突发公共卫生事件案例库结构化表达及构建研究

Establishment and structured representation of a public health emergency cases bank

目的建立突发公共卫生事件结构化、规范化的描述标准,实现多源信息的有效整合、抽取、总结及推理,为应急决策提供信息化、数字化辅助支持。方法采用焦点小组法、关键知情人访谈等定性研究方法,针对事件分类、纳入原则、编制框架及主题影响因素等收集专家意见及相关信息,对既往案例进行分析总结,构建突发公共卫生事件案例结构化表达模型。结果研究最终纳入25个突发公共卫生事件案例,形成7步法案例编制框架,基于"案例描述-解决方案-案例结论"的案例描述树结构,提出包括案例档案、概述、大事记、预防与先期准备、应急响应与救援、风险沟通、恢复与重建、分析及评述、参考文献与附件9部分在内的案例结构化表达模型。结论构建"情景-应对"结构化表达模型,建立规范化、结构化的突发公共卫生事件案例库,实现突发公共卫生事件全过程、全方位的规范化记录和表达,突破突发公共卫生事件响应决策过程中时间、环境和信息等的多重限制,推动历史信息与专家经验的智能化利用。

Objective To set up a structured or semi-structured database of public health emergencies,to integrate,extract,summarize and speculate effectively based on multi-source information,and to provide informatization and digitization support for emergency decision-making.Methods Qualitative research methods,such as focus group and nominal group technique,in-depth interviews,were used to collect data and professional expertise of cases focusing on case categories,inclusion and exclusion principle,compiling framework and main influence factors.Structured model was constructed based on analyzing and summarizing emergency case essentials.Results Twenty-five public health emergency cases were selected and included in this study.Followed by the 7-step compiling framework constructed in this study,a description-solution-conclusion scheme was proposed,composed of 9 parts,including structured case file,overview,chronicles,prevention and preparation,response and rescue,risk communication,restoration and reconstruction,after action report,references and attachments.Conclusion A structured model was designed from the scenario-to-response perspective,with a database constructed following the standardized procedures,to retrospect the whole process from various aspects for the quick and impersonal reference of policy makers,which helping to overcome several obstacles for decision-making,for example,urgency,complexity,information uncertainty and accessibility,during public health emergency response,as well as further inspire the artificial intelligence utilization of historical experiences.