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CC BY 4.0 · Yearb Med Inform 2024; 33(01): 070-072
DOI: 10.1055/s-0044-1800721
Special Section: Digital Health for Precision in Prevention
Synopsis

Special Section on Digital Health for Precision in Prevention: Notable Papers that Leverage Informatics Approaches to Support Precision Prevention Efforts in Health Systems

Brian E. Dixon
1   Department of Health Policy & Management, Richard M. Fairbanks School of Public Health, Indiana University, Indianapolis, IN, USA
2   Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, IN, USA
,
John H. Holmes
3   Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
4   Institute for Biomedical Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
,
Section Editors of the Special Section on Inclusive Digital Health › Institutsangaben
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Summary

Objective: To identify notable research contributions relevant to digital health applications for precision prevention published in 2023.

Methods: 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.

Results: 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.

Conclusion: 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.

Keywords

Public Health Informatics - Primary Prevention - Secondary Prevention - Precision Medicine - Digital Health


Publikationsverlauf

Artikel online veröffentlicht:
08. April 2025

© 2024. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution License, permitting unrestricted use, distribution, and reproduction so long as the original work is properly cited. (https://creativecommons.org/licenses/by/4.0/)

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