暴发调查的数据收集：使用德尔菲法定义最小数据集的过程。
Data collection for outbreak investigations: process for defining a minimal data set using a Delphi approach.
机构信息
World Health Organisation, Geneva, Switzerland.
London School of Hygiene & Tropical Medicine, London, UK.
出版信息
BMC Public Health. 2021 Dec 13;21(1):2269. doi: 10.1186/s12889-021-12206-5.
BACKGROUND
Timely but accurate data collection is needed during health emergencies to inform public health responses. Often, an abundance of data is collected but not used. When outbreaks and other health events occur in remote and complex settings, operatives on the ground are often required to cover multiple tasks whilst working with limited resources. Tools that facilitate the collection of essential data during the early investigations of a potential public health event can support effective public health decision-making. We proposed to define the minimum set of quantitative information to collect whilst using electronic device or not. Here we present the process used to select the minimum information required to describe an outbreak of any cause during its initial stages and occurring in remote settings.
METHODS
A working group of epidemiologists took part in two rounds of a Delphi process to categorise the variables to be included in an initial outbreak investigation form. This took place between January-June 2019 using an online survey.
RESULTS
At a threshold of 75 %, consensus was reached for nineteen (23.2%) variables which were all classified as 'essential'. This increased to twenty-six (31.7%) variables when the threshold was reduced to 60% with all but one variable classified as 'essential'. Twenty-five of these variables were included in the 'Time zero initial case investigation' '(T0)' form which was shared with the members of the Rapid Response Team Knowledge Network for field testing and feedback. The form has been readily available online by WHO since September 2019.
CONCLUSION
This is the first known Delphi process used to determine the minimum variables needed for an outbreak investigation. The subsequent development of the T0 form should help to improve the efficiency and standardisation of data collection during emergencies and ultimately the quality of the data collected during field investigation.
背景
在卫生突发事件期间，需要及时准确地收集数据，以为公共卫生应对提供信息。通常，会收集大量的数据但未被使用。当疫情和其他卫生事件发生在偏远和复杂的环境中时，现场工作人员通常需要在有限资源的情况下完成多项任务。在潜在公共卫生事件的早期调查期间，有助于收集基本数据的工具可以支持有效的公共卫生决策。我们提议定义在使用电子设备或不使用电子设备时收集基本定量信息的最小集合。在此，我们介绍了选择在偏远地区发生的任何原因引起的疫情初始阶段所需的最小信息量的过程。
方法
一组流行病学家参与了两轮德尔菲（Delphi）流程，对纳入初始疫情调查报告表的变量进行分类。这是在 2019 年 1 月至 6 月之间使用在线调查进行的。
结果
在 75%的阈值下，19 个（23.2%）变量达成了共识，这些变量都被归类为“基本”。当阈值降低到 60%时，所有变量都被归类为“基本”，共识变量增加到 26 个（31.7%）。这 25 个变量被纳入“零时初始病例调查”（T0）表中，该表与快速反应小组知识网络的成员共享，供现场测试和反馈。自 2019 年 9 月以来，该表一直可在世界卫生组织的网站上获得。
结论
这是首次用于确定疫情调查所需的最小变量的德尔菲流程。随后开发的 T0 表应有助于提高紧急情况下数据收集的效率和标准化，最终提高现场调查中收集的数据的质量。
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