大型医院医疗物资保障系统韧性评价

Resilience evaluation of medical material support systems in large hospitals

为有效评价大型医院医疗物资保障系统抵御突发事件干扰并快速恢复的能力,需要引入韧性概念。本文提出利用动态贝叶斯网络对大型医院的医疗物资保障系统进行韧性评价。首先,筛选出影响系统韧性的因素;其次,引入时间维度,利用动态贝叶斯网络建立韧性评价模型,采用专家打分法量化节点概率,并结合Leaky Noisy-or gate模型修正计算条件概率。随后,利用动态贝叶斯网络的双向推理功能对系统的韧性进行评价。最后,选取案例验证该评价模型的可行性和实用性。通过正向分析,得到了系统韧性的时序变化曲线和最大致因链,通过逆向推理得到影响系统韧性的5个关键因素。结果表明,动态贝叶斯网络能够有效评价大型医院医疗物资保障系统韧性,为有效提高医院医疗物资保障系统韧性提供有效思路。

To effectively evaluate the ability of large hospital medical material support systems to withstand and quickly recover from unexpected events,the concept of resilience needs to be introduced.This study proposes using dynamic Bayesian networks to evaluate the resilience of medical material support systems in large hospitals.First,factors influencing system resilience are identified.Next,the time dimension is incorporated,and a resilience evaluation model is established using dynamic Bayesian networks.Node probabilities are quantified using expert scoring,and the Leaky Noisy-or gate model is applied to adjust conditional probabilities.Subsequently,the bidirectional reasoning function of dynamic Bayesian networks is utilized to evaluate system resilience.Finally,a case study is selected to verify the feasibility and practicality of the evaluation model.Through forward analysis,the time-series variation curve of system resilience and the maximum causal chain are obtained.Through reverse reasoning,five key factors influencing system resilience are identified.Results indicate that dynamic Bayesian networks can effectively evaluate the resilience of large hospital medical material support systems,providing valuable insights for enhancing the resilience of these systems.