An approach to automating resource management of a service organization based on simulation modeling integrating the predicted input flows of patients, is considered. Methods for predicting input flows based on SARIMA, Holt-Winters, LSTM, and controlled recurrent GRU models have been investigated. The results of a computational experiment on predicting patient flows in a medical organization are presented. Based on the results, a meta-algorithm for forecasting the input flow and its further integration into the simulation model of the service process of a multidisciplinary healthcare organization was developed.
Prokofyeva, Elizaveta; Svetlana, Maltseva; and Tsiu-Zhen-Tsin, Dmitry, "Forecasting Heterogeneous Patient Flow through Big Data Application in Medical Facilities for Rational Staffing" (2020). International Conference on Information Systems 2020 Special Interest Group on Big Data Proceedings. 1.