Hostname: page-component-78c5997874-v9fdk Total loading time: 0 Render date: 2024-11-11T10:09:08.410Z Has data issue: false hasContentIssue false
  • English
  • Français

MATHEMATICAL MODELING: THE CASE OF EMERGENCY DEPARTMENT WAITING TIMES

Published online by Cambridge University Press:  26 April 2012

Morgan E. Lim ,
Tim Nye ,
James M. Bowen ,
Jerry Hurley ,
Ron Goeree  and
Jean-Eric Tarride
Morgan E. Lim
Affiliation:
McMaster University email: limme@mcmaster.ca
Tim Nye
Affiliation:
McMaster University
James M. Bowen
Affiliation:
McMaster University
Jerry Hurley
Affiliation:
McMaster University
Ron Goeree
Affiliation:
McMaster University
Jean-Eric Tarride
Affiliation:
McMaster University
Get access Rights & Permissions [Opens in a new window]

Extract

A decision analytic model often comprises a significant part of a health technology assessment. As health technology assessment in the hospital setting evolves, there is an increased need for modeling methods that account for patient care pathways and interactions between patients and their environment. For example, an evaluation of a computed tomography (CT) scanner for a new indication would need to consider the current and increased demand of the machine and how that may affect service in other areas of the hospital. This problem solving approach views “problems” through a systems perspective.

Type
ASSESSMENTS
Information
International Journal of Technology Assessment in Health Care , Volume 28 , Issue 2 , April 2012 , pp. 93 - 109
Copyright
Copyright © Cambridge University Press 2012

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

1.Ahmed, MA, Alkhamis, TM. Simulation optimization for an emergency department healthcare unit in Kuwait. Eur J Oper Res. 2009;198:936–942.CrossRefGoogle Scholar
2.Beck, E, Balasubramanian, H, Henneman, PL. Resource management and process change in a simplified model of the emergency department. Proceedings of the 2009 Winter Simulation Conference (WSC 2009). University of Massachusetts Amherst, Amherst, MA: IEEE; 2009:1887-1895.CrossRefGoogle Scholar
3.Bernstein, SL, Aronsky, D, Duseja, R, et al. The effect of emergency department crowding on clinically oriented outcomes. Acad Emerg Med. 2009;16:1–10.CrossRefGoogle ScholarPubMed
4.Bonabeau, E. Agent-based modeling: Methods and techniques for simulating human systems. Proc Natl Acad Sci U S A. 2002;99:7280–7287.CrossRefGoogle ScholarPubMed
5.Bond, K, Ospina, MB, Blitz, S, et al. Frequency, determinants and impact of overcrowding in emergency departments in Canada: A national survey. Healthc Q. 2007;10:32–40.CrossRefGoogle ScholarPubMed
6.Bossuyt, PM, Reitsma, JB, Bruns, DE, et al. Towards complete and accurate reporting of studies of diagnostic accuracy: The STARD initiative. Clin Radiol. 2003;58:575–580.CrossRefGoogle ScholarPubMed
7.Brailsford, S. Tutorial: Advances and challenges in healthcare simulation modelling. Proceedings of the 2007 Winter Simulation Conference, Washington, DC; 2007;1436-1448.CrossRefGoogle Scholar
8.Brailsford, S. System dynamics: What's in it for healthcare simulation modelers. Proceedings of the 2008 Winter Simulation Conference, Miami, FL; 2008:1478-1483.CrossRefGoogle Scholar
9.Brailsford, SC, Lattimer, VA, Tarnaras, P, Turnbull, JC. Emergency and on-demand health care: Modelling a large complex system. J Oper Res Soc. 2004;55:34–42.CrossRefGoogle Scholar
10.Carter, MW, Lapierre, SD. Scheduling emergency room physicians. Health Care Manage Sci. 2001;4:347–360.CrossRefGoogle ScholarPubMed
11.Coats, TJ, Michalis, S. Mathematical modelling of patient flow through an accident and emergency department. Emerg Med J. 2001;18:190–192.CrossRefGoogle ScholarPubMed
12.Cochran, JK, Roche, KT. A multi-class queuing network analysis methodology for improving hospital emergency department performance. Comput Oper Res. 2009;36:1497–1512.CrossRefGoogle Scholar
13.Connelly, LG, Bair, AE. Discrete event simulation of emergency department activity: A platform for system-level operations research. Acad Emerg Med. 2004;11:1177–1185.Google ScholarPubMed
14.Duguay, C, Chetouane, F. Modeling and improving emergency department systems using discrete event simulation. Simulation. 2007;83:311–320.CrossRefGoogle Scholar
15.Ferrin, D, McBroom, D, Miller, M. Maximizing hospital financial impact and emergency department throughput with simulation. Proceedings of the 2007 Winter Simulation Conference, Washington, DC; 2007:1566-1573.CrossRefGoogle Scholar
16.Fone, D, Hollinghurst, S, Temple, M, et al. Systematic review of the use and value of computer simulation modelling in population health and health care delivery. J Public Health Med. 2003;25:325–335.CrossRefGoogle ScholarPubMed
17.Gunal, M, Pidd, M. Understanding accident and emergency department performance using simulation. Proceedings for the 2006 Winter Simulation Conference, Monterey, CA; 2006:446-452.CrossRefGoogle Scholar
18.Guttmann, A, Schull, MJ, Vermeulen, MJ, Stukel, TA. Association between waiting times and short term mortality and hospital admission after departure from emergency department: Population based cohort study from Ontario, Canada. BMJ. 2011;342:d2983.CrossRefGoogle ScholarPubMed
19.Hillier, F, Lieberman, G. Introduction to operations research. 8th ed.New York: McGraw Hill; 2004.Google Scholar
20.Holm, LB, Dahl, FA. Simulating the effect of physician triage in the emergency department of Akershus University Hospital. Proceedings of the 2009 Winter Simulation Conference (WSC 2009), Austin, TX; 2009:1896-1905.CrossRefGoogle Scholar
21.Hoot, N, Aronsky, D. Systematic review of emergency department crowding: Causes, effects and solutions. Ann Emerg Med. 2008;52:126–136.CrossRefGoogle ScholarPubMed
22.Hung, GR, Whitehouse, SR, O'Neill, C, Gray, AP, Kissoon, N. Computer modeling of patient flow in a pediatric emergency department using discrete event simulation. Pediatr Emerg Care. 2007;23:5–10.CrossRefGoogle Scholar
23.Jun, JB, Jacobson, SH, Swisher, J. Application of discrete-event simulation in health care clinics: A survey. J Oper Res Soc. 1999;50:109–123.CrossRefGoogle Scholar
24.Kelton, W, Sadowski, R, Sturrock, D. Simulation with arena. 4th ed.New York: McGraw Hill; 2007.Google Scholar
25.Khadem, M, Bashir, H, Al-Lawati, Y, Al-Azri, F. Evaluating the layout of the emergency department of a public hospital using computer simulation modeling: A case study. Proceedings of the 2008 IEEE, Singapore; 2008:1709-1713.CrossRefGoogle Scholar
26.Khare, RK, Powell, ES, Reinhardt, G, Lucenti, M. Adding more beds to the emergency department or reducing admitted patient boarding times: Which has a more significant influence on emergency department congestion? Ann Emergency Med. 2009;53:575–585.CrossRefGoogle Scholar
27.Kolb, E, Peck, J. Reducing emergency department overcrowding - Five patient buffer concepts in comparison. Proceedings of the 2008 Winter Simulation Conference, Miami, FL; 2008:1516-1525.CrossRefGoogle Scholar
28.Komashie, A, Mousavi, A. Modeling emergency departmens using discrete event simulation techniques. Proceedings from the 2005 Winter Simulation Conference, Orlando, FL; 2005:2681-2685.Google Scholar
29.Lane, DC, Monefeldt, C, Rosenhead, JV. Looking in the wrong place for healthcare improvements: A system dynamics study of an accident and emergency department. J Oper Res Soc. 2000;51:518–531.CrossRefGoogle Scholar
30.Laskowski, M, McLeod, RD, Friesen, MR, Podaima, BW, Alfa, AS. Models of emergency departments for reducing patient waiting times. PLoS One. 2009;4:e6127.CrossRefGoogle ScholarPubMed
31.Law, A, Kelton, W. Basic simulation modeling. Simulation modeling and analysis. 3rd ed.New York: McGraw Hill; 2000:1–105.Google Scholar
32.Macal, C, North, M. Tutorial on agent-based modeling and simulation part 2: How to model with agents. Proceedings of the 2006 Winter Simulation Conference, Monterey, CA; 2006:73-83.CrossRefGoogle Scholar
33.Mahapatra, S, Koellig, C, Patvivatsiri, L, et al. Pairing emergency severity index level triage data with computer aided system design to improve emergency department access and throughput. Proceedings of the 2003 Winter Simulation Conference, New Orleans, LA; 2003:1917-1925.Google Scholar
34.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. 2008;11:11–21.CrossRefGoogle ScholarPubMed
35.Medeiros, D, Swenson, E, DeFlitch, C. Improving patient flow in a hospital emergency department. Proceedings of the 2008 Winter Simulation Conference, Miami, FL; 2008:1526-1531.CrossRefGoogle Scholar
36.Meng, L-Y, Spedding, T. Modeling patient arrivals when simulating an accident and emergency unit. Proceedings of the 2008 Winter Simulation Conference, Miami, FL; 2008:1509-1515.Google Scholar
37.Mustafee, N, Katsaliaki, , Taylor, K, SJE, . Profiling literature in healthcare simulation. Simulation. 2010;86:543–558.CrossRefGoogle Scholar
38.Nielsen, AL, Hilwig, H, Kissoon, N, Teelucksingh, S. Discrete event simulation as a tool in optimization of a professional complex adaptive system. Stud Health Technol Inform. 2008;136:247–252.Google ScholarPubMed
39.Pines, JM, Localio, AR, Hollander, JE, et al. The impact of emergency department crowding measures on time to antibiotics for patients with community-acquired pneumonia. Ann Emerg Med. 2007;50:510–516.CrossRefGoogle ScholarPubMed
40.Puente, J, Gomez, A, Parreno, J, de la Fuente, D. Applying a fuzzy logic methodology to waiting list management at a hospital emergency unit: A case study. Int J Healthc Technol Manag. 2003;5:432–442.CrossRefGoogle Scholar
41.Research Into Global Healthcare Tools (RIGHT). Modelling and simulation techniques for supporting healthcare decision making: A selection framework. Cambridge: University of Cambridge: Engineering Design Centre; 2009.Google Scholar
42.Ruohonen, T, Neittanmaki, P, Teittinen, J. Simulation model for improving the operation of the emergency department of special healthcare. Proceedings of the 2006 Winter Simulation Conference, Monterey, CA: 2006:453-458.CrossRefGoogle Scholar
43.Schulz, KF, Altman, DG, Moher, D. CONSORT 2010 statement: Updated guidelines for reporting parallel group randomised trials. BMJ. 2010;340:c332.CrossRefGoogle ScholarPubMed
44.Stahl, JE. Modelling methods for pharmacoeconomics and health technology assessment: An overview and guide. Pharmacoeconomics. 2008;26:131–148.CrossRefGoogle ScholarPubMed
45.Storrow, AB, Zhou, C, Gaddis, G, Han, JH, Miller, K, et al. Decreasing lab turnaround time improves emergency department throughput and decreases emergency medical services diversion: A simulation model. Acad Emerg Med. 2008;15:1130–1135.CrossRefGoogle ScholarPubMed
46.Takakuwa, S, Shiozaki, H. Functional analysis for operating emergency department of a general hospital. Proceedings of the 2004 Winter Simulation Conference, Washington, DC; 2004:2003-2011.Google Scholar
47.Tao, W, Guinet, A, Belaidi, A, Besombes, B. Modelling and simulation of emergency services with ARIS and Arena. Case study: The emergency department of Saint Joseph and Saint Luc Hospital. Prod Plan Control. 2009;20:484–495.Google Scholar
48.Thomas, M, Wilson, G. Applications of queuing theory. In: Zandin, K, ed. Maynard's industrial engineering handbook. 5th ed.New York: McGraw Hill Professional; 2001:11.67–11.99.Google Scholar
49.Topaloglu, S. A multi-objective programming model for scheduling emergency medicine residents. Comput Ind Eng. 2006;51:375–388.CrossRefGoogle Scholar
50.Wang, L. An agent-based simulation for workflow in the emergency department. Proceedings of the 2009 IEEE Systems and Information Engineering Design Symposium, Charlottesville, Virginia, 2009:19-23.CrossRefGoogle Scholar
51.Yeh, J-Y, Lin, WS. Using simulation technique and genetic algorithm to improve the quality care of a hospital emergency department. Expert Syst Appl. 2007;32:1073–1083.CrossRefGoogle Scholar