Transforming Pediatric Care Through AI: Bridging the Digital Divide in Global Health Informatics (Preprint)

<sec> <title>UNSTRUCTURED</title> Health informatics and artificial intelligence (AI) technologies present unprecedented opportunities for transforming pediatric healthcare delivery globally. Following post-pandemic digital health acceleration and rising demands for equitable pediatric care, this viewpoint explores how public health informatics systems, combined with AI-powered clinical decision support systems, electronic health record (EHR) integration, and telemedicine platforms, can enhance pediatric care quality and accessibility. Case studies analyzing the Pediatric Emergency Care Applied Research Network (PECARN) clinical decision rules, AI-enhanced neonatal sepsis detection systems, and automated autism screening protocols demonstrate successful health informatics implementations in pediatric settings. Key benefits include improved diagnostic accuracy through computer-aided detection, personalized treatment protocols facilitated by clinical decision support, enhanced accessibility via telehealth platforms, and early intervention capabilities enabled by predictive modeling. However, implementation faces significant challenges, including issues with health information system interoperability, data standardization, gaps in digital health infrastructure, and concerns regarding health equity and access to technology. Strategic recommendations emphasize collaborative development of interoperable health information systems, standardized data governance frameworks, and equitable digital health infrastructure to ensure global pediatric care transformation through public health informatics innovation. </sec>

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Publication Details

Published
2025-08-09
DOI
https://doi.org/10.2196/preprints.82108
Primary Topic
Mobile Health and mHealth Applications
Type
article
Field-Weighted Citation Impact
0.00
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article

Transforming Pediatric Care Through AI: Bridging the Digital Divide in Global Health Informatics (Preprint)

R Sterling Snead, Radha Ambalavanan, Julia Marczika, Gideon Towett et al.
Mobile Health and mHealth Applications
article

Transforming Pediatric Care Through AI: Bridging the Digital Divide in Global Health Informatics (Preprint)

R Sterling Snead, Radha Ambalavanan, Julia Marczika, Gideon Towett, Alex Malioukis, Mercy Mbogori Kairichi
article en

Abstract

<sec> <title>UNSTRUCTURED</title> Health informatics and artificial intelligence (AI) technologies present unprecedented opportunities for transforming pediatric healthcare delivery globally. Following post-pandemic digital health acceleration and rising demands for equitable pediatric care, this viewpoint explores how public health informatics systems, combined with AI-powered clinical decision support systems, electronic health record (EHR) integration, and telemedicine platforms, can enhance pediatric care quality and accessibility. Case studies analyzing the Pediatric Emergency Care Applied Research Network (PECARN) clinical decision rules, AI-enhanced neonatal sepsis detection systems, and automated autism screening protocols demonstrate successful health informatics implementations in pediatric settings. Key benefits include improved diagnostic accuracy through computer-aided detection, personalized treatment protocols facilitated by clinical decision support, enhanced accessibility via telehealth platforms, and early intervention capabilities enabled by predictive modeling. However, implementation faces significant challenges, including issues with health information system interoperability, data standardization, gaps in digital health infrastructure, and concerns regarding health equity and access to technology. Strategic recommendations emphasize collaborative development of interoperable health information systems, standardized data governance frameworks, and equitable digital health infrastructure to ensure global pediatric care transformation through public health informatics innovation. </sec>

Openalex Percentile: Top 66%
Mobile Health and mHealth Applications
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