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BMC Health Services Research
Published in: BMC Health Services Research 1/2018

Open Access 01-12-2018 | Research article

Application of discrete event simulation in health care: a systematic review

Author: Xiange Zhang

Published in: BMC Health Services Research | Issue 1/2018

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Abstract

Background

The objective was to explore the current advances and extent of DES (Discrete Event Simulation) applied to assisting with health decision making, as well as to categorize the wide spectrum of health-related topics where DES was applied.

Methods

A systematic review was conducted of the literature published over the last two decades. Original research articles were included and reviewed if they concentrated on the topic of DES technique applied to health care management with model frameworks explicitly demonstrated. No restriction regarding the settings of DES application was applied.

Results

A total of 211 papers met the predefined inclusion criteria. The number of publications included increased significantly especially after 2010.101 papers (48%) stated explicitly disease areas targeted, the most frequently modeled of which are related to circulatory system, nervous system and Neoplasm. The DES applications were distributed unevenly into 4 major classes: health and care systems operation (HCSO) (65%), disease progression modeling (DPM) (28%), screening modeling (SM) (5%) and health behavior modeling (HBM) (2%). More than 68% of HCSO by DES were focused on specific problems in individual units. However, more attempts at modeling highly integrated health service systems as well as some new trends were identified.

Conclusions

DES technique has been an effective tool to approach a wide variety of health care issues. Among all DES applications in health care, health system operations research occupied the most considerable proportion and increased most significantly. Health Economic Evaluation (HEE) was the second most common topic for DES in health care, but with stable rather than increasing numbers of publications.
Literature
1.
Karnon J, Stahl J, Brennan A, Caro JJ, Mar J, Moller J. Modeling using discrete event simulation: a report of the ISPOR-SMDM modeling good research practices task Force-4. Med Decis Mak. 2012;32(5):701–11.CrossRef
2.
Pidd M. Computer simulation in management science. 5th ed. New York: John Wiley; 2004.
3.
Brennan A, Chick SE, Davies R. A taxonomy of model structures for economic evaluation of health technologies. Health Econ. 2006;15(12):1295–310.CrossRefPubMed
4.
Brailsford SC, Hilton NA, editors. A comparison of discrete event simulation and system dynamics for modelling healthcare systems. Operational Research Applied to Health Services (ORAHS). Glasgow: Glasgow Caledonian University; 2000.
5.
Caro JJ. Pharmacoeconamic analyses using discrete event simulation. PharmacoEconomics. 2005;23(4):323–32.CrossRefPubMed
6.
Karnon J, Stahl J, Brennan A, Caro JJ, Mar J, Moller J, et al. Modeling using discrete event simulation: a report of the ISPOR-SMDM modeling good research practices task Force-4. Value Health. 2012;15(6):821–7.CrossRefPubMed
7.
Jun JB, Jocaboson SH, Swisher JR. Application of discrete-event simulation in health care clinics: a survey. J Oper Res Soc. 1999;25(4):325–35.
8.
Gunal MM, Pidd M. Discrete event simulation for performance modelling in health care: a review of the literature. J Simul. 2010;4(1):42–51.CrossRef
9.
Mielczarek B, Uzialko-Mydlikowska J. Application of computer simulation modeling in the health care sector: a survey. Simul-T Soc Mod m. 2010;88(2):197–216.
10.
Fone D, Hollinghurst S, Temple M, Round A. Systematic review of the use and value of computer simulation modelling in population health and health care delivery. J Public Health Med. 2003;25(4):325–35.CrossRefPubMed
11.
Caro JJ, Huybrechts KF, Xenakis JG, O'Brien JA, Rajagopalan K, Lee K. Budgetary impact of treating acute bipolar mania in hospitalized patients with quetiapine: an economic analysis of clinical trials. Curr Med Res Opin. 2006;22(11):2233–42.CrossRefPubMed
12.
Mielczarek B. Review of modelling approaches for healthcare simulation. Oper Res Decisions. 2016;26(1):55–72.
13.
Lagergren M. What is the role and contribution of models to management and research in the health services a view from Europe. Eur J Oper Res. 1998;105(2):257–66.CrossRef
14.
Zhao YC, Peng QJ, Strome T, Weldon E, Zhang M, Chochinov A. Bottleneck detection for improvement of emergency department efficiency. Bus Process Manag J. 2015;21(3):564–85.CrossRef
15.
Carmen R, Defraeye M, Van Nieuwenhuyse I. A decision support system for capacity planning in emergency departments. Int J Model Simul. 2015;14(2):299–312.CrossRef
16.
Bessen T, Keefe DM, Karnon J. Does one size fit all? Cost utility analyses of alternative mammographic follow-up schedules, by risk of recurrence. Int J Technol Assess Health Care. 2015;31(5):281–8.CrossRefPubMed
17.
Stout NK, Rosenberg MA, Trentham-Dietz A, Smith MA, Robinson SM, Fryback DG. Retrospective cost-effectiveness analysis of screening mammography. J Natl Cancer Inst. 2006;98(11):774–82.CrossRefPubMed
18.
Lee CI, Cevik M, Alagoz O, Sprague BL, Tosteson AN, Miglioretti DL, et al. Comparative effectiveness of combined digital mammography and tomosynthesis screening for women with dense breasts. Radiology. 2015;274(3):772–80.CrossRefPubMed
19.
Comas M, Arrospide A, Mar J, Sala M, Vilaprinyo E, Hernandez C, et al. Budget impact analysis of switching to digital mammography in a population-based breast cancer screening program: a discrete event simulation model. PLoS One. 2014;9(5):e97459.CrossRefPubMedPubMedCentral
20.
Coelli FC, Ferreira RB, Almeida RM, Pereira WC. Computer simulation and discrete-event models in the analysis of a mammography clinic patient flow. Comput Methods Prog Biomed. 2007;87(3):201–7.CrossRef
21.
Berg B, Denton B, Nelson H, Balasubramanian H, Rahman A, Bailey A, et al. A discrete event simulation model to evaluate operational performance of a colonoscopy suite. Med Decis Mak. 2010;30(3):380–7.CrossRef
22.
Campbell LA, Blake JT, Kephart G, Grunfeld E, MacIntosh D. Understanding the effects of competition for constrained colonoscopy services with the introduction of population-level colorectal Cancer screening. Med Decis Mak. 2017;37(2):253–63.CrossRef
23.
Heim JA, Huang H, Zabinsky ZB, Dickerson J, Wellner M, Astion M, et al. Design and implementation of a combined influenza immunization and tuberculosis screening campaign with simulation modelling. J Eval Clin Pract. 2015;21(4):727–34.CrossRefPubMed
24.
van Karnebeek CDM, Mohammadi T, Tsao N, Sinclair G, Sirrs S, Stockler S, et al. Health economic evaluation of plasma oxysterol screening in the diagnosis of Niemann-pick type C disease among intellectually disabled using discrete event simulation. Mol Genet Metab. 2015;114(2):226–32.CrossRefPubMed
25.
Davies R, Roderick P, Canning C, Brailsford S. The evaluation of screening policies for diabetic retinopathy using simulation. Diabet Med. 2002;19(9):762–70.CrossRefPubMed
26.
Igarashi A, Goto R, Suwa K, Yoshikawa R, Ward AJ, Moller J. Cost-effectiveness analysis of smoking cessation interventions in Japan using a discrete-event simulation. Appl Health Econ Health Policy. 2016;14(1):77–87.CrossRefPubMed
27.
Getsios D, Marton JP, Revankar N, Ward AJ, Willke RJ, Rublee D, et al. Smoking cessation treatment and outcomes patterns simulation: a new framework for evaluating the potential health and economic impact of smoking cessation interventions. PharmacoEconomics. 2013;31(9):767–80.CrossRefPubMed
28.
Xenakis JG, Kinter ET, Ishak KJ, Ward AJ, Marton JP, Willke RJ, et al. A discrete-event simulation of smoking-cessation strategies based on varenicline pivotal trial data. PharmacoEconomics. 2011;29(6):497–510.CrossRefPubMed
29.
Brailsford SC, Harper PR, Sykes J. Incorporating human behaviour in simulation models of screening for breast cancer. Eur J Oper Res. 2012;219(3):491–507.CrossRef
30.
Brailsford S, Schmidt B. Towards incorporating human behaviour in models of health care systems: an approach using discrete event simulation. Eur J Oper Res. 2003;150(1):19–31.CrossRef
31.
Deo S, Topp SM, Garcia A, Soldner M, Yagci Sokat K, Chipukuma J, et al. Modeling the impact of integrating HIV and outpatient health services on patient waiting times in an urban health clinic in Zambia. PLoS One. 2012;7(4):e35479.CrossRefPubMedPubMedCentral
32.
Nguefack HLN, Gwet H, Desmonde S, Oukem-Boyer OOM, Nkenfou C, Tejiokem M, et al. Estimating mother-to-child HIV transmission rates in Cameroon in 2011: a computer simulation approach. BMC Infect Dis. 2016;16(11):1–11.
33.
Revankar N, Ward AJ, Pelligra CG, Kongnakorn T, Fan W, LaPensee KT. Modeling economic implications of alternative treatment strategies for acute bacterial skin and skin structure infections. J Med Econ. 2014;17(10):730–40.CrossRefPubMed
34.
Huynh N, Snyder R, Vidal JM, Sharif O, Cai B, Parsons B, et al. Assessment of the nurse medication administration workflow process. J Healthc Eng. 2016;2016:1–14.CrossRef
35.
Jahn B, Pfeiffer KP, Theurl E, Tarride JE, Goeree R. Capacity constraints and cost-effectiveness: a discrete event simulation for drug-eluting stents. Med Decis Mak. 2010;30(1):16–28.CrossRef
36.
Pendharkar SR, Bischak DP, Rogers P, Flemons W, Noseworthy TW. Using patient flow simulation to improve access at a multidisciplinary sleep Centre. J Sleep Res. 2015;24(3):320–7.CrossRefPubMed
37.
Fialho AS, Oliveira MD, Sa AB. Using discrete event simulation to compare the performance of family health unit and primary health care Centre organizational models in Portugal. BMC Health Serv Res. 2011;11:274.CrossRefPubMedPubMedCentral
38.
Tako AA, Kotiadis K, Vasilakis C, Miras A, le Roux CW. Improving patient waiting times: a simulation study of an obesity care service. Bmj Quality & Safety. 2014;23(5):373–81.CrossRef
39.
Bard JF, Shu Z, Morrice DJ, Wang DE, Poursani R, Leykum L. Improving patient flow at a family health clinic. Health Care Manag Sci. 2016;19(2):170–91.CrossRefPubMed
40.
Asamoah DA, Sharda R, Rude HN, Doran D. RFID-based information visibility for hospital operations: exploring its positive effects using discrete event simulation. Health Care Manag Sci. 2018;21(3):305–16.CrossRefPubMed
41.
Crawford EA, Parikh PJ, Kong N, Thakar CV. Analyzing discharge strategies during acute care: a discrete-event simulation study. Med Decis Mak. 2014;34(2):231–41.CrossRef
42.
Lebcir R, Demir E, Ahmad R, Vasilakis C, Southern D. A discrete event simulation model to evaluate the use of community services in the treatment of patients with Parkinson’s disease in the United Kingdom. BMC Health Serv Res. 2017;17(1):50.CrossRefPubMedPubMedCentral
43.
Santos A, Gurling J, Dvorak MF, Noonan VK, Fehlings MG, Burns AS, et al. Modeling the patient journey from injury to community reintegration for persons with acute traumatic spinal cord injury in a Canadian Centre. PLoS One. 2013;8(8):1–10.CrossRef
44.
Matta A, Li J, Sahin E, Lanzarone E, Fowler J. Editors. Proceedings of the international conference on health care systems engineering. Int Conf health care Syst Eng 2013; Milan, Italy. Bern: Springer; 2014.
45.
Chemweno P, Brackenier L, Thijs V, Pintelon L, Van Horenbeek A, Michiels D. Optimising the complete care pathway for cerebrovascular accident patients. Comput Ind Eng. 2016;93:236–51.CrossRef
46.
Soto-Gordoa M, Arrospide A, Merino Hernandez M, Mora Amengual J, Fullaondo Zabala A, Larranaga I, et al. Incorporating budget impact analysis in the implementation of complex interventions: a case of an integrated intervention for multimorbid patients within the CareWell study. Value Health. 2017;20(1):100–6.CrossRefPubMed
47.
Monks T, Worthington D, Allen M, Pitt M, Stein K, James MA. A modelling tool for capacity planning in acute and community stroke services. BMC Health Serv Res. 2016;16(1):530.CrossRefPubMedPubMedCentral
48.
Willoughby KA, Chan BTB, Marques S. Using simulation to test ideas for improving speech language pathology services. Eur J Oper Res. 2016;252(2):657–64.CrossRef
49.
Bowers J, Mould G, Marshall C. Location of services and the impact on healthcare quality: insights from a simulation of a musculoskeletal physiotherapy service. J Oper Res Soc. 2015;66(7):1212–21.CrossRef
50.
Pilgrim H, Tappenden P, Chilcott J, Bending M, Trueman P, Shorthouse A, et al. The costs and benefits of bowel cancer service developments using discrete event simulation. J Oper Res Soc. 2009;60(10):1305–14.CrossRef
51.
Katsaliaki K, Brailsford S, Browning D, Knight P. Mapping care pathways for the elderly. J Health Organ Manag. 2005;19(1):57–72.CrossRefPubMed
52.
Hartz S, Getsios D, Tao S, Blume S, Maclaine G. Evaluating the cost effectiveness of donepezil in the treatment of Alzheimer's disease in Germany using discrete event simulation. BMC Neurol. 2012;12:2.CrossRefPubMedPubMedCentral
53.
Erenay FS, Alagoz O, Banerjee R, Said A, Cima RR. Cost-effectiveness of alternative colonoscopy surveillance strategies to mitigate metachronous colorectal cancer incidence. Cancer. 2016;122(16):2560–70.CrossRefPubMedPubMedCentral
54.
Fines P, Garner R, Bancej C, Bernier J, Manuel DG. Development and implementation of microsimulation models of neurological conditions. Health Rep. 2016;27(3):3–9.PubMed
55.
Simpson KN, Pei PP, Moller J, Baran RW, Dietz B, Woodward W, et al. Lopinavir/ritonavir versus darunavir plus ritonavir for HIV infection: a cost-effectiveness analysis for the United States. PharmacoEconomics. 2013;31(5):427–44.CrossRefPubMed
56.
Standfield L, Comans T, Raymer M, O'Leary S, Moretto N, Scuffham P. The efficiency of increasing the capacity of physiotherapy screening clinics or traditional medical services to address unmet demand in Orthopaedic outpatients: a practical application of discrete event simulation with dynamic queuing. Appl Health Econ Health Policy. 2016;14(4):479–91.CrossRefPubMed
57.
Cooper K, Brailsford SC, Davies R. Choice of modelling technique for evaluating health care interventions. J Oper Res Soc. 2007;58(2):168–76.CrossRef
58.
Caro JJ, Möller J, Karnon J, Stahl J, Ishak J. Special Topics. Discrete Event Simulation for Health Technology Assessment. 1st ed. Boca Raton: CRC Press; 2016. p. 273–310.
59.
Southard PB, Chandra C, Kumar S. RFID in healthcare: a six sigma DMAIC and simulation case study. Int J Health Care Qual Assur. 2012;25(4):291–321.CrossRefPubMed
60.
Langley I, Doulla B, Lin HH, Millington K, Squire B. Modelling the impacts of new diagnostic tools for tuberculosis in developing countries to enhance policy decisions. Health Care Manag Sci. 2012;15(3):239–53.CrossRefPubMed
61.
Lee D, Wilson K, Akehurst R, Cowie MR, Zannad F, Krum H, et al. Cost-effectiveness of eplerenone in patients with systolic heart failure and mild symptoms. Heart. 2014;100(21):1681–7.CrossRefPubMedPubMedCentral
62.
Higashi H, Barendregt JJ. Cost-effectiveness of total hip and knee replacements for the Australian population with osteoarthritis: discrete-event simulation model. PLoS One. 2011;6(9):e25403.CrossRefPubMedPubMedCentral
63.
Vataire AL, Aballea S, Antonanzas F, Roijen LH, Lam RW, McCrone P, et al. Core discrete event simulation model for the evaluation of health care technologies in major depressive disorder. Value Health. 2014;17(2):183–95.CrossRefPubMed
64.
Katsaliaki K, Mustafee N. Applications of simulation within the healthcare context. J Oper Res Soc. 2011;62(8):1431–51.CrossRef
Metadata
Title
Application of discrete event simulation in health care: a systematic review
Author
Xiange Zhang
Publication date
01-12-2018
Publisher
BioMed Central
Published in
BMC Health Services Research / Issue 1/2018
Electronic ISSN: 1472-6963
DOI
https://doi.org/10.1186/s12913-018-3456-4

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