. The resulting simulation platform is able to predict human resources’ utilization, patient throughput and length of stay (LOS); in order to support clinical decision making (e.g. resource allocation) and improve the outcome of the emergency care delivery process. The systems engineering approach provided a better understanding of the problem, data needs and requirements, the function, the structure and the behavior of the ED system. Simulation results show an observed crowding situation at the ED, where room utilization rates range between 75\% to 100\%, and patients wait inside the ED rooms more than 55\% of the time. Results also show large utilization rates and workload for ED physicians. Sensitivity analysis was conducted on ED resources to optimize the average length of stay and the current resource allocation. Simulation results show that re-allocation of existing ED resources will result in 15\% reduction in the average LOS, and allocation of more staff to the ED will result in more than 25\% reduction in the average LOS.
Degree
M.S.M.E.
Advisors
El Mounayri, Purdue University.
Subject Area
Industrial engineering|Mechanical engineering|Medicine
Off-Campus Purdue Users:
To access this dissertation, please log in to our
proxy server.