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Modelling Population Dynamics Using a Hybrid Simulation Approach: Application to Healthcare

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 676))

Abstract

The goal of the study is presenting a population submodel developed using the system dynamics (SD) approach and discussing solutions for the integration of the SD methodology with discrete time control in formulating long-term projections for population evolution and its influence on healthcare demand. This study relies on historical demographic data and officially formulated scenarios for the most likely population projections for the Wrocław Region. The historical parameters are applied from 2002 to 2014, and projected trends are adopted for 2015 to 2035. The preliminary findings confirm the validity of using the hybrid simulation approach for a more advanced exploration of demography-dependent health policy issues.

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References

  1. Lisenkova, K., Mérette, M., Wright, R.: Population ageing and the labour market: modelling size and age-specific effects. Econ. Model. 35, 981–989 (2013)

    Article  Google Scholar 

  2. Tian, Y., Zhao, X.: Stochastic forecast of the financial sustainability of basic pension in China. Sustainability 8, 46 (2016)

    Article  Google Scholar 

  3. Lauf, S., Haase, D., Kleinschmit, B.: The effects of growth, shrinkage, population aging and preference shifts on urban development–a spatial scenario analysis of Berlin, Germany. Land Use Policy 52, 240–254 (2016)

    Article  Google Scholar 

  4. Ansah, J.P., Eberlein, R.L., Love, S.R., Bautista, M.A., Thompson, J.P., Malhotra, R., Matchar, D.B.: Implications of long-term care capacity response policies for an aging population: a simulation analysis. Health Policy 116, 105–113 (2014)

    Article  Google Scholar 

  5. Lutz, W., Sanderson, W., Scherbov, S.: The end of world population growth. Nature 412, 543–545 (2001)

    Article  Google Scholar 

  6. Lassila, J., Valkonen, T., Alho, J.M.: Demographic forecasts and fiscal policy rules. Int. J. Forecast. 30, 1098–1109 (2014)

    Article  Google Scholar 

  7. Davis, P., Lay-Yee, R., Pearson, J.: Using micro-simulation to create a synthesised data set and test policy options: the case of health service effects under demographic ageing. Health Policy 97, 267–274 (2010)

    Article  Google Scholar 

  8. Homer, J.B., Hirsch, G.B.: System dynamics modeling for public health: background and opportunities. Am. J. Public Health 96, 452–458 (2006)

    Article  Google Scholar 

  9. Barber, P., Lopez-Valcarcel, B.: Forecasting the need for medical specialists in Spain: application of a system dynamics model. Hum. Resour. Health 8, 24 (2010)

    Article  Google Scholar 

  10. Masnick, K., McDonnell, G.: A model linking clinical workforce skill mix planning to health and health care dynamics. Hum. Resour. Health 8, 11 (2010)

    Article  Google Scholar 

  11. 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, 109–123 (1999)

    Article  MATH  Google Scholar 

  12. Mielczarek, B., Uziałko-Mydlikowska, J.: Application of computer simulation modeling in the health care sector: a survey. Simulation 88, 197–216 (2012)

    Article  Google Scholar 

  13. GUS, Główny Urząd Statystyczny. www.stat.gov.pl. Accessed Dec 2015

  14. Sterman, J.D.: Business Dynamics. System Thinking and Modeling for a Complex World. McGraw-Hill Higher Education, Boston (2000)

    Google Scholar 

  15. Mustafee, N., Katsaliaki, K., Taylor, S.J.E.: Profiling literature in healthcare simulation. Simulation 86, 543–558 (2010)

    Article  Google Scholar 

  16. Testi, A., Tanfani, E., Torre, G.: A three-phase approach for operating theatre schedules. Health Care Manag. Sci. 10, 72–163 (2007)

    Article  Google Scholar 

  17. Sinreich, D., Marmor, Y.N.: Emergency department operations: the basis for developing a simulation model. IIE Trans. 37, 233–245 (2005)

    Article  Google Scholar 

  18. Hughes, G.R., Currie, C.S.M., Corbett, E.L.: Modeling tuberculosis in areas of high HIV prevalence. In: Perrone, L.F., Wieland, F.P., Liu, J., Lawson, B.G., Nicol, D.M., Fujimoto, R.M. (eds.) Proceedings of the 2006 Winter Simulation Conference, pp. 459–465. Institute of Electrical and Electronics Engineers, Inc., Piscataway (2006)

    Google Scholar 

  19. Kasaie, P., Kelton, W.D., Vaghefi, A., Naini, S.G.R.J.: Toward optimal resource-allocation for control of epidemics: an agent-based-simulation approach. In: Johansson, B., Jain, S., Montoya-Torres, J., Hugan, J., Yücesan, E. (eds.) Proceedings of the 2010 Winter Simulation Conference, pp. 2237–2248. Institute of Electrical and Electronics Engineers, Inc., Piscataway (2010)

    Google Scholar 

  20. Ashton, R., Hague, L., Brandreth, M., Worthington, D., Cropper, S.: A simulation-based study of a NHS walk-in centre. J. Oper. Res. Soc. 56, 153–161 (2005)

    Article  MATH  Google Scholar 

  21. Cardoso, T., Oliveira, M., Barbosa-Póvoa, A., Nickel, S.: Modeling the demand for long-term care services under uncertain information. Health Care Manag. Sci. 15, 385–412 (2012)

    Article  Google Scholar 

  22. Christie, P.M., Levary, R.R.: The use of simulation in planning the transportation of patients to hospitals following a disaster. J. Med. Syst. 22, 289–300 (1998)

    Article  Google Scholar 

  23. Han, L.D., Yuan, F., Shih-Miao, C., Hwang, H.: Global optimization of emergency evacuation assignments. Interfaces 36, 502–513 (2006)

    Google Scholar 

  24. Caro, J.J., Guo, S., Ward, A., Shajil, C., Malik, F., Leyva, F.: Modelling the economic and health consequences of cardiac resynchronization therapy in the UK. Curr. Med. Res. Opin. 22, 1171–1179 (2006)

    Article  Google Scholar 

  25. 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, 518–531 (2000)

    Article  MATH  Google Scholar 

  26. Mielczarek, B., Zabawa, J.: Modelling population growth, shrinkage and aging using a hybrid simulation approach: application to healthcare. In: Merkuryev, J., Oren, T., Obaidat, M.S. (eds.) Proceedings of the 6th International Conference on Simulation and Modeling Methodologies, Technologies and Applications, SIMULTECH 2016, pp. 75–83. SciTePress (2016)

    Google Scholar 

  27. Eberlein, R.L., Thompson, J.P., Matchar, D.B.: Chronological aging in continuous time. In: Husemann, E., Lane, D. (eds.) Proceedings of the 30th International Conference of the System Dynamics Society (2011)

    Google Scholar 

  28. Mielczarek, B., Zabawa, J., Lubicz, M.: A system dynamics model to study the impact of an age pyramid on emergency demand. In: Obaidat, M.S., Kacprzyk, J., Oren, T. (eds.) Proceedings of the 4th International Conference on Simulation and Modeling Methodologies, Technologies and Applications, pp. 879–888. SciTePress (2014)

    Google Scholar 

  29. Krahl, D.: ExtendSim advanced technology: discrete rate simulation. In: Rossetti, M.D., Hill, R.R., Johansson, B., Dunkin, A, Ingalls, R.G. (eds.) Proceedings of the 2009 Winter Simulation Conference, pp. 333–338. Institute of Electrical and Electronics Engineers, Inc., Piscataway (2009)

    Google Scholar 

  30. Waligórska, M., Kostrzewa, Z., Potyra, M., Rutkowska, L.: Population projection 2014–2050, CSO, Demographic Surveys and Labour Market Department (2014)

    Google Scholar 

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Acknowledgements

This Project Was Financed by the Grant Simulation Modeling of the Demand for Healthcare Services from the National Science Centre, Poland, and Was Awarded based on the Decision 2015/17/B/HS4/00306.

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Correspondence to Bożena Mielczarek .

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Mielczarek, B., Zabawa, J. (2018). Modelling Population Dynamics Using a Hybrid Simulation Approach: Application to Healthcare. In: Obaidat, M., Ören, T., Merkuryev, Y. (eds) Simulation and Modeling Methodologies, Technologies and Applications. SIMULTECH 2016. Advances in Intelligent Systems and Computing, vol 676. Springer, Cham. https://doi.org/10.1007/978-3-319-69832-8_14

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  • DOI: https://doi.org/10.1007/978-3-319-69832-8_14

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-319-69832-8

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