Dixon Brian E, Holmes John H
Department of Health Policy & Management, Richard M. Fairbanks School of Public Health, Indiana University, Indianapolis, IN, USA.
Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, IN, USA.
Yearb Med Inform. 2024 Aug;33(1):70-72. doi: 10.1055/s-0044-1800721. Epub 2025 Apr 8.
To identify notable research contributions relevant to digital health applications for precision prevention published in 2023.
An extensive search was conducted to identify peer-reviewed articles published in 2023 that examined ways that informatics approaches and digital health applications could facilitate precision prevention. The selection process comprised three steps: 1) candidate best papers were first selected by the two section editors; 2) a diverse, international group of external informatics subject matter experts reviewed each candidate best paper; and 3) the final selection of four best papers was conducted by the editorial committee of the Yearbook. The section editors attempted to balance selection by authors' global region and areas with clinical medicine and public health.
Selected best papers represent studies that advanced knowledge surrounding the use of digital health applications to facilitate precision prevention. In general, papers identified in the search fell into one of the following categories: 1) applications in precision nutrition; 2) applications in precision medicine; and 3) applications in precision public health. The best papers spanned several disease targets, including Alzheimer's disease, HIV, and COVID-19. Several candidate papers sought to improve prediction of disease onset, whereas others focused on predicting response to interventions.
Although the selected papers are notable, significant work is needed to realize the full potential for precision prevention using digital health. Current data and applications only scratch the surface of the potential that information technologies can bring to support primary and secondary prevention in support of health and well-being for all populations globally.
识别2023年发表的与精准预防数字健康应用相关的显著研究贡献。
进行了广泛的检索,以识别2023年发表的、探讨信息学方法和数字健康应用可促进精准预防方式的同行评议文章。选择过程包括三个步骤:1)首先由两位栏目编辑选出候选最佳论文;2)一个多元化的国际信息学主题专家小组对每篇候选最佳论文进行评审;3)由年鉴编辑委员会最终选出四篇最佳论文。栏目编辑试图在按作者所在全球区域以及临床医学和公共卫生领域进行选择之间取得平衡。
入选的最佳论文代表了围绕使用数字健康应用促进精准预防的知识进展研究。总体而言,检索中确定的论文属于以下类别之一:1)精准营养中的应用;2)精准医学中的应用;3)精准公共卫生中的应用。最佳论文涵盖多个疾病靶点,包括阿尔茨海默病、艾滋病病毒和2019冠状病毒病。几篇候选论文试图改善疾病发病预测,而其他论文则专注于预测对干预措施的反应。
尽管入选的论文很显著,但要实现利用数字健康进行精准预防的全部潜力,仍需要开展大量工作。当前的数据和应用仅触及了信息技术在支持全球所有人群的健康和福祉方面进行一级和二级预防的潜力的表面。