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Systematic Review of the Use of Computer Simulation Modeling of Patient Flow in Surgical Care

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Abstract

Computer simulation has been employed to evaluate proposed changes in the delivery of health care. However, little is known about the utility of simulation approaches for analysis of changes in the delivery of surgical care. We searched eight bibliographic databases for this comprehensive review of the literature published over the past five decades, and found 34 publications that reported on simulation models for the flow of surgical patients. The majority of these publications presented a description of the simulation approach: 91% outlined the underlying assumptions for modeling, 88% presented the system requirements, and 91% described the input and output data. However, only half of the publications reported that models were constructed to address the needs of policy-makers, and only 26% reported some involvement of health system managers and policy-makers in the simulation study. In addition, we found a wide variation in the presentation of assumptions, system requirements, input and output data, and results of simulation-based policy analysis.

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References

  1. Naylor, C. D., A different view of queues in Ontario. Health Aff. 10(3):110–128, 1991.

    Article  Google Scholar 

  2. Sobolev, B., and Kuramoto, L., Policy analysis using patient flow simulations: conceptual framework and study design. Clin. Invest. Med. 28(6):359–363, 2005.

    Google Scholar 

  3. Zellermeyer, V., Report of the surgical process analysis and improvement expert panel. Ministry of Health and Long-Term Care, Toronto, 2005.

    Google Scholar 

  4. Weinberger, M., Oddone, E. Z., Henderson, W. G., Smith, D. M., Huey, J., Giobbie-Hurder, A., et al., Multisite randomized controlled trials in health services research: scientific challenges and operational issues. Med. Care. 39(6):627–634, 2001.

    Article  Google Scholar 

  5. Aiken, L. H., Sochalski, J., and Lake, E. T., Studying outcomes of organizational change in health services. Med. Care. 35(11 Suppl):NS6–NS18, 1997.

    Article  Google Scholar 

  6. Jun, J. B., Jacobson, S. H., and Swisher, J. R., Application of discrete-event simulation in health care clinics: a survey. J. Oper. Res. Soc. 50(2):109–123, 1999.

    MATH  Google Scholar 

  7. Benneyan, J. C., An introduction to using computer simulation in healthcare: patient wait case study. J. Soc. Health Syst. 5(3):1–15, 1997.

    Google Scholar 

  8. Mahachek, A. R., An introduction to patient flow simulation for health-care managers. J. Soc. Health Syst. 3(3):73–81, 1992.

    Google Scholar 

  9. Everett, J. E., A decision support simulation model for the management of an elective surgery waiting system. Health Care Manag. Sci. 5(2):89–95, 2002.

    Article  Google Scholar 

  10. Fone, D., Hollinghurst, S., Temple, M., Round, A., Lester, N., Weightman, A., et al., Systematic review of the use and value of computer simulation modelling in population health and health care delivery. J. Public Health Med. 25(4):325–335, 2003.

    Article  Google Scholar 

  11. Law, M. A., and Kelton, W. D., Simulation modelling and analysis, 3 ed. McGraw Hill, Singapore, 2000.

    Google Scholar 

  12. Forrester, J. W., Industrial dynamics. M.I.T. Press, Cambridge, 1961.

    Google Scholar 

  13. Taylor, K., and Lane, D., Simulation applied to health services: opportunities for applying the system dynamics approach. J. Health Serv. Res. Policy. 3(4):226–232, 1998.

    Google Scholar 

  14. Bartholomew, D. J., Stochastic models for social processes, 3rd ed. Wiley, London, 1982.

    MATH  Google Scholar 

  15. Karnon, J., Alternative decision modelling techniques for the evaluation of health care technologies: Markov processes versus discrete event simulation. Health Econ. 12(10):837–848, 2003.

    Article  Google Scholar 

  16. Stevenson, M. D., Oakley, J., and Chilcott, J. B., Gaussian process modeling in conjunction with individual patient simulation modeling: a case study describing the calculation of cost-effectiveness ratios for the treatment of established osteoporosis. Med. Decis. Making. 24 (1):89–100, 2004.

    Article  Google Scholar 

  17. Banks, J., Carson, J. S. I., and Nelson, B. L., Discrete-event system simulation. Prentice-Hall, New Jersey, 2001.

    Google Scholar 

  18. Davies, R., An assessment of models of a health system. J. Oper. Res. Soc. 36(8):679–687, 1985.

    Google Scholar 

  19. Shen, W., and Norrie, D. H., Agent-based systems for intelligent manufacturing: a state-of-the-art survey. Knowledge and Information Systems. 1(2):129–156, 1999.

    Google Scholar 

  20. Hutzschenreuter, A. K., Bosman, P. A. N., Blonk-Altena, I., van Aarle, J., and La Poutré, H., Agent-based patient admission scheduling in hospitals. Richland, SC: International Foundation for Autonomous Agents and Multiagent Systems; 2008 p. 45–52.

  21. Young, T., An agenda for healthcare and information simulation. Health Care Manag. Sci. 8(3):189–196, 2005.

    Article  Google Scholar 

  22. ACM Digital Library. http://portal.acm.org/. Last accessed 29 June 2009.

  23. CINAHL. http://www.ebscohost.com/cinahl/. Last accessed 29 June 2009.

  24. EMBASE. http://www.info.embase.com/. Last accessed 29 June 2009.

  25. INFORMS. http://www.informs.org/. Last accessed 29 June 2009.

  26. INSPEC. http://www.engineeringvillage2.org/. Last accessed 29 June 2009.

  27. MathSciNet. http://www.ams.org/mathscinet/. Last accessed 29 June 2009.

  28. MEDLINE. http://www.nlm.nih.gov/databases/databases_medline.html. Last accessed 29 June 2009.

  29. Web of Science. http://scientific.thomson.com/products/wos/. Last accessed 29 June 2009.

  30. Sobolev, B., Harel, D., Vasilakis, C., and Levy, A. L., Using the statecharts paradigm for simulation of patient flow in surgical care. Health Care Manag. Sci. 11:79–86, 2008.

    Article  Google Scholar 

  31. Cooper, K., Davies, R., Roderick, P., Chase, D., and Raftery, J., The development of a simulation model of the treatment of coronary heart disease. Health Care Manag. Sci. 5(4):259–267, 2002.

    Article  Google Scholar 

  32. Tuft, S., and Gallivan, S., Computer modelling of a cataract waiting list. Brit. J. Ophthalmol. 85(5):582–585, 2001.

    Article  Google Scholar 

  33. Akkerman, R., and Knip, M., Reallocation of beds to reduce waiting time for cardiac surgery. Health Care Manag. Sci. 7(2):119–126, 2004.

    Article  Google Scholar 

  34. Altinel, I. K., and Usla, E., Simulation modeling for emergency bed requirement planning. Ann. Oper. Res. 67(1):183–210, 1996.

    Article  Google Scholar 

  35. Amladi, P., Outpatient health care facility planning and sizing via computer simulation. Proceedings of the 16th Conference on Winter Simulation; Dallas, TX: Institute of Electrical and Electronics Engineers, 1984 p. 704–711.

  36. Anderson, J. G., Harshbarger, W., Weng, H. C., Jay, S. J., and Anderson, M. M., Modeling the costs and outcomes of cardiovascular surgery. Health Care Manag. Sci. 5(2):103–111, 2002.

    Article  Google Scholar 

  37. Butler, T. W., Reeves, G. R., Karwan, K. R., and Sweigart, J. R., Assessing the impact of patient care policies using simulation analysis. J. Soc. Health Syst. 3(3):38–53, 1992.

    Google Scholar 

  38. Cipriano, L., Chesworth, B., Anderson, C., and Zaric, G., Predicting joint replacement waiting times. Health Care Manag. Sci. 10(2):195–215, 2007.

    Article  Google Scholar 

  39. Davies, R., Simulation for planning services for patients with coronary artery disease. Eur. J. Oper. Res. 71:323–332, 1994.

    Article  Google Scholar 

  40. Denton, B. T., Rahman, A. S., Nelson, H., and Bailey, A. C., Simulation of a multiple operating room surgical suite. Proceedings of the 38th Conference on Winter Simulation; Monterey, CA: Winter Simulation Conference; 2006 p. 414–424.

  41. Dexter, F., Macario, A., and Dexter, E. U., Computer simulation of changes in nursing productivity from early tracheal extubation of coronary artery bypass graft patients. J. Clin. Anesth. 10(7):593–598, 1998.

    Article  Google Scholar 

  42. Dexter, F., Marcon, E., Epstein, R. H., and Ledolter, J., Validation of statistical methods to compare cancellation rates on the day of surgery. Anesth. Analg. 101(2):465–473, 2005.

    Article  Google Scholar 

  43. Fetter, R. B., and Thompson, J. D., Simulation of hospital systems. Oper. Res. 13(5):689–711, 1965.

    Article  Google Scholar 

  44. Harper, P. R., A framework for operational modelling of hospital resources. Health Care Manag. Sci. 5(3):165–173, 2002.

    Article  MathSciNet  Google Scholar 

  45. Hunter, G., Aslan, S., and Wiget, K., Computer simulation of surgical patient movement in a medical care facility. Proceedings of the Eleventh Annual Symposium on Computer Applications in Medical Care; Washington, DC: Institute of Electrical and Electronics Engineers, 1987 p. 691–697.

  46. Kuzdrall, P. J., Kwak, N. K., and Schmitz, H. H., Simulating space requirements and scheduling policies in a hospital surgical suite. Simulation. 36(5):163–172, 1981.

    Article  Google Scholar 

  47. Kwak, N. K., Kuzdrall, P. J., and Schmitz, H. H., The GPSS simulation of scheduling policies for surgical patients. Manage. Sci. 22(9):982–989, 1976.

    Article  Google Scholar 

  48. Lim, T., Uyeno, D., and Vertinski, I., Hospital admissions systems: a simulation approach. Simulation gaming. 6(2):188–201, 1975.

    Article  Google Scholar 

  49. Lowery, J. C., Simulation of a hospital's surgical suite and critical care area. Proceedings of the 24th Conference on Winter Simulation; Arlington, VA: ACM, 1992 p. 1071–1078.

  50. Lowery, J. C., Multi-hospital validation of critical care simulation model. WSC '93: Proceedings of the 25th Conference on Winter Simulation; Los Angeles, CA: ACM, 1993 p. 1207–1215.

  51. Lowery, J. C., Design of hospital admissions scheduling system using simulation. WSC '96: Proceedings of the 28th Conference on Winter Simulation; Coronado, CA: Institute of Electrical and Electronics Engineers, 1996 p. 1199–1204.

  52. Mahjub, H., and Cox, T. F., Bed occupancy rate and throughput of patients in cardiac surgery departments using simulation models. Arch. Iran. Med. 6(3):170–175, 2003.

    Google Scholar 

  53. Marcon, E., Kharraja, S., Smolski, N., Luquet, B., and Viale, J. P., Determining the number of beds in the postanesthesia care unit: a computer simulation flow approach. Anesth. Analg. 96(5):1415–1423, 2003.

    Article  Google Scholar 

  54. Marcon, E., and Dexter, F., Impact of surgical sequencing on post anesthesia care unit staffing. Health Care Manag. Sci. 9(1):87–98, 2006.

    Article  Google Scholar 

  55. McAleer, W. E., Turner, J. A., Lismore, D., and Naqvi, I. A., Simulation of a hospital's theatre suite. J. Manag. Med. 9(5):14–26, 1995.

    Article  Google Scholar 

  56. Nall, D. H., Computer simulation streamlines ambulatory surgery patient flow and increases capacity at Bay Medical Center. Strateg. Healthc. Excell. 5(4):9–12, 1992.

    Google Scholar 

  57. Rakich, J. S., Kuzdrall, P. J., Klafehn, K. A., and Krigline, A. G., Simulation in the hospital setting: implications for managerial decision making and management development. J. Manage. Dev. 10(4):31–37, 1991.

    Article  Google Scholar 

  58. Ravn, H., and Petersen, L. O., Balancing the surgical capacity in a hospital. Int. J. Healthc. Technol. Manag. 8(6):603–624, 2007.

    Article  Google Scholar 

  59. Stahl, J. E., Rattner, D., Wiklund, R., Lester, J., Beinfeld, M., and Gazelle, G. S., Reorganizing the system of care surrounding laparoscopic surgery: a cost-effectiveness analysis using discrete-event simulation. Med. Decis. Mak. 24(5):461–471, 2004.

    Article  Google Scholar 

  60. Testi, A., Tanfani, E., and Torre, G., A three-phase approach for operating theatre schedules. Health Care Manag. Sci. 10(2):163–172, 2007.

    Article  Google Scholar 

  61. VanBerkel, P., and Blake, J., A comprehensive simulation for wait time reduction and capacity planning applied in general surgery. Health Care Manag. Sci. 10(4):373–385, 2007.

    Article  Google Scholar 

  62. Vasilakis, C., Sobolev, B. G., Kuramoto, L., and Levy, A. R., A simulation study of scheduling clinic appointments in surgical care: individual surgeon versus pooled lists. J. Oper. Res. Soc. 58(2):202–211, 2007.

    MATH  Google Scholar 

  63. Wolstenholme, E., A patient flow perspective of UK Health Services: Exploring the case for new “intermediate care” initiatives. Syst. Dyn. Rev. 15(3):253–271, 1999.

    Article  Google Scholar 

  64. Wright, M. B., The application of a surgical bed simulation model. Eur. J. Oper. Res. 32(1):26–32, 1987.

    Article  Google Scholar 

  65. Ham, C., Kipping, R., and McLeod, H., Redesigning work processes in health care: lessons from the National Health Service. Milbank Q. 81(3):415–439, 2003.

    Article  Google Scholar 

  66. Haraden, C., and Resar, R., Patient flow in hospitals: understanding and controlling it better. Front Health Serv. Manage. 20(4):3–15, 2004.

    Google Scholar 

  67. Walshe, K., and Rundall, T., Evidence-based management: from theory to practice in health care. Milbank Q. 79(3):429–459, 2001.

    Article  Google Scholar 

  68. Medical Research Council. A framework for the development and evaluation of RCTs for complex interventions to improve health. 2000. Medical Research Council. 10-3-2009.

  69. Sobolev, B., Linking operations and health services research. Clin. Invest. Med. 28(6):305–307, 2005.

    MathSciNet  Google Scholar 

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Acknowledgements

The selection of databases was based on suggestions made by Mimi Doyles, MLIS, an information specialist, and by librarian Robert Stibravy.

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Correspondence to Boris G. Sobolev.

Appendix

Appendix

Table 7 MEDLINE search strategy
Table 8 EMBASE search strategy
Table 9 INFORMS search strategy
Table 10 INSPEC search strategy
Table 11 CINAHL search strategy
Table 12 MathSciNet search strategy
Table 13 Web of science search strategy
Table 14 ACM digital library search strategy

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Sobolev, B.G., Sanchez, V. & Vasilakis, C. Systematic Review of the Use of Computer Simulation Modeling of Patient Flow in Surgical Care. J Med Syst 35, 1–16 (2011). https://doi.org/10.1007/s10916-009-9336-z

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