{"title":"肿瘤患者路线组织的仿真建模方法","authors":"J. Zuenkova, D. Kicha","doi":"10.46793/iccbi21.247z","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":9171,"journal":{"name":"Book of Proceedings: 1st International Conference on Chemo and BioInformatics,","volume":"49 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"THE SIMULATION MODELLING METHODS FOR ORGANIZATION OF THE ONCOLOGY PATIENTS ROUTING\",\"authors\":\"J. Zuenkova, D. Kicha\",\"doi\":\"10.46793/iccbi21.247z\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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.\",\"PeriodicalId\":9171,\"journal\":{\"name\":\"Book of Proceedings: 1st International Conference on Chemo and BioInformatics,\",\"volume\":\"49 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Book of Proceedings: 1st International Conference on Chemo and BioInformatics,\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.46793/iccbi21.247z\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Book of Proceedings: 1st International Conference on Chemo and BioInformatics,","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.46793/iccbi21.247z","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
患者路径是确保癌症治疗的可用性和质量,确保早期发现病理和及时治疗的关键工具。数学和仿真建模方法允许预测患者流的瓶颈并规划医疗资源的最佳分配。目的利用模拟建模方法优化肿瘤患者的治疗途径。材料与方法在离散事件逻辑中提出了患者路径,描述了系统的平均资源利用率和患者住院时间,确定了系统的瓶颈。采用仿真建模方法构建区域肿瘤护理服务的最优组织。结果院前阶段平均候诊时间为10 d, x线治疗平均住院时间为24床d, x线治疗室吞吐量为6例/周,x线治疗时间平均为10 min /例。利用仿真建模方法,建立了肿瘤皮肤科多模式护理系统并付诸实践,使患者的等待治疗时间减少到0.7天,提高了整个系统的吞吐量。
THE SIMULATION MODELLING METHODS FOR ORGANIZATION OF THE ONCOLOGY PATIENTS ROUTING
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.