DOI 10.17586/0021-3454-2018-61-8-730-733
UDC 004.942
SIMULATION, ANALYSIS, AND PREDICTION OF MEDICAL CARE PROCESSES FOR CARDIOLOGICAL IN-PATIENTS
ITMO University, Department of High-Performance Computing; Post-Graduate Student, Engineer
S. V. Kovalchuk
ITMO University, Saint Petersburg, 197101, Russian Federation; Associate Professor
M. A. Balakhontceva
, ITMO University, Saint Petersburg, 197101, Russian Federation; Senior Researcher
A. V. Boukhanovsky
ITMO University, Saint Petersburg, 197101, Russian Federation; Director
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Abstract. A simulation model of the patient flow for estimating the load of a specialized medical center is developed using empirical data, as well as simulating discrete events, and queuing theory. The results of the simulation demonstrate an inverse relationship between the rate of arrival of patients and their number, and show that the pooling of all resources into one common fund is not always a solution to reduce the burden on a particular department.
Keywords: simulation, medical care processes, machine learning, intellectual analysis of data
References:
References:
1. Santibáñez P., Chow V.S., French J., Puterman M.L., and Tyldesley S. Health Care Manag. Sci., 2009, no. 4(12), pp. 392–407.
2. Christensen B.A. Improving ICU patient flow through discrete-event simulation, Massachusetts Institute of Technology, 2012.
3. Konrad R. et al. Oper. Res. Heal. Care, 2013, no. 4(2), pp. 66–74.
4. Cocke S. et al. 2016 IEEE Syst. Inf. Eng. Des. Symp., 2016, pp. 118–123.
5. Hurwitz J.E., Lee J.A., Lopiano K.K., McKinley S.A., Keesling J., and Tyndall J.A. BMC Med. Inform. Decis. Mak., 2014, no. 1(14), p. 50.
6. Bhattacharjee P. and Ray P.K. Comput. Ind. Eng., 2014, vol. 78, pp. 299–312.
7. Gunal M.M. Heal. Syst., 2012, vol. 18, pp. 17–25.
8. Abuhay T.M., Krikunov A.V., Bolgova E.V., Ratova L.G., and Kovalchuk S.V. Procedia Comput. Sci., 2016, vol. 101, pp. 143–151.