Bulletin of Semashko National Research Institute of Public HealthBulletin of Semashko National Research Institute of Public Health2415-84102415-8429FSSBI «N.A. Semashko National Research Institute of Public Health»2494Научная статьяSimulation modeling for assessing the efficiency of using the resources of a medical organization and the quality of medical care in the context of the COVID-19 epidemicOrlovSergey A.orlovsergio@mail.ruLisovskiiDmitrii A.lisikux@gmail.comLivshitzSergey A.slmd21@gmail.comTikhonovaElena V.glvrachbmk@gmail.comN. A. Semashko National Research Institute of Public HealthState Budgetary Health Institution of the Moscow oblast region «Noginsk Central District Hospital»151220224697525112022Copyright © 2022,2022Patient flow management in hospital departments and observance of stages in the provision of medical care should be systematized, determined by the sequence of implementation of standard operating procedures and worked out in experimental simulation models that assess the level and volume of use of the medical organizations resources.This article discusses the principles of using simulation modeling to assess the efficiency of using the resources of a medical organization and the quality of medical care during the COVID-19 epidemic.The work was performed on the basis of the state budgetary health care institution «Noginsk Central District Hospital» on the basis of retrospective data on the results of hospitalization of 7573 patients over the period April 2020 to June 2021.COVID-19simulationCOVID-19standard operating proceduresquality of medical careимитационное моделированиестандартные операционные процедурыкачество медицинской помощи1.Pförringer, D., Breu, M., Crönlein, M., Kolisch, R., & Kanz, K. G. (2018). Closure simulation for reduction of emergency patient diversion: a discrete agent-based simulation approach to minimizing ambulance diversion. European journal of medical research, 23(1), 32. https://doi.org/10.1186/s40001-018-0330-0.2.Ahalt, V., Argon, N. T., Ziya, S., Strickler, J., & Mehrotra, A. (2018).Comparison of emergency department crowding scores: a discrete-event simulation approach. Health care management science, 21(1), 144-155. https://doi.org/10.1007/s10729-016-9385-z.3.Klein, M. G., Cheng, C. J., Lii, E., Mao, K., Mesbahi, H., Zhu, T., Muckstadt, J. A., & Hupert, N. (2020). COVID-19 Models for Hospital Surge Capacity Planning: A Systematic Review. Disaster medicine and public health preparedness, 1-8. Advance online publication. https://doi.org/10.1017/dmp.2020.332.4.Garcia-Vicuña, D., Esparza, L., & Mallor, F. (2022). Hospital preparedness during epidemics using simulation: the case of COVID-19. Central European journal of operations research, 30(1), 213-249. https://doi.org/10.1007/s10100-021-00779-w.5.Tavakoli, M., Tavakkoli-Moghaddam, R., Mesbahi, R., Ghanavati-Nejad, M., & Tajally, A. (2022). Simulation of the COVID-19 patient flow and investigation of the future patient arrival using a time-series prediction model: a real-case study. Medical & biological engineering & computing, 60(4), 969-990. https://doi.org/10.1007/s11517-022-02525-z.6.Easter, B., Houshiarian, N., Pati, D., & Wiler, J. L. (2019). Designing efficient emergency departments: Discrete event simulation of internal-waiting areas and split flow sorting. The American journal of emergency medicine, 37(12), 2186-2193. https://doi.org/10.1016/j.ajem.2019.03.017.7.López-Cheda, A., Jácome, M. A., Cao, R., & De Salazar, P. M. (2021). Estimating lengths-of-stay of hospitalised COVID-19 patients using a non-parametric model: a case study in Galicia (Spain). Epidemiology and infection, 149, e102. https://doi.org/10.1017/S0950268821000959.8.Garbey M, Joerger G, Furr S, Fikfak V. A model of workflow in the hospital during a pandemic to assist management. PLoS One. 2020 Nov 30;15(11):e0242183. https://doi.org/10.1371/journal.pone.0242183.9.Oliveira, D., Miranda, R., Leuschner, P., Abreu, N., Santos, M. F., Abelha, A., & Machado, J. (2021). OpenEHR modeling: improving clinical records during the COVID-19 pandemic. Health and technology, 11(5), 1109-1118. https://doi.org/10.1007/s12553-021-00556-4.10.Michael Roimi, Rom Gutman, Jonathan Somer, Asaf Ben Arie, Ido Calman, Yaron Bar-Lavie, Udi Gelbshtein, Sigal Liverant-Taub, Arnona Ziv, Danny Eytan, Malka Gorfine, Uri Shalit, Development and validation of a machine learning model predicting illness trajectory and hospital utilization of COVID-19 patients: A nationwide study, Journal of the American Medical Informatics Association, Volume 28, Issue 6, June 2021, Pages 1188-1196, https://doi.org/10.1093/jamia/ocab005.11.Cudney, E.A., Baru, R.A., Guardiola, I., Materla, T., Cahill, W., Phillips, R., Mutter, B., Warner, D. and Masek, C. (2019), «A decision support simulation model for bed management in healthcare», International Journal of Health Care Quality Assurance, Vol. 32 No. 2, pp. 499-515. https://doi.org/10.1108/IJHCQA-10-2017-0186.12.Багненко С. Ф., Полушин Ю. С., Шлык И. В., Теплов В. М., Карпова Е. А., Гаврилова Е. Г., Афанасьев А. А., Бовкун И. В., Малинина Д. А., Калмансон Л. М., Хряпа А. А., Скворцова Р. Д., Коробенков Е. А. Опыт работы ПСПБГМУ им. И. П. Павлова по оказанию помощи больным с новой коронавирусной инфекцией: первые итоги и уроки. Вестник анестезиологии и реаниматологии. 2021;18(2):7-16.13.Карпов О. Э., Орлова О. А., Гусаров В. Г., Пивкина А. И., Габоян Я. С., Силаева Н. А. Организация оказания медицинской помощи в федеральном многопрофильном медицинском учреждении в условиях пандемии. Вестник Росздравнадзора. 2020;(4):67-75.