Google scholar arxiv informatics ads IJAIS publications are indexed with Google Scholar, NASA ADS, Informatics et. al.

Call for Paper


March Edition 2023

International Journal of Applied Information Systems solicits high quality original research papers for the March 2023 Edition of the journal. The last date of research paper submission is February 15, 2023.

Queue Management in Non-Tertiary Hospitals for Improved Healthcare Service Delivery to Outpatients

Charity Ojochogwu Egbunu, Oluoha Onyekwere, Malik Adeiza Rufai, Terungwa Simon Yange, Sonter Pascal Atsanan in Information Sciences

International Journal of Applied Information Systems
Year of Publication:2020
Publisher: Foundation of Computer Science (FCS), NY, USA
Authors:Charity Ojochogwu Egbunu, Oluoha Onyekwere, Malik Adeiza Rufai, Terungwa Simon Yange, Sonter Pascal Atsanan
Download full text
  1. Charity Ojochogwu Egbunu, Oluoha Onyekwere, Malik Adeiza Rufai, Terungwa Simon Yange and Sonter Pascal Atsanan. Queue Management in Non-Tertiary Hospitals for Improved Healthcare Service Delivery to Outpatients. International Journal of Applied Information Systems 12(31):36-48, July 2020. URL, DOI BibTeX

    	author = "Charity Ojochogwu Egbunu and Oluoha Onyekwere and Malik Adeiza Rufai and Terungwa Simon Yange and Sonter Pascal Atsanan",
    	title = "Queue Management in Non-Tertiary Hospitals for Improved Healthcare Service Delivery to Outpatients",
    	journal = "International Journal of Applied Information Systems",
    	issue_date = "July 2020",
    	volume = 12,
    	number = 31,
    	month = "July",
    	year = 2020,
    	issn = "2249-0868",
    	pages = "36-48",
    	url = "",
    	doi = "10.5120/ijais2020451870",
    	publisher = "Foundation of Computer Science (FCS), NY, USA",
    	address = "New York, USA"


A common problem associated with hospitals especially the non-tertiary hospitals (primary and secondary hospitals) is long queue. Attempts have been made to address this using the ticket approach, however, this does not minimize crowd in and around hospitals. In the wake of the consciousness of the need to avoid crowd with the emergence of the Corona Virus (COVID-19), it has become important to note that some diseases are transmissible when people clinch close within a vicinity especially in the hospital environment. It is therefore imperative to devise a means to reduce the usual crowd witnessed at the different units/sections in the hospital, precisely by outpatients. In this study, a centralized queue control system was developed that can be used in the different sections of hospitals. The system applied Poisson Distribution, Haversine Model, Little’s Law and Kendall Notation. It is a web-based system, designed to run on the Internet as it focused on the outpatients and the fact that different sections of most non-tertiary hospitals could also be situated in different buildings or geographical area. The system was implemented using ASP.NET and Microsoft SQL. It was evaluated using data collected from non-tertiary hospitals in Benue State, Nigeria. The result showed reduced number of patients in the hospital per time and a little variation between the arrival and expected time of some patients. The system saves time for the patients, the hospital is more organized and crowds are avoided. Also, the pressure on the facilities of the hospitals at a time is also reduced significantly. Service delivery is improved and a healthier environment is assured for both patients and health workers.


  1. Adeleke, R.A., Ogunwale, O.D. and Halid O.Y. 2009. Application of Queuing Theory to Waiting Time of Outpatients in the Hospitals. Pacific journal of science and technology, 10(2): 270-274.
  2. Afolabi, M.O. and Erhun, W.O. 2005. Patients Response to waiting time in an Outpatient Pharmacy in Nigeria. Journal of pharmacy reserve, 8(2): 118-121
  3. Helbig, M., Helbig, S., Kahla-Witzsch, H., and May, A. 2009. Quality Management: Reduction of Waiting Time and Efficiency Enhancement in an ENT-University Outpatients’ Department. BMC Health Services Research, 9(21): 1-9.
  4. Ndukwe, H.C. Omale, S., and Opanuga, O. O. 2011. Reducing queues in a Nigerian Hospital Pharmacy. African Journal of Pharmacy and Pharmacology, 5(8): 1020-1026.
  5. Shanmugasundaram, S. and Umarani, P. 2015. Queuing Theory Applied in Our Day to Day Life. International Journal of Scientific & Engineering Research, 6 (4): 533-540.
  6. Eze, E. O. and Odunukwe, A. D. 2015. On Application of Queuing Models to Customers Management in Banking System. American Research Journal of Bio Sciences, 1 (2): 14-20.
  7. Bakari, H. R., Chamalwa, H. A. and Baba, A. M. (2014). Queuing Process and Its Application to Customer Service Delivery: A Case study of Fidelity Bank Plc, Maiduguri. International Journal of Mathematics and Statistics Invention (IJMSI), 2(1): 14-21.
  8. Ingole, P. V. and Nichat, M. K. 2013. Landmark Based Shortest Path Detection by Using Dijkestra Algorithm and Haversine Formula. International Journal of Engineering Research and Applications (IJERA), 3(3): 162-165.
  9. Li, D., Cova, T. J. and Dennison, P. E. 2017. Using reverse geocoding to identify prominent wildfire evacuation trigger points. Applied Geography 87: 14 – 27.
  10. Lumauag, R. G. 2016. SENT SMS: School Event Notification Through SMS. Asia Pacific Journal of Multidisciplinary Research, 4(4): 61 – 68.
  11. Mehandiratta, R. 2011. Applications of Queuing Theory in Health Care. International Journal of Computing and Business Research, 2(2): 1-11.
  12. Titarmare, N. and Yerlekar, A. 2018. A Survey on Patient Queue Management System. International Journal of Advanced Engineering, Management and Science (IJAEMS),4(4): 229-232.
  13. Ngorsed, M. and Suesaowaluk, P. 2015. Hospital Service Queue Management System with Wireless Approach. Journal of Interdisciplinary Research, 550-559.
  14. Preater, J. 2002. Queues in Health. Healthcare Management Science, 5(4): 283.
  15. Young, J. P. 1962. The Basic Model in a Queuing Theory Approach the Control of Hospital Inpatient Census. John Hopkins University, Baltimore,74-79.
  16. Bruin A. M., Bekker R., Zanten L. V. and Koole G. M. 2010. Dimensioning Hospital Wards using the Erlang Loss Model. Annals of Operations Research. 178: 23 – 24.
  17. Burungale S., Kurane K., Mhatre S., Vora D. 2018. Patient Queue Management System. International Journal of Engineering Science Invention (IJESI), 7(2): 39-41.
  18. Wangrakdiskul, U. 2014. Designing Queuing System for Public Hospitals in Thailand. Conference: Tokyo International Conference on Engineering and Applied Science, At Tokyo, Japan, 539-550
  19. Prabakaran, R. and Kumar, K. 2019. Application of Queuing Theory in Hospital Management. International Journal of Innovative Technology and Exploring Engineering (IJITEE), 8(8): 1788 – 1790.


Queue, Management, Healthcare, Service Delivery, Non-Tertiary, Outpatient