Factors affecting the implementation of simulation modelling in healthcare: A longitudinal case study evaluation

References

• Barnes, C. D., Benson, C., Quiason, J. L., & McGuiness, D. (1997). Success stories in simulation in health care. Paper presented at the Winter Simulation Conference, Atlanta, Georgia, USA.
   Google Scholar
• Ben-Zvi, T. (2012). Measuring the perceived effectiveness of decision support systems and their impact on performance. Decision Support Systems, 54(1), 248–256. doi:10.1016/j.dss.2012.05.033
   Web of Science ®Google Scholar
• Biesta, G. (2010). Pragmatism and the philosophical foundations of mixed methods research. In Tashakkori A and Teddlie C (Eds.), SAGE handbook of mixed methods in social and behavioral research 2010 (2nd ed., pp. 95–118). Los Angeles, CA: SAGE Publications.
   Google Scholar
• Birt, L., Scott, S., Cavers, D., Campbell, C., & Walter, F. (2016). Member checking: A tool to enhance trustworthiness or merely a nod to validation? Qualitative Health Research, 26(13), 1802–1811. doi:https://doi.org/10.1177/1049732316654870.
   PubMed Web of Science ®Google Scholar
• Brailsford, S. C. (2005). Overcoming the barriers to implementation of operations research simulation models in healthcare. Clinical and Investigative Medicine, 28(6), 312–315.
   PubMed Web of Science ®Google Scholar
• Brailsford, S. C., Bolt, T., Connell, C., Klein, J. H., & Patel, B. (2009). Stakeholder engagement in health care simulation. Paper presented at the Winter Simulation Conference, Austin, Texas.
   Google Scholar
• Brailsford, S. C., Bolt, T. B., Bucci, G., Chaussalet, T. M., Connell, N. A., Harper, P. R., … Taylor, M. (2013). Overcoming the barriers: A qualitative study of simulation adoption in the NHS. Journal of the Operational Research Society, 64(2), 157–168. doi:10.1057/jors.2011.130
   Web of Science ®Google Scholar
• Brailsford, S. C., Harper, P. R., Patel, B., & Pitt, M. (2009). An analysis of the academic literature on simulation and modelling in health care. Journal of Simulation, 3(3), 130–140. doi:10.1057/jos200910
   Web of Science ®Google Scholar
• Butterfield, L. D., Borgen, W. A., Amundson, N. E., & Maglio, A.-S. T. (2005). Fifty years of the critical incident technique: 1954-2004 and beyond. Qualitative Research, 5(4), 475–497. doi:10.1177/1468794105056924
   Google Scholar
• Byrne, D. S. (1998). Complexity theory and the social sciences: an introduction. London: Routledge.
   Google Scholar
• Eldabi, T. (2009). Implementation issues of modeling healthcare problems: misconceptions and lessons. Paper presented at the Winter Simulation Conference, Austin, Texas.
   Google Scholar
• England, W., & Roberts, S. D. (1978). Applications of computer simulation in health care. Paper presented at the Winter Simulation Conference, Miami Beach, Florida.
   Google Scholar
• Fishman, D. B. (1992). Postmodernism comes to program evaluation: A critical review of Guba and Lincoln's fourth generation evaluation. Evaluation and Program Planning, 15(3), 263–270. doi:10.1016/0149-7189(92)90090-H
   Web of Science ®Google Scholar
• Flanagan, J. C. (1954). The critical incident technique. Psychological Bulletin, 51(4), 327–358.
   PubMed Web of Science ®Google Scholar
• Fone, D., Hollinghurst, S., Temple, M., Round, A., Lester, N., Weightman, A., … Palmer, S. (2003). Systematic review of the use and value of computer simulation modelling in population health and health care delivery. Journal of Public Health Medicine, 25(4), 325–335. doi:10.1093/pubmed/fdg075
   PubMedGoogle Scholar
• Forsberg, H. H., Aronsson, H., Keller, C., & Lindblad, S. (2011). Managing health care decisions and improvement through simulation modeling. Quality Management in Health Care, 20(1), 15–29. doi:https://doi.org/10.1097/QMH.0b013e3182033bdc.
   PubMedGoogle Scholar
• Fraser, S. W., & Greenhalgh, T. (2001). Coping with complexity: Educating for capability. BMJ, 323(7316), 799–803. doi:https://doi.org/10.1136/bmj.323.7316.799.
   PubMed Web of Science ®Google Scholar
• Fries, B. E. (1976). Bibliography of operations research in health-care systems. Operations Research, 24(5), 801–814. doi:10.1287/opre.24.5.801
   Web of Science ®Google Scholar
• Guba, E. G., & Lincoln, Y. S. (1989). Fourth generation evaluation. Newbury Park, Ca.: Sage.
   Google Scholar
• Guimaraes, T., Igbaria, M., & Lu, M. (1992). The determinants of DSS success: An integrated model. Decision Sciences, 23(2), 409–430. doi:10.1111/j.1540-5915.1992.tb00397.x
   Web of Science ®Google Scholar
• Gunal, M. M., & Pidd, M. (2010). Discrete event simulation for performance modelling in health care: a review of the literature. Journal of Simulation, 4(1), 42–51. doi:10.1057/jos.2009.25
   Web of Science ®Google Scholar
• Holland, J. H. (2014). Complexity: A very short introduction. Oxford, UK: Oxford University Press.
   Google Scholar
• Innvaer, S., Vist, G., Trommald, M., & Oxman, A. (2002). Health policy-makers' perceptions of their use of evidence: a systematic review. Journal of Health Services Research & Policy, 7(4), 239–244. doi:https://doi.org/10.1258/135581902320432778.
   PubMedGoogle Scholar
• Jahangirian, M., Naseer, A., Stergioulas, L., Young, T., Eldabi, T., Brailsford, S., … Harper, P. (2012). Simulation in health-care: Lessons from other sectors. Operational Research, 12(1), 45–55. doi:10.1007/s12351-010-0089-8
   Web of Science ®Google Scholar
• Jun, J. B., Jacobson, S. H., & Swisher, J. R. (1999). Application of discrete-event simulation in health care clinics: A survey. The Journal of the Operational Research Society, 50(2), 109–123. doi:10.2307/3010560
   Web of Science ®Google Scholar
• Kirchhof, P., & Meseth, N. (2012). A survey on the use of simulation in German healthcare. Paper presented at the Winter Simulation Conference, Berlin, Germany.
   Google Scholar
• Klein, J. H., & Young, T. (2015). Health care: a case of hypercomplexity? Health Systems, 4(2), 104–110. doi:10.1057/hs.2014.21
   Web of Science ®Google Scholar
• Kuljis, J., Paul, R. J., & Stergioulas, L. K. (2007). Can health care benefit from modeling and simulation methods in the same way as business and manufacturing has? Paper presented at the Winter Simulation Conference, Washington DC, USA.
   Google Scholar
• Lane, D. C., Monefeld, C., & Husemann, E. (2003). Client involvement in simulation model building: hints and insights from a case study in a London hospital. Health Care Management Science, 6(2), 105–116. doi:10.1023/A:1023385019514
   PubMedGoogle Scholar
• Lehaney, B., & Hlupic, V. (1995). Simulation modelling for resource allocation and planning in the health sector. Journal of the Royal Society of Health, 115(6), 382–385. doi:10.1177/146642409511500611
   PubMedGoogle Scholar
• Long, K. M. (2018). The pragmatic implementation and evaluation of a mental healthcare decision support intervention (PhD thesis). Melbourne: Monash University.
   Google Scholar
• Long, K. M., McDermott, F., & Meadows, G. (2018). Being pragmatic about healthcare complexity: our experiences applying complexity theory and pragmatism to health services research. BMC Medicine, 16(1), 94. doi:https://doi.org/10.1186/s12916-018-1087-6. [https://doi.org/29921277]
   PubMedGoogle Scholar
• Long, K. M., & Meadows, G. (2018a). Simulation modelling in mental health: A systematic review. Journal of Simulation, 12(1), 76–85. doi:10.1057/s41273-017-0062-0
   Web of Science ®Google Scholar
• Long, K. M., & Meadows, G. (2018b). Simulation modelling for psychiatric service planning: Protocol for a mixed-methods study. JMIR Research Protocols, 7(11), e11119. doi:10.2196/11119
   Web of Science ®Google Scholar
• Mahmood, A., Burn, J. M., Gemoets, L. A., & Jacquez, C. (2000). Variables affecting information technology end-user satisfaction: a meta-analysis of the empirical literature. International Journal of Human-Computer Studies, 52(4), 751–771. doi:10.1006/ijhc.1999.0353
   Web of Science ®Google Scholar
• Marshall, M., Eyre, L., Lalani, M., Khan, S., Mann, S., de Silva, D., & Shapiro, J. (2016). Increasing the impact of health services research on service improvement: The researcher-in-residence model. Journal of the Royal Society of Medicine, 109(6), 220–225. doi:https://doi.org/10.1177/0141076816634318.
   Web of Science ®Google Scholar
• Marshall, M., Pagel, C., French, C., Utley, M., Allwood, D., Fulop, N., … Goldmann, A. (2014). Moving improvement research closer to practice: The researcher-in-residence model. BMJ Quality & Safety, 23(10), 801. doi:10.1136/bmjqs-2013-002779
   PubMed Web of Science ®Google Scholar
• Mielczarek, B., & Uziałko-Mydlikowska, J. (2012). Application of computer simulation modeling in the health care sector: A survey. SIMULATION, 88(2), 197–216. doi:10.1177/0037549710387802
   Google Scholar
• Mingers, J. (2000). The contribution of critical realism as an underpinning philosophy for OR/MS and systems. The Journal of the Operational Research Society, 51(11), 1256–1270. doi:10.2307/254211
   Web of Science ®Google Scholar
• Monks, T., Pearson, M., Pitt, M., Stein, K., & James, M. A. (2015). Evaluating the impact of a simulation study in emergency stroke care. Operations Research for Health Care, 6, 40–49. doi:10.1016/j.orhc.2015.09.002
   Web of Science ®Google Scholar
• Mora, M., Cervantes-Pérez, F., Gelman-Muravchik, O., & Forgionne, G. A. (2012). Modeling the strategic process of decision-making support systems implementations: A system dynamics approach review. IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews), 42(6), 899–912. doi:10.1109/TSMCC.2011.2171482
   Web of Science ®Google Scholar
• Morgan, D. L. (2007). Paradigms lost and pragmatism regained: Methodological implications of combining qualitative and quantitative. Journal of Mixed Methods Research, 1(1), 48–76. doi:10.1177/2345678906292462
   Web of Science ®Google Scholar
• Mustafee, N., Katsaliaki, K., & Taylor, S. J. E. (2010). Profiling literature in healthcare simulation. SIMULATION, 86(8-9), 543–558. doi:10.1177/0037549709359090
   Google Scholar
• Nilsen, P. (2015). Making sense of implementation theories, models and frameworks. Implementation Science, 10(1), 53. doi:10.1186/s13012-015-0242-0
   PubMed Web of Science ®Google Scholar
• Ormerod, R. J. (2014). The mangle of OR practice: Towards more informative case studies of ‘technical’ projects. Journal of the Operational Research Society, 65(8), 1245–1260. doi:10.1057/jors.2013.78
   Web of Science ®Google Scholar
• Pickering, A. (1995). The mangle of practice: Time, agency, and science. Chicago, IL: University of Chicago Press.
   Google Scholar
• Pitt, M. (2008). Simulation for strategic planning in healthcare: The state of the art. Retrieved from http://www.institute.nhs.uk/images//documents/BuildingCapability/ScenarioGenerator/state-of-the-art.pdf
   Google Scholar
• Plsek, P. E., & Greenhalgh, T. (2001). Complexity science: The challenge of complexity in health care. BMJ, 323(7313), 625–628. doi:https://doi.org/10.1136/bmj.323.7313.625.
   PubMed Web of Science ®Google Scholar
• Plsek, P. E., & Wilson, T. (2001). Complexity, leadership, and management in healthcare organisations. BMJ, 323(7315), 746–749.doi:https://doi.org/10.1136/bmj.323.7315.746.
   PubMed Web of Science ®Google Scholar
• QSR International Pty Ltd. (2012). Nvivo qualitative data analysis software (Version 10). Doncaster, Victoria: QSR International Pty Ltd.
   Google Scholar
• Rittel, H. W. J., & Webber, M. M. (1973). Dilemmas in a general theory of planning. Policy Sciences, 4(2), 155–169. doi:10.1007/BF01405730
   Web of Science ®Google Scholar
• Robinson, S., & Pidd, M. (1998). Provider and customer expectations of successful simulation projects. The Journal of the Operational Research Society, 49(3), 200–209. doi:10.2307/3010469
   Web of Science ®Google Scholar
• Ryan, G. W., & Bernard, H. R. (2003). Techniques to identify themes. Field Methods, 15(1), 85–109. doi:10.1177/1525822X02239569
   Google Scholar
• Smith-Daniels, V. L., Schweikhart, S. B., & Smith-Daniels, D. E. (1988). Capacity management in health care services: Review and future research directions. Decision Sciences, 19(4), 889–919. doi:10.1111/j.1540-5915.1988.tb00310.x
   Web of Science ®Google Scholar
• Tako, A. A., & Robinson, S. (2015). Is simulation in health different? Journal of the Operational Research Society, 66(4), 602–614. doi:10.1057/jors.2014.25
   Web of Science ®Google Scholar
• Talisse, R. B., & Aikin, S. F. (2008). Pragmatism: A guide for the perplexed. London: Continuum.
   Google Scholar
• Thompson, J. P., Howick, S., & Belton, V. (2016). Critical learning incidents in system dynamics modelling engagements. European Journal of Operational Research, 249(3), 945–958. doi:10.1016/j.ejor.2015.09.048
   Web of Science ®Google Scholar
• Tunnicliffe-Wilson, J. C. (1980). A review of population health care problems tackled by computer simulation. Public Health, 94(3), 174–182.
   PubMed Web of Science ®Google Scholar
• Tunnicliffe-Wilson, J. C. (1981). Implementation of computer simulation projects in health care. The Journal of the Operational Research Society, 32(9), 825–832. doi:10.2307/2581399
   Web of Science ®Google Scholar
• van Lent, W. A., VanBerkel, P., & van Harten, W. H. (2012). A review on the relation between simulation and improvement in hospitals. BMC Medical Informatics and Decision Making, 12(1), 18–25. doi:https://doi.org/10.1186/1472-6947-12-18.
   PubMed Web of Science ®Google Scholar
• van Sambeek, J. R., Cornelissen, F. A., Bakker, P. J., & Krabbendam, J. J. (2010). Models as instruments for optimizing hospital processes: A systematic review. International Journal of Health Care Quality Assurance, 23(4), 356–377. doi:https://doi.org/10.1108/09526861011037434.
   PubMedGoogle Scholar
• Walton, M. (2014). Applying complexity theory: A review to inform evaluation design. Evaluation and Program Planning, 45, 119–126. doi:https://doi.org/10.1016/j.evalprogplan.2014.04.002.
   PubMed Web of Science ®Google Scholar
• Wilson, T., Holt, T., & Greenhalgh, T. (2001). Complexity science: Complexity and clinical care. BMJ, 323(7314), 685–688. doi:https://doi.org/10.1136/bmj.323.7314.685.
   PubMed Web of Science ®Google Scholar