Evaluating a Nationwide Neonatal Research Infrastructure: A Bibliometric Network Analysis of the Korean Neonatal Network

Background/Objectives: Since the establishment of the Korean Neonatal Network (KNN) in 2013, numerous studies have been conducted using its nationwide registry of very low birth weight infants (VLBWIs). Beyond serving as a clinical database, the KNN has evolved into a national healthcare research infrastructure supporting multicenter collaboration, evidence generation, and quality improvement in neonatal care. This study aimed to evaluate the scientific productivity, collaborative structure, and knowledge-generation capacity of the KNN through bibliometric network analysis and to identify future research directions in Korean neonatal research. Methods: Publications from 1 January 2015 to 5 June 2024 were retrieved from the Web of Science Core Collection. Literature searches were performed using Medical Subject Headings (MeSH), Emtree terms, and related keywords associated with very low birth weight infants, extremely low birth weight infants, and the Korean Neonatal Network. A total of 7060 global publications and 86 KNN-related publications were identified for analysis. Co-authorship and keyword co-occurrence analyses were conducted using VOSviewer to evaluate international collaborations, research themes, and temporal trends in keyword emergence. Scimago Graphica was used to visualize keyword evolution, and burst detection analysis was performed using CiteSpace to identify emerging research topics. Results: Among global publications on VLBWIs, South Korea ranked 13th worldwide with 226 publications and demonstrated substantial international collaboration, particularly with researchers in the United States. Analysis of the 86 KNN-related publications revealed the rapid development of observational and topic-focused research areas within a relatively short period. Keyword clustering and temporal analyses demonstrated a progressive expansion of research interests as the database matured. Burst analysis identified emerging themes related to mortality and morbidity risk factors, neurodevelopmental outcomes, and predictive modeling using machine learning techniques. Conclusions: Bibliometric analysis demonstrated that research based on the KNN has largely followed global trends in neonatal research despite its relatively recent establishment. The KNN has successfully functioned as a nationwide research infrastructure facilitating collaborative knowledge generation and scientific productivity. Nevertheless, several underrepresented research areas and opportunities for broader international collaboration were identified. These findings may help guide future research strategies and maximize the impact of national neonatal registry-based healthcare systems.