Optimizing processes to improve the effectiveness of medical care

The purpose of the research is to analyze the potential of mathematical optimization as a tool for improving the efficiency of medical care, as well as to substantiate the role of dispatching in managing patient flows, diagnostic, and treatment processes in multidisciplinary medical organizations. Methods. The methodological basis consisted of a comparative analysis of scientific publications, a summary of practical cases, the interpretation of simulation results, and an analysis of retrospective data from a pilot hospital. The study utilized M/M/1 and M/M/c models for estimating queues and service channel utilization, min-max and max-min criteria for resource balancing, linear programming methods for optimizing operating room schedules, and the HoltWinters and ARIMA models for load forecasting. Results. It was confirmed that dispatching ensures the coordination of patient flows, diagnostic tests, surgical interventions, and equipment transportation and distribution based on operational information. Mathematical models have been shown to formalize the selection of the optimal number of service channels, minimize wait times, balance department loads, and reduce downtime for high-cost resources. A 37 % reduction in average queue length, an increase in operating room occupancy from 71,8 to 84,7%, and forecasting of peak demand with a MAPE accuracy of less than 12 % were demonstrated. An analysis of 1,240 hospitalizations showed a reduction in the average hospital stay for myocardial infarction, cholecystectomy, and stroke, resulting in an annual economic benefit of 18,562 million rubles at a cost of approximately 3,5 million rubles. Conclusion. Mathematical process optimization is a system-forming tool for improving the efficiency of medical care. Its greatest impact is seen in emergency departments, operating rooms, and radiology services.