A Distance Integrated Triage System for Crowded Health Centers

  • Kambombo MtongaEmail author
  • Willie Kasakula
  • Santhi Kumaran
  • Kayalvizhi Jayavel
  • Jimmy Nsenga
  • Chomora Mikeka
Conference paper
Part of the Learning and Analytics in Intelligent Systems book series (LAIS, volume 7)


Due to overcrowding in hospital waiting rooms, queue abandonment by frustrated patients remains a great problem. In the out-patient department, patients are normally served on a first-come-first-serve policy. Since there exists a distance decay association, whereby patients living further away from healthcare facilities experience worse health outcomes, it is these patients that are likely to return home without medical assistance. In the developing world, health facilities are few and scattered such that patients walk long distance to reach to the nearest health center. Triage can play an important role to ensure that such patients have a better chance to access medical care. Unfortunately, all the existing triage systems do not consider patient distance. In this paper, we propose a distance integrated triage system. We propose using patient distance as a queue shuffling variable. The patient’s vitals are captured by a kit of bio-sensors. This is unlike the existing triage systems that are associated with mis-triage due to lack of discriminator use or numerical miscalculations. Our work is based on the Charlotte Maxeke Johannesburg Academic Hospital triage system which is based on the Cape Triage System.


Patient triage Overcrowded waiting room Queue abandonment Patient distance Internet of things Vital signs 


  1. 1.
    Fontanesi, J.M., DeGuire, M., et al.: Application of workflow analysis tools in outpatient primary care settings. Jt Comm. J. Qual. Improv. 26, 654–660 (2000)Google Scholar
  2. 2.
    Tan, K.W., Lau, H.C., Lee F.C.Y.: Improved patient length-of-stay in emergency department through dynamic queue management. In: Winter Simulations Conference (WSC), Washington, DC, pp. 2362–2373 (2013)Google Scholar
  3. 3.
    Dong, S.L., Bullard, M.J., Meurer, D.P., Blitz, S., Ohinmaa, A., Holroyd, B.R., Rowe, B.H.: Reliability of computerized emergency triage. Acad. Emerg. Med. 13(3), 269–275 (2016)CrossRefGoogle Scholar
  4. 4.
    Kelly, C., Hulme, C., Farragher, T., et al.: Are differences in travel time or distance to healthcare for adults in global north countries associated with an impact on health outcomes? A systematic review. BMJ Open 6, e013059 (2016). Scholar
  5. 5.
    Nicholl, J., West, J., Goodacre, S., Turner, J.: The relationship between distance to hospital and patient mortality in emergencies: an observational study. Emerg. Med. J. 24, 665–668 (2007)CrossRefGoogle Scholar
  6. 6.
  7. 7.
    Hui, M.K., Tse, D.K.: What to tell consumers in waits of different length: an integrative model of service evaluation. J. Mark. 60(2), 81–90 (1996)CrossRefGoogle Scholar
  8. 8.
    Pruyn, A., Smidts, A.: Effects of waiting on the satisfaction with the service: beyond objective time measures. Int. J. Res. Mark. 15(4), 321–334 (1998)CrossRefGoogle Scholar
  9. 9.
    Batt, R.J., Terwiesch, C.: Waiting patiently: an empirical study of queue abandonment in an emergency department. Manag. Sci. 61(1), 39–59 (2005). Scholar
  10. 10.
    Shah, S. Patel, A., Rumoro, D.P., Hohmann, S., Fullam, F.: Managing patient expectations at emergency department triage. Patient Exp. J. 2(2) (2015). Scholar
  11. 11.
    Abo-Zahhad, M., Ahmed, S.M., Elnahas, O.: A wireless emergency telemedicine system for patients monitoring and diagnosis. Int. J. Telemed. Appl. 11 (2014)., Article ID 380787CrossRefGoogle Scholar
  12. 12.
    Michael, C., et al.: Morden triage in the emergency department. Deutches Arzteblatt Int. 107(50), 892–898 (2010)Google Scholar
  13. 13.
    Gottschalk, S.B., Wood, D., DeVries, S., Wallis, L.A.: The cape triage score: a new triage system. Emerg. Med. J. 23, 149–153 (2006)CrossRefGoogle Scholar
  14. 14.
    Goldstein, L.N., Morrow, L.M., Sallie, T.A., Gathoo, K., Alli, K., Mothopeng, T.M., Samodien, F.: The accuracy of nurse performance of the triage process in a tertiary hospital emergency department in Gauteng Province, South Africa. S. Afr. Med. J. 107, 243–247 (2017)CrossRefGoogle Scholar
  15. 15.
    Macharia, P.M., Ouma, P.O., Gogo, P.M., Snow, R.W., Noor, A.M.: Spatial accessibility of basic public health services in South Sudan. Geospatial Health 12, 510 (2017)CrossRefGoogle Scholar
  16. 16.
    Knight, V.C., McNulty, A.: Triage in a public outpatient sexual health clinic. Sex Health 3(2), 87–90 (2006)CrossRefGoogle Scholar
  17. 17.
    Pereira, S., et al.: Predicting triage waiting time in maternity emergency care by mean of data mining. In: New Advances in Information Systems and Technologies. Advances in Intelligent Systems and Computing, vol. 445. Springer, ChamGoogle Scholar
  18. 18.
    Michalowski, W., et al.: Design and development of a mobile system for supporting emergency triage. Methods Inf. Med. 44(1), 14–24 (2005)CrossRefGoogle Scholar
  19. 19.
    Chong, H.A., Gan, K.B.: Development of automated triage system for emergency medical service. In: International Conference on Advances in Electrical, Electronic and Systems Engineering (ICAEES), Putrajaya, pp. 642–645 (2016).
  20. 20.
    Azeez, D., Gan, K.B., Ali, M.A.M., Ismail, M.S.: Secondary triage classification using an ensemble random forest technique. Technol. Health Care 23(4), 419–428 (2015)CrossRefGoogle Scholar
  21. 21.
    Diesfeld, H.J.: The definition of the hospital catchment area and its population as a denominator for the evaluation of hospital returns in developing countries. Int. J. Epidemiol. 2(1), 47–53 (1973). Scholar
  22. 22.
    Birkin, M., Clarke, G.P., Clarke, M.: GIS for business and service planning. In: Longley, P.A., Goodchild, M.F., Maguire, D.J., Rhind, D.W. Geographical Information Systems: Principles Techniques Management and Applications, 2 Abridged edn. Wiley, New York (2005)Google Scholar
  23. 23.
    Kate, Z., et al.: Determining health-care facility catchment areas in Uganda using data on malaria-related visits. Bull. World Health Organ. 92, 178–186 (2014)CrossRefGoogle Scholar
  24. 24.
    Nadine, S., Robert, S.F., Stefan, C.G., Darrin, G.: Defining rational hospital catchments for non-urban areas based on travel-time. Int. J. Health Geogr. (2006).
  25. 25.
    Shaikh, B.T., Hatcher, J.: Health-seeking behaviour and health service utilization in Pakistan: challenging the policy makers. J. Public Health 27, 49–54 (2004)CrossRefGoogle Scholar
  26. 26.
    Hjortsberg, C.A., Mwikisa, C.N.: Cost of access to health services in Zambia. J. Health Policy Plann. 17, 71–77 (2002)CrossRefGoogle Scholar
  27. 27.
    Gilmour, S.J.: Identification of hospital catchment areas using clustering: an example from the NHS. Health Serv. Res. 45(2), 497–513 (2010)CrossRefGoogle Scholar
  28. 28.
    Jimenez-Meza, A., Aramburo-Lizarraga, J., Fluente, E.D.L.: Framework for estimating travel time, distance, speed, and street segment level of service (LOS), based on GPS data. Procedia Technol. 7(4), 61–70 (2013)CrossRefGoogle Scholar
  29. 29.
    Kayalvizhi, J., Nagarajan, V., Sharma, G.: An analysis of iot test beds with application in the field of medicine and health care. Res. J. Pharm. Tech. 10(12), 4155–4161 (2017)CrossRefGoogle Scholar
  30. 30.
  31. 31.
    Burgess, E.W.: The Urban Community. University of Chicago Press, Chicago (1926)Google Scholar
  32. 32.
    Person, P.H.: Geographic variation in first admission rates to a state mental hospital. Public Health Rep. (Washington, D.C.: 1896) 77(8), 719–731 (1962)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Kambombo Mtonga
    • 1
    Email author
  • Willie Kasakula
    • 1
  • Santhi Kumaran
    • 1
  • Kayalvizhi Jayavel
    • 2
  • Jimmy Nsenga
    • 1
  • Chomora Mikeka
    • 3
  1. 1.African Center of Excellence in Internet of ThingsUniversity of RwandaKigaliRwanda
  2. 2.Department of Information TechnoloySRM Institute of Science and TechnologyChennaiIndia
  3. 3.Physics DepartmentUniversity of MalawiZombaMalawi

Personalised recommendations