School of Logistics, Beijing Wuzi University, No.321, Fuhe Street, Tongzhou District, Beijing, 101149, China.
BMC Health Serv Res. 2024 Apr 17;24(1):477. doi: 10.1186/s12913-024-10955-8.
Public health emergencies are characterized by uncertainty, rapid transmission, a large number of cases, a high rate of critical illness, and a high case fatality rate. The intensive care unit (ICU) is the "last line of defense" for saving lives. And ICU resources play a critical role in the treatment of critical illness and combating public health emergencies.
This study estimates the demand for ICU healthcare resources based on an accurate prediction of the surge in the number of critically ill patients in the short term. The aim is to provide hospitals with a basis for scientific decision-making, to improve rescue efficiency, and to avoid excessive costs due to overly large resource reserves.
A demand forecasting method for ICU healthcare resources is proposed based on the number of current confirmed cases. The number of current confirmed cases is estimated using a bilateral long-short-term memory and genetic algorithm support vector regression (BILSTM-GASVR) combined prediction model. Based on this, this paper constructs demand forecasting models for ICU healthcare workers and healthcare material resources to more accurately understand the patterns of changes in the demand for ICU healthcare resources and more precisely meet the treatment needs of critically ill patients.
Data on the number of COVID-19-infected cases in Shanghai between January 20, 2020, and September 24, 2022, is used to perform a numerical example analysis. Compared to individual prediction models (GASVR, LSTM, BILSTM and Informer), the combined prediction model BILSTM-GASVR produced results that are closer to the real values. The demand forecasting results for ICU healthcare resources showed that the first (ICU human resources) and third (medical equipment resources) categories did not require replenishment during the early stages but experienced a lag in replenishment when shortages occurred during the peak period. The second category (drug resources) is consumed rapidly in the early stages and required earlier replenishment, but replenishment is timelier compared to the first and third categories. However, replenishment is needed throughout the course of the epidemic.
The first category of resources (human resources) requires long-term planning and the deployment of emergency expansion measures. The second category of resources (drugs) is suitable for the combination of dynamic physical reserves in healthcare institutions with the production capacity reserves of corporations. The third category of resources (medical equipment) is more dependent on the physical reserves in healthcare institutions, but care must be taken to strike a balance between normalcy and emergencies.
公共卫生事件具有不确定性、快速传播、大量病例、高重症率和高病死率的特点。重症监护病房（ICU）是拯救生命的“最后一道防线”。ICU 资源在治疗重症和应对公共卫生事件中起着至关重要的作用。
本研究旨在通过对短期内重症患者数量的激增进行准确预测，估算 ICU 医疗资源的需求。目的是为医院提供科学决策的依据，提高抢救效率，避免因资源储备过大而导致过度成本。
提出了一种基于当前确诊病例数的 ICU 医疗资源需求预测方法。采用双边长短时记忆和遗传算法支持向量回归（BILSTM-GASVR）组合预测模型对当前确诊病例数进行预测。在此基础上，构建 ICU 医护人员和医疗物资资源需求预测模型，更准确地了解 ICU 医疗资源需求变化规律，更精准地满足重症患者的治疗需求。
利用 2020 年 1 月 20 日至 2022 年 9 月 24 日上海市 COVID-19 感染病例数据进行数值实例分析。与个体预测模型（GASVR、LSTM、BILSTM 和 Informer）相比，组合预测模型 BILSTM-GASVR 的预测结果更接近真实值。ICU 医疗资源需求预测结果表明，第一类（ICU 人力资源）和第三类（医疗设备资源）在早期不需要补充，但在高峰期出现短缺时会出现滞后补充；第二类（药品资源）在早期消耗较快，需要更早补充，但与第一类和第三类相比，补充时间更及时。然而，整个疫情期间都需要补充。
第一类资源（人力资源）需要长期规划和应急扩充措施的部署。第二类资源（药品）适合医疗机构动态实物储备与企业生产能力储备相结合。第三类资源（医疗设备）更依赖医疗机构的实物储备，但必须在常态和应急之间取得平衡。
