VOSviewer-based content analysis of international papers (published in 2015–2024) on the quality and safety of ICU informatization
Year: 2025
Type: article
Abstract: Objective. The study is a VOSviewer-based content analysis of international publications regarding the implementation of information systems in intensive care units (ICUs) published in 2015–2024. Methodology. Publications were obtained from the international PubMed database using the terms “‘Informatics AND ‘Intensive Care Units’” in the Medical Subject Headings (MeSH). The study identified 1508 apapers published over the past decade (2015–2024). The titles underwent a systematic review to generate a .txt dataset; once saved, the dataset was fed into VOSviewer 1.6.20. In total, the dataset yielded 3977 keywords. Considering 8 term iterations and cluster merging for word combinations, the outcoming dataset comprised 258 keywords. Results and discussion. The VOSviewer was used to split the keywords into 7 clusters to represent specific topics covered by the text data regarding international ICU informatization research – general informatization and patient safety (30.1 % of papers with 26.8 % of total link strength), information and analytical support, Risk Assessment (15.9 % of papers with 17.9 % link strength), retrospective studies and databases (12.6 % of papers with 14 % link strength), application of artificial intelligence (10.6 % of papers with 11.5 % link strength); the last three clusters included improving outcomes for critically ill patients (cluster 5, neonatal care (cluster 6) and infection management (cluster 7), constituting a total 29.8 % of papers (29.8 % total link strength). Conclusion. The VOSviewer-based content analysis and clustering of international research papers provided insights into the key research dimensions regarding ICU informatization. The obtained results can improve the information support in emergency medical care research. The international PubMed database provides investigators with vast informational opportunities, with 65 % of full-text papers available for free.
Author: V. I. Gorban
Language: English
Subfield: Health Information Management
Field: Health Professions
Domain: Health Sciences
Open Access status: diamond
OpenAlex ID: W4411127308