Advertisement

How Do Missing Patients Aggravate Emergency Department Overcrowding? A Real Case and a Simulation Study

Conference paper
First Online:
Part of the Springer Proceedings in Mathematics & Statistics book series (PROMS, volume 169)

Abstract

Emergency department overcrowding has been reported over decades around the globe and the phenomenon is observed to be worsening in recent years. The overcrowding issue will hinder critically-ill patients from accessing timely and adequate medical services, and may result in unnecessary deaths of emergency patients. Furthermore, it may lead to patient dissatisfaction due to the many hours of waiting for consultation. While most studies suggest that there is a mismatch between demand and supply for emergency care and this is the primary factor for the phenomenon, reducing system inefficiency is a possible way to relieve the overcrowding situation when the demand and supply are not adjustable. In this paper, we study the impacts of missing patients, referring to the patients who are not present at the time that they are called for consultation. We conduct a real case study and a simulation study of an emergency department in Hong Kong. We found that even if there is only a small proportion of missing patients and their missing time is short, there is a significant increase in patient waiting time. We suggest that emergency departments should consider to adopt information technology to reduce the inefficiency due to missing patients.

Keywords

Emergency Department Real Case Study Triage Nurse Wale Hospital Triage Category 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
This is a preview of subscription content, log in to check access.

Notes

Acknowledgements

The research of the first author is supported by Microsoft Research Asia Collaborative Research Fund FY15-RES-THEME-049 and Macao Science and Technology Development Fund 088/2013/A3. The research of the second author is partially supported by GRF grant 414313 from the Hong Kong Research Grant Council. The authors would also like to thank Mr. Stones Wong, Operations Manager of the Emergency Department of the Prince of Wales Hospital, for his assistance in data collection.

References

  1. Ahmed, M.A., Alkhamis, T.M.: Simulation optimization for an emergency department healthcare unit in Kuwait. Eur. J. Oper. Res. 198 (3), 936–942 (2009)CrossRefzbMATHGoogle Scholar
  2. American College of Emergency Physicians. Efficiency in the Emergency Department: Doing things faster without sacrificing quality. ACEP Reference and Resource Guide (2004)Google Scholar
  3. Australasian College for Emergency Medicine: Policy document — standard terminology. Emerg. Med. 14, 337–340 (2002)Google Scholar
  4. Baesler, F.F., Jahnsen, H.E., DaCosta, M.: The use of simulation and design of experiments for estimating maximum capacity in an emergency room. In: Proceedings of the 2003 Winter Simulation Conference, pp. 1903–1906 (2003)Google Scholar
  5. Brailsford, S.C., Harper, P.R., Patel, B., Pitt, M.: Analysis of the academic literature on simulation and modelling in health care. J. Simul. 3, 130–140 (2009)CrossRefGoogle Scholar
  6. Chung, C.H.: Emergency department misuse and administrative interventions. Hong Kong J. Emerg. Med. 7 (4), 220–229 (2000)Google Scholar
  7. Cochran, J.K., Roche, K.T.: A multi-class queuing network analysis methodology for improving hospital emergency department performance. Comput. Oper. Res. 36 (5), 1497–1512 (2009)CrossRefzbMATHGoogle Scholar
  8. Connelly, L.G., Bair, A.E.: Discrete event simulation of emergency department activity: a platform for system-level operations research. Acad. Emerg. Med. 11 (11), 1177–1185 (2004)CrossRefGoogle Scholar
  9. Cowan, R.M., Trzeciak, S.: Clinical review: emergency department overcrowding and the potential impact on the critically ill. Crit. Care 9 (3), 291–295 (2005)CrossRefGoogle Scholar
  10. Derlet, R.W., Richards, J.R.: Overcrowding in the nation’s emergency departments: complex causes and disturbing effects. Ann. Emerg. Med. 35 (1), 63–68 (2000)CrossRefGoogle Scholar
  11. Derlet, R.W., Richards, J.R., Kravitz, R.L.: Frequent overcrowding in US emergency departments. Acad. Emerg. Med. 8 (2), 151–155 (2001)CrossRefGoogle Scholar
  12. Fetter, R.B., Thompson, J.D.: The simulation of hospital systems. Oper. Res. 13 (5), 689–711 (1965)CrossRefGoogle Scholar
  13. Gallagher, E.J., Lynn, S.G.: The etiology of medical gridlock: causes of emergency department overcrowding in New York City. J. Emerg. Med. 8 (6), 785–790 (1990)CrossRefGoogle Scholar
  14. Günal, M.M., Pidd, M.: Discrete event simulation for performance modelling in health care: a review of the literature. J. Simul. 4 (1), 42–51 (2010)CrossRefGoogle Scholar
  15. Green, L.V., Soares, J., Giglio, J.F., Green, R.A.: Using queueing theory to increase the effectiveness of emergency department provider staffing. Acad. Emerg. Med. 13 (1), 61–68 (2008)CrossRefGoogle Scholar
  16. Hing, E., Bhuiya, F.A.: Wait Time for Treatment in Hospital Emergency Departments, 2009. US Department of Health and Human Services, Centers for Disease Control and Prevention, National Center for Health Statistics (2012)Google Scholar
  17. Hoot, N.R., Aronsky, D.: Systematic review of emergency department crowding: causes, effects, and solutions. Ann. Emerg. Med. 52 (2), 126–136 (2008)CrossRefGoogle Scholar
  18. Hoot, N.R., LeBlanc, L.J., Jones, I., Levin, S.R., Zhou, C., Gadd, C.S., Aronsky, D.: Forecasting emergency department crowding: a discrete event simulation. Ann. Emerg. Med. 52(5), 116–125 (2008)CrossRefGoogle Scholar
  19. Horwitz, L.I., Bradley, E.H.: Percentage of US emergency department patients seen within the recommended triage time: 1997 to 2006. Arch. Intern. Med. 169 (20), 1857–1865 (2009)CrossRefGoogle Scholar
  20. Huang, Y.C., Chu, C.P., Lin, Y.S., Kuo, C.H.: RFID Applications in Hospitals—A Case Study for Emergency Department (2010)Google Scholar
  21. Hulshof, P.J., Kortbeek, N., Boucherie, R.J., Hans, E.W., Bakker, P.J.: Taxonomic classification of planning decisions in health care: a structured review of the state of the art in OR/MS. Health Syst. 1 (2), 129–175 (2012)CrossRefGoogle Scholar
  22. Hwang, U., McCarthy, M.L., Aronsky, D., Asplin, B., Crane, P.W., Craven, C.K., Epstein, S.K., Fee, C., Handal, D.A., Pines, J.M., Rathlev, N.K., Schafermeyer, R.W., Zwemer, F.L., Bernstein, S.L.: Measures of crowding in the emergency department: a systematic review. Acad. Emerg. Med. 18 (5), 527–538 (2011)CrossRefGoogle Scholar
  23. Jahangirian, M., Naseer, A., Stergioulas, L., Young, T., Eldabi, T., Brailsford, S., Patel, B., Harper, P.: Simulation in health-care: lessons from other sectors. Oper. Res. 12, 45–55 (2012)Google Scholar
  24. Jun, J.B., Jacobson, S.H., Swisher, J.R.: Application of discrete-event simulation in health care clinics: a survey. J. Oper. Res. Soc. 50 (2), 109–123 (1999)CrossRefzbMATHGoogle Scholar
  25. Kuo, Y.H., Rado, O., Lupia, B., Leung, J.M., Graham, C.A.: Improving the efficiency of a hospital emergency department: a simulation study with indirectly imputed service-time distributions. Flex. Serv. Manuf. J. 28 (1), 120–147 (2016)CrossRefGoogle Scholar
  26. Lane, D.C., Monefeldt, C., Rosenhead, J.V.: Looking in the wrong place for healthcare improvements: a system dynamics study of an accident and emergency department. J. Oper. Res. Soc. 51 (5), 518–531 (2000)CrossRefzbMATHGoogle Scholar
  27. Mayhew, L., Smith, D.: Using queuing theory to analyse the Government’s 4-h completion time target in accident and emergency departments. Health Care Manag. Sci. 11 (1), 11–21 (2008)CrossRefGoogle Scholar
  28. Miro, O., Antonio, M.T., Jimenez, S., De Dios, A., Sanchez, M., Borras, A., Milla, J.: Decreased health care quality associated with emergency department overcrowding. Eur. J. Emerg. Med. 6 (2), 105–107 (1999)CrossRefGoogle Scholar
  29. Pérez, M.M., Cabrero-Canosa, M., Hermida, J.V., García, L.C., Gómez, D.L., González, G.V., Herranz, I.M.: Application of RFID technology in patient tracking and medication traceability in emergency care. J. Med. Syst. 36 (6), 3983–3993 (2012)CrossRefGoogle Scholar
  30. Rado, O., Lupia, B., Leung, J.M., Kuo, Y.H., Graham, C.A.: Using simulation to analyze patient flows in a hospital emergency department in Hong Kong. In: Proceedings of the International Conference on Health Care Systems Engineering, pp. 289–301 (2014)Google Scholar
  31. Rainer, T.: Why are Hong Kong’s emergency departments so understaffed? Emerg. Physicians Int. 11, 26–27 (2013)Google Scholar
  32. Rais, A., Viana, A.: Operations research in healthcare: a survey. Int. Trans. Oper. Res. 18 (1), 1–31 (2011)MathSciNetCrossRefGoogle Scholar
  33. Richardson, L.D., Hwang, U.: Access to care a review of the emergency medicine literature. Acad. Emerg. Med. 8 (11), 1030–1036 (2001)CrossRefGoogle Scholar
  34. Rossetti, M.D., Trzcinski, G.F., Syverud, S.A.: Emergency department simulation and determination of optimal attending physician staffing schedules. In: Proceedings of the 1999 Winter Simulation Conference, pp. 1532–1240 (1999)Google Scholar
  35. Saghafian, S., Hopp, W.J., Van Oyen, M.P., Desmond, J.S., Kronick, S.L.: Patient streaming as a mechanism for improving responsiveness in emergency departments. Oper. Res. 60 (5), 1080–1097 (2012)CrossRefzbMATHGoogle Scholar
  36. Shih, F.Y., Huel-Ming, M., Chen, S.C., Wang, H.P., Fang, C.C., Shyu, R.S., Huang, G.T., Wang, S.M.: ED overcrowding in Taiwan: facts and strategies. Am. J. Emerg. Med. 17 (2), 198–202 (1999)CrossRefGoogle Scholar
  37. Turner, J., Mehrotra, S., Daskin, M.S.: Perspectives on health-care resource management problems. In: A Long View of Research and Practice in Operations Research and Management Science, pp. 231–247 (2010)Google Scholar
  38. United Christian Hospital (2014): DREAMS. http://www3.ha.org.hk/uch/hospital/show.asp?c=spIQDS Accessed 16 February 2015

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Stanley Ho Big Data Decision Analytics Research CentreChinese University of Hong Kong, ShatinHong KongChina
  2. 2.Department of Systems Engineering and Engineering ManagementChinese University of Hong Kong, ShatinHong KongChina
  3. 3.Accident and Emergency Medicine Academic UnitChinese University of Hong Kong, ShatinHong KongChina

Personalised recommendations

Cite paper

Buy options