APPLICATION OF MULTI-SERVER QUEUING MODEL TO ANALYZETHE QUEUING SYSTEM OF OPD DURING COVOD-19 PANDEMIC: A CASE STUDY
Keywords:
Covid-19, multi-server queuing model, hospital, outpatient department (OPD), pandemic.Abstract
The purpose of this research paper was to suggest the optimum service level of queuing system of reception and the outpatient department during COVID-19 pandemic. The data was collected from the reception and OPD of the ABC public hospital of Hyderabad. Data included, the arrival times, service times of patients and number of doctors and receptionist at the workplace, their salaries and waiting cost of patients. Input analysis of patients` arrivals and service was conducted by in input analyzer of Rockwell Arena software. TORA optimization software was used for the calculation of performance measures. Various costs of queuing system were calculated in MS Excel and the required graphs were also plotted. After the in-depth analysis, it was revealed that one receptionist and one doctor should be increased to bring optimality in the queuing system and patients` flow. After this decision, waiting cost of patients decreased to greater extent.
Downloads
References
Adaora .D., O. (2013). Application of Queuing Models To Customers Management in the Banking System (A Case Study of United Bank for Africa, Okpara Avenue Branch Enugu). Caritas University Enugu.
Afzal, U., & Yusuf, A. (2013). The State of Health in Pakistan: An Overview. The Lahore Journal of Economics, 18(September), pp 233–247.
Agyei, W., Asare-darko, C., & Odilon, F. (2015). Modeling and Analysis of Queuing Systems in Banks : A case study of Ghana Commercial Bank Ltd. Kumasi Main Branch. International Journal of Scientific & Technology Research, 4(07), pp 160–163.
Ahmad, N., Khattak, M. K., Khattak, K. F., Ullah, F., Khattak, A., Rehman, M., … Shah, A. (2013). Health conditions: Analysis of patients ‘social problems at public hospitals in southern region of Khyber Pakhtunkhwa. Gomal University Journal of Research, 2(2), pp 47–54.
Armony, M., Israelit, S., Mandelbaum, A., Marmor, Y. N., Tseytlin, Y., & Yom-Tov, G. B. (2015). On patient flow in hospitals: A data-based queueing-science perspective. Stochastic Systems, 5(1), pp 146–194. https://doi.org/10.1214/14-SSY153
Bastani, P. (2009). A Queueing Model of Hospital Congestion. Simon Praser University. Bergman, A. (2011). Health and Social Work-Private Secotr hospitals. Washington DC. Callen, M., Gulzar, S., Hasanain, A., Khan, A. R., Khan, Y., & Mehmood, M. Z. (2013).
Improving Public Health Delivery in Punjab, Pakistan: Issues and Opportunities. The Lahore Journal of Economics, 18, pp 249–269.
Cho, K. W., Kim, S. M., Chae, Y. M., & Song, Y. U. (2017). Application of queueing theory to the analysis of changes in outpatients’ waiting times in hospitals introducing EMR. Healthcare Informatics Research, 23(1), pp 35–42. https://doi.org/10.4258/hir.2017.23.1.35
Connelly, L. G., & Bair, A. E. (2004). Discrete event simulation of emergency department activity: A platform for system-level operations research. Academic Emergency Medicine, 11(11), pp 1177–1185. https://doi.org/10.1197/j.aem.2004.08.021
Felix Albert, I. (2007). Queuing Theory For Healthcare Operations Management: A Case Study of University of Benin Health Center and Faith Mediplex.
Fitzsimmons, J. A., Fitzsimmons, M. J., & Bordoli, S. (2008). Service management: operations, strategy, and information technology. (7th ed.). NewYork: McGraw-Hill New York, NY.
Fomundam, S., & Herrmann, J. (2007). A survey of queuing theory applications in healthcare. ISR Technical Report. Retrieved from http://drum.lib.umd.edu/bitstream/handle/1903/7222/tr_2007-24.pdf
Green, L. (2006). Queuing Analysis in Healthcare. In In Patient flow: Reducing Delay in Healthcare Delivery (pp. 281–307). Springer, Boston, MA. https://doi.org/10.1007/978- 0-387-33636-7
Green, L. (2011). Queueing theory and modeling. In Handbook of healthcare delivery
systems (pp. 1–22).
Haghighinejad, H. A., Kharazmi, E., Hatam, N., Yousefi, S., Ali Hesami, S., Danaei, M., &Askarian, M. (2016). Using Queuing Theory and Simulation Modelling to Reduce Waiting Times in An Iranian Emergency Department. IJCBNM January, 44(11), pp 11– 26.
Jen, G. H.-H., Chen, S.-Y., Chang, W.-J., Chen, C.-N., Yen, A. M.-F., & Chang, R.-E.
(2021). Evaluating medical capacity for hospitalization and intensive care unit of COVID-19: A queue model approach. Journal of the Formosan Medical Association. Elsevier Ltd. https://doi.org/10.1016/j.jfma.2021.05.002
Kalwar, M. A., Khan, M. A., & Malik, A. J. (2020). Formulation of Mathematical Model for Maximization of Profit: Case of Leather Fotowear Company. International Research Journal of Computer Science and Technology, 1(1), pp 54–70.
Kalwar, M. A., Khaskheli, S. A., Khan, M. A., Siddiqui, A. A., & Gopang, M. A. (2018). Comfortable Waiting Time of Patients at the OPD with Varying Demographics. Industrial Engineering Letters, 8(2), pp 20–27. Retrieved from https://core.ac.uk/download/pdf/234685697.pdf
Kalwar, M. A., Mari, S. I., Memon, M. S., Tanwari, A., & Siddiqui, A. A. (2020). Simulation Based Approach for Improving Outpatient Clinic Operations. Mehran University Research Journal of Engineering and Technology, 39(1), pp 153–170. https://doi.org/10.22581/muet1982.2001.15
Kalwar, M. A., Marri, H. B., Khan, M. A., & Khaskheli, S. A. (2021). Applications of Queuing Theory and Discrete Event Simulation in Health Care Units of Pakistan. International Journal of Science and Engineering Investigations, 10(109), pp 6–18.
Kandemir-Cavas, C., & Cavas, L. (2007). An Application of Queueing Theory to the Relationship Between Insulin Level and Number of Insulin Receptors. Turkish Journal of Biochemistry, 32(1), pp 32–38.
Kembe, M. M., Onah, E. S., & Iorkegh, S. (2012). A Study of Waiting And Service Costs of A Multi- Server Queuing Model In A Specialist Hospital. International Journal Of Scientific & Technology Research, 1(8), pp 19–23.
Khaskheli, S. A. (2018). Optimization of Serving Costs in Two Public Sector Hospitals by Using Multi-Server Queuing Model. Mehran University of Engineering and Technology. Khaskheli, S. A., Marri, H. B., Nebhwani, M., Khan, M. A., & Ahmed, M. (2020). Compartive Study of Queuing Systems of Medical Out Patient Departments of Two Public Hospitals. In Proceedings of the International Conference on Industrial Engineering and Operations Management (Vol. 1913, pp. 2702–2720). Dubai, UAE.
Retrieved from http://www.ieomsociety.org/ieom2020/papers/177.pdf
Kissani, I., & Rifai, M. (2015). Modeling Dispatching Buses with High Service Level. In International Conference on Industrial Engineering and Operations Management (pp. 771–775).
Kumar, S., & Bano, S. (2017). Comparison and Analysis of Health Care Delivery Systems: Pakistan versus Bangladesh. Journal of Hospital & Medical Management, 03(01), pp 1–
https://doi.org/10.4172/2471-9781.100020
Latha Lavanya, B., & Ahmed, N. (2015). A Study to Find the Level of Satisfaction of Patients in Hospitals. IOSR Journal Of Humanities And Social Science, 20(7), pp 61–76. https://doi.org/10.9790/0837-20756176
Musgrove, P., Creese, A., Preker, A., Baeza, C., Anell, A., & Prentice, T. (2000). Health Systems: Improving Perfomance. World Health Organization. https://doi.org/10.1146/annurev.ecolsys.35.021103.105711
Mustafa, S., & Nisa, S. u. (2015). A Comparison of Single Server and Multiple Server Queuing Models in Different Departments of Hospitals Saima. Joural of Mathematics, 47(1), pp 73–80.
Mwangi, S. K., & Ombuni, T. M. (2015). An empirical analysis of queuing model and queuing behaviour in relation to customer satisfaction at Jkuat Students Finance Office. American Journal of Theoretical and Applied Statistics, 4(4), pp 233–246. https://doi.org/10.11648/j.ajtas.20150404.12
Naz, A., Daraz, U., Khan, T., Khan, W., & Hussain, M. (2012). An Analytical Study Of Patients ’ Health Problems In Public Hospitals Of Khyber Pakhtunkhwa Pakistan. International Journal of Business and Social Science, 3(5), pp 133–143.
Obamiro, J. K. (2010). Queuing Theory and Patient Satisfaction: An Overview of Terminology and Application in Ante-Natal Care Unit. Petroleum-Gas University of Ploiesti Bulletin, LXII(1), pp 1–12. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&profile=ehost&scope=site&authtyp e=crawler&jrnl=12246832&AN=52918232&h=9VzpxEyGmooRC74IgfkTpZvkzYH8U J6vSCPokRPEuPZyC6gezJ5Jv8PggmRpSkurfIyoXFzPYt5CyqJJoPot0g==&crl=c
Obulor, R., & B.O, E. (2016). Outpatient Queuing Model Development for Hospital Appointment System. International Journal of Scientific Engineering and Applied Science (IJSEAS), 2(4), pp 15–22.
Olorunsola, S. A., Adeleke, R. A., & Ogunlade, T. O. (2014). Queueing Analysis of Patient Flow in Hospital. IOSR Journal of Mathematics, 10(4), pp 47–53.
Puoza, J. C., & Hoggar, E. K. (2014). Patients Flowin Health Care Centers: An Overview of Terminology and Application in the Out Patient Department (OPD) Julius. International Journal of Innovative and Applied Research, 2(Issue (9): 5-1), pp 5–11.
Saima Mustafa, S. un N. (2015). A Comparison of Single Server and Multiple Server Queuing Models in Different Departments of Hospitals, 47(1), pp 73–80.
Uriarte, A. G., Zuniga, E. R., Moris, M. U., & Ng, A. H. C. (2015). System design and improvement of an emergency department using Simulation-Based Multi-Objective Optimization. Journal of Physics: Conference Series, 616(1), pp 12–15. https://doi.org/10.1088/1742-6596/616/1/012015
Varma, S. P. (2016). Waiting Time Reduction in a Local Health Care Centre Using Queueing Theory. IOSR Journal of Mathematics, 12(1), pp 95–100. https://doi.org/10.9790/5728- 121495100
Wang, T., Guinet, A., Belaidi, A., & Besombes, B. (2009). Modelling and simulation of emergency services with ARIS and Arena. case study: The emergency department of Saint Joseph and Saint Luc hospital. Production Planning and Control, 20(6), pp 484–495. https://doi.org/10.1080/09537280902938605
Winston, W. . (2004). Queuing Theory. Operations Research, 3, pp 1051–1144.
Yusuff, S. A. (2015). Analysis of Expected , Actual Waiting Time and Service Delivery : Evidence from Nigeria Banking Industry. The International Journal Of Humanities & Social Studies, 3(1), pp 398–402.
Downloads
Published
How to Cite
Issue
Section
License
You are free to:
- Share — copy and redistribute the material in any medium or format for any purpose, even commercially.
- Adapt — remix, transform, and build upon the material for any purpose, even commercially.
- The licensor cannot revoke these freedoms as long as you follow the license terms.
Under the following terms:
- Attribution — You must give appropriate credit , provide a link to the license, and indicate if changes were made . You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
Notices:
You do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable exception or limitation .
No warranties are given. The license may not give you all of the permissions necessary for your intended use. For example, other rights such as publicity, privacy, or moral rights may limit how you use the material.
