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Public Health and Epidemiology Informatics: Recent Research Trends

机译:公共卫生与流行病学信息学:最近的研究趋势

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摘要

Objectives: To introduce and analyse current trends in Public Health and Epidemiology Informatics. Methods: PubMed search of 2020 literature on public health and epidemiology informatics was conducted and all retrieved references were reviewed by the two section editors. Then, 15 candidate best papers were selected among the 920 references. These papers were then peer-reviewed by the two section editors, two chief editors, and external reviewers, including at least two senior faculty, to allow the Editorial Committee of the 2021 International Medical Informatics Association (IMIA) Yearbook to make an informed decision regarding the selection of the best papers. Results: Among the 920 references retrieved from PubMed, four were suggested as best papers and the first three were finally selected. The fourth paper was excluded because of reproducibility issues. The first best paper is a very public health focused paper with health informatics and biostatistics methods applied to stratify patients within a cohort in order to identify those at risk of suicide; the second paper describes the use of a randomized design to test the likely impact of fear-based messages, with and without empowering self-management elements, on patient consultations or antibiotic requests for influenza-like illnesses. The third selected paper evaluates the perception among communities of routine use of Whole Genome Sequencing and Big Data technologies to capture more detailed and specific personal information. Conclusions: The findings from the three studies suggest that using Public Health and Epidemiology Informatics methods could leverage, when combined with Deep Learning, early interventions and appropriate treatments to mitigate suicide risk. Further, they also demonstrate that well informing and empowering patients could help them to be involved more in their care process.
机译:目标: 介绍和分析公共卫生和流行病学信息学的当前趋势。方法: 对 2020 年公共卫生和流行病学信息学文献进行 PubMed 检索,所有检索到的参考文献均由两个部分编辑审查。然后从 920 篇参考文献中选出 15 篇候选最佳论文。然后,这些论文由两名栏目编辑、两名主编和外部审稿人(包括至少两名高级教师)进行同行评审,以便 2021 年国际医学信息学协会 (IMIA) 年鉴的编辑委员会就最佳论文的选择做出明智的决定。结果: 在从 PubMed 检索到的 920 篇参考文献中,有 4 篇被建议为最佳论文,前 3 篇最终被选中。由于可重复性问题,第四篇论文被排除在外。第一篇最佳论文是一篇非常注重公共卫生的论文,采用健康信息学和生物统计学方法对队列中的患者进行分层,以识别有自杀风险的患者;第二篇论文描述了使用随机设计来测试基于恐惧的信息(有和没有授权自我管理元素)对流感样疾病的患者咨询或抗生素请求的可能影响。第三篇入选论文评估了社区对常规使用全基因组测序和大数据技术来捕获更详细和具体的个人信息的看法。结论:这三项研究的结果表明,当与深度学习相结合时,使用公共卫生和流行病学信息学方法可以利用早期干预和适当的治疗来降低自杀风险。此外,他们还表明,充分告知和赋予患者权力可以帮助他们更多地参与他们的护理过程。

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