Optimizing ER Flow: Strategies and Insights from An Emirates Case Study
| International Journal of Industrial Engineering |
| © 2024 by SSRG - IJIE Journal |
| Volume 11 Issue 2 |
| Year of Publication : 2024 |
| Authors : Mahmoud Z. Mistarihi, Abdulla Alhammadi, Mohamed Al Hammadi, Rashed Al Breiki, Manar Suliman, Khaled Saleh, Hamad Al Mansoori |
10.14445/23499362/IJIE-V11I2P102
How to Cite?
Mahmoud Z. Mistarihi, Abdulla Alhammadi, Mohamed Al Hammadi, Rashed Al Breiki, Manar Suliman, Khaled Saleh, Hamad Al Mansoori, "Optimizing ER Flow: Strategies and Insights from An Emirates Case Study," SSRG International Journal of Industrial Engineering, vol. 11, no. 2, pp. 16-30, 2024. Crossref, https://doi.org/10.14445/23499362/IJIE-V11I2P102
Abstract:
Overcrowding and long wait times in emergency departments are serious issues that can impact patient safety and health. Reduced waiting time, on the other hand, allows the system to provide faster services in such emergencies. Therefore, the main objective of this study was to apply the discrete event simulation method and DMAIC to reduce patient waiting time, overcrowding, and system efficiency in the emergency department of Burjeel Hospital. The results showed that the average waiting time can be reduced from 37.88 minutes to 29.36 minutes. Furthermore, the reduced waiting time helped decrease the number of patients inside the ED by three at one time, leading to less ED overcrowding. Moreover, the overall average system efficiency was improved. In addition, the proposed reconfiguration of Burjeel's Hospital Emergency Department (ED) aims to enhance patient flow and resource utilization. By introducing specialized treatment pathways and nurse allocation strategies, the hospital seeks to address waiting time challenges and improve overall efficiency. Expected outcomes include reduced wait times and improved patient outcomes. Advanced methodologies such as Data Envelope Analysis (DEA) will assist in selecting the most effective scenario for optimized ED performance.
Keywords:
Emergency department, Simulation, Waiting time, Utilization, ED, DMAIC.
References:
[1] Astrid Guttmann et al., “Association Between Waiting Times and Short-Term Mortality and Hospital Admission After Departure From Emergency Department: Population-Based Cohort Study From Ontario,” Canada,” British Medical Journal, pp. 1-8, 2011.
[CrossRef] [Google Scholar] [Publisher Link]
[2] Drew B. Richardson, “Increase in Patient Mortality at 10 Days Associated with Emergency Department Overcrowding,” The Medical Journal of Australia, vol. 184, no. 5, pp. 213-216, 2006.
[CrossRef] [Google Scholar] [Publisher Link]
[3] Alexander Kolker, “Process Modeling of Emergency Department Patient Flow: Effect of Patient Length of Stay on Ed Diversion,” Journal of Medical Systems, vol. 32, no. 5, pp. 389-401, 2008.
[CrossRef] [Google Scholar] [Publisher Link]
[4] Sharan Srinivas, Roland Paul Nazareth, and Md. Shoriat Ullah, “Modeling and Analysis of Business Process Reengineering Strategies for Improving Emergency Department Efficiency,” Simulation, vol. 99, no. 1, pp. 3-18, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[5] Chantal Baril, Viviane Gascon, and Dominic Vadeboncoeur, “Discrete-Event Simulation and Design of Experiments to Study Ambulatory Patient Waiting Time in an Emergency Department,” Journal of the Operational Research Society, vol. 70, no. 12, pp. 2019-2038, 2019.
[CrossRef] [Google Scholar] [Publisher Link]
[6] V. Babashov et al., “Reducing Patient Waiting Times for Radiation Therapy and Improving the Treatment Planning Process: A Discrete-Event Simulation Model (Radiation Treatment Planning),” Clinical Oncology, vol. 29, no. 6, 385-391, 2017.
[CrossRef] [Google Scholar] [Publisher Link]
[7] Aregawi yemane Meresa, Hagazi Abrha Heniey, and Kidane Gidey, “Performance Measurement and Improvement of Healthcare Service Using Discrete Event Simulation in Bahir Dar Clinic,” Industrial and Manufacturing Engineering, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[8] Niamat Ullah Ibne Hossain et al., “Reducing Patient Waiting Time in an Outpatient Clinic: A Discrete Event Simulation (Des) Based Approach, In Proceedings of the 2017 Industrial and Systems Engineering Conference (IISE), pp. 241-246, 2017.
[Google Scholar] [Publisher Link]
[9] Junwen Wang et al., “Reducing Length of Stay in Emergency Department: A Simulation Study At A Community Hospital,” IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans, vol. 42, no. 6, pp. 1314-1322, 2012.
[CrossRef] [Google Scholar] [Publisher Link]
[10] Leonardo Bedoya-Valencia, and Emre Kirac, “Evaluating Alternative Resource Allocation in an Emergency Department Using Discrete Event Simulation,” Simulation, vol. 92, no. 12, pp. 1041-1051, 2016.
[CrossRef] [Google Scholar] [Publisher Link]
[11] A. Komashie, and Ali Mousavi, “Modeling Emergency Departments Using Discrete Event Simulation Techniques,” Proceedings of the Winter Simulation Conference, Orlando, FL, USA, 2005.
[CrossRef] [Google Scholar] [Publisher Link]
[12] Qingjin Peng et al., “Evaluation of Physician in Triage Impact on Overcrowding in Emergency Department Using Discrete-Event Simulation,” Journal of Project Management, vol. 5, no. 4, pp. 211-226, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[13] Christine Duguay, and Fatah Chetouane, “Modeling and Improving Emergency Department Systems using Discrete Event Simulation,” Simulation, vol. 83, no. 4, no. 311-320, 2007.
[CrossRef] [Google Scholar] [Publisher Link]
[14] Aliyu Isah Aliyu, Tukur Abdulkadir Sulaiman and Abdullahi Yusuf, “Modeling and Simulation Analysis of Health Care Appointment System Using Arena,” International Journal of Science and Applied Information Technology, vol. 4, no. 1, pp. 1-7, 2015.
[Google Scholar] [Publisher Link]
[15] Dong-Shang Chang Chang et al., “Improving Waiting Time for Surgical Rooms Using Workflow and the Six-Sigma Method,” Total Quality Management and Business Excellence, vol. 31, pp. 869-886, 2018.
[CrossRef] [Google Scholar] [Publisher Link]
[16] Ali Al Owad, M.A. Karim, and Lin Ma, “Integrated Lean Six Sigma Approach for Patient Flow Improvement in Hospital Emergency Department,” Advanced Materials Research, vol. 834-836, pp. 1893-1902, 2013.
[CrossRef] [Google Scholar] [Publisher Link]
[17] W.D. Lin, X. Jin, and S.Y. Chia, “Simulation Based Lean Six Sigma Approach to Reduce Patients Waiting Time in an Outpatient Eye Clinic,” 2014 IEEE International Conference on Industrial Engineering and Engineering Management, Selangor, Malaysia, pp. 394-398, 2014.
[CrossRef] [Google Scholar] [Publisher Link]
[18] E.V. Gijo, and Jiju Antony, “Reducing Patient Waiting Time in Outpatient Department using Lean Six Sigma Methodology,” Quality and Reliability Engineering International, vol. 30, no. 8, pp. 1481-1491, 2013.
[CrossRef] [Google Scholar] [Publisher Link]
[19] Nurul Fadly Habidin, Noor Zakiah Yahya, and Mohd Fahmi Shukur Ramli, “Using LSS DMAIC in Improving Emergency Department Waiting Time,” International Journal of Pharmaceutical Sciences Review and Research, vol. 35, no. 2, pp. 151-155, 2015.
[Google Scholar] [Publisher Link]
[20] Sandra L. Furterer, “Applying Lean Six Sigma Methods to Reduce Length of Stay in a Hospital’s Emergency Department,” Quality Engineering, vol. 30, no. 3, pp. 389-404, 2018.
[CrossRef] [Google Scholar] [Publisher Link]
[21] Peter B. Southard, Charu Chandra, and Sameer Kumar, “RFID in Healthcare: a Six Sigma DMAIC and Simulation Case Study,” International Journal of Health Care Quality Assurance, vol. 25, no. 4, pp. 291-321, 2012.
[CrossRef] [Google Scholar] [Publisher Link]
[22] Qian Yu, and Kai Yang, “Hospital Registration Waiting Time Reduction Through Process Redesign,” International Journal of Six Sigma and Competitive Advantage, vol. 4, no. 3, pp. 240-253, 2008.
[CrossRef] [Google Scholar] [Publisher Link]
[23] Dorsaf Daldoul et al., “A Stochastic Model to Minimize Patient Waiting Time in an Emergency Department,” Operations Research for Health Care, vol. 18, pp. 16-25, 2018.
[CrossRef] [Google Scholar] [Publisher Link]
[24] Nemat A. Hussein et al., “Mitigating Overcrowding in Emergency Departments Using Six Sigma and Simulation: A Case Study in Egypt,” Operations Research for Health Care, vol. 15, pp. 1-12, 2017.
[CrossRef] [Google Scholar] [Publisher Link]
[25] Widya Setia Findari, and Yohanes Anton Nugroho, “Design Improvement of Queuing System Using Simulation and Six Sigma: A Case Study,” International Journal of Applied Business and Information Systems, vol. 3, no. 1, pp. 1-8, 2019.
[Google Scholar] [Publisher Link]
[26] Soori Sasanfar, Morteza Bagherpour, and Afrooz Moatari-Kazerouni, “Improving Emergency Departments: Simulation-Based Optimization of Patients Waiting Time and Staff Allocation in an Iranian Hospital,” International Journal of Healthcare Management, vol. 14, no. 4, pp. 1449-1456, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[27] Kimsy Gulhane, “Enhancing Queuing Efficiency using Discrete Event Simulation,” International Journal of Logistics Systems and Management, vol. 36, no. 4, pp. 531-546, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[28] Alperen Bal, Cemil Ceylan, and Caner Taçoğlu, “Using Value Stream Mapping and Discrete Event Simulation to Improve Efficiency of Emergency Departments,” International Journal of Healthcare Management, vol. 10, no. 3, pp. 196-206, 2017.
[CrossRef] [Google Scholar] [Publisher Link]
[29] Gustavo Teodoro Gabriel et al., “Lean Thinking By Integrating With Discrete Event Simulation and Design of Experiments: An Emergency Department Expansion,” PeerJ Computer Science, vol. 6, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[30] Abbas Al-Refaie et al., “Applying Simulation and Dea to Improve Performance of Emergency Department in A Jordanian Hospital,” Simulation Modelling Practice and Theory, vol. 41, pp. 59-72, 2014.
[CrossRef] [Google Scholar] [Publisher Link]