Offord Centre for Child Studies, 3710McMaster University, Hamilton, Ontario, Canada.
Can J Psychiatry. 2022 Feb;67(2):101-103. doi: 10.1177/07067437211016255. Epub 2021 May 10.
Population-based prevalence estimates of mental illness are foundational to health service planning, strategic resource allocation, and the development and evaluation of public mental health policy. Generating valid, reliable, and context-specific population-level estimates is of utmost importance and can be achieved by combining various data sources. This pursuit benefits from the right combination of theory, applied statistics, and the conceptualization of available data sources as a collective rather than in isolation. We believe there is a need to read between the lines as theory, methodology, and context (i.e., strengths and limitations) are what determines the meaningfulness of a combined prevalence estimate. Currently lacking is a gold standard approach to combining estimates from multiple data sources. Here, we compare and contrast various approaches to combining data and introduce an idea that leverages the strengths of pre-existing individually linked population-based survey and health administrative data sources currently available in Canada.
基于人群的精神疾病患病率估计对于卫生服务规划、战略资源分配以及公共精神卫生政策的制定和评估至关重要。通过结合各种数据源，可以生成有效、可靠和具体情境的人群水平估计值。这一追求得益于理论、应用统计学以及将现有数据源概念化为一个整体而不是孤立的理论的正确结合。我们认为，需要深入研究理论、方法和背景（即优势和局限性），因为这些因素决定了综合患病率估计的意义。目前缺乏一种结合多个数据源的估计值的黄金标准方法。在这里，我们比较和对比了各种结合数据的方法，并提出了一种利用加拿大现有的、预先存在的个体关联的基于人群的调查和健康管理数据源的优势的想法。
