Patient routing is a key tool for ensuring the availability and quality of cancer care, ensuring early detection of pathology and timely treatment. Mathematical and simulation modeling methods allow to predict the bottlenecks of patient flows and plan the optimal distribution of healthcare resources. Goal to optimize patients’ pathways for oncology care using the simulation modelling methods. Materials and methods Patient routing was presented in the logic of discrete events, the average resource utilization, the patient’s stay time were described, the bottlenecks of the system were determined. Simulation modeling methods were used to build the optimal organization of oncology care services in the region. Results The average waiting time at the pre-hospital stage was 10 days, the average hospitalization time for X-ray therapy was 24 bed days, the throughput of the X-ray therapy room was 6 patients per week, the average duration of the X-ray therapy session per patient was 10 minutes. With the help of simulation modeling methods, a multimodal system of oncodermatology care was created and put into practice, which allowed to reduce the patient’s waiting time for treatment to 0.7 days, increasing the throughput of the entire system.
Diffusion entropy and waiting time statistics of hard-x-ray solar flares