Objectives: This study analyzed publications in Healthcare Informatics Research (HIR) to identify trends and shifts in research focus within both the journal and the broader Korean medical informatics landscape. By examining keywords across these papers, the study aimed to elucidate evolving priorities and innovations in the field over time.
Methods: Data from 958 papers published between 1995 and 2024 were extracted from the HIR journal's online archive. The analysis focused on English-language articles published since 2010 (n = 658) to examine publication trends using descriptive statistics. Keyword and Medical Subject Headings (MeSH) term analyses (term frequency-inverse document frequency, latent Dirichlet allocation, co-occurrence) were performed on a subset of articles with available abstracts (n = 632) to identify research themes and interrelationships. Inferential statistics, including chi-square and regression analysis, were applied to assess changes in research trends over time.
Results: Among 958 total papers identified (672 in English), analysis of 658 English articles published since 2010 revealed increasing publication trends, peaking between 2015 and 2018. Keyword and MeSH term analyses of 632 papers with abstracts highlighted persistent themes (e.g., health systems, electronic health records) alongside emerging topics (e.g., machine learning, telemedicine). Inferential analysis indicated no statistically significant changes in keyword distribution over time.
Conclusions: This study offers insights into the evolution of health informatics research in Korea, underscoring the role of HIR in documenting this progression. The findings reveal a balance between emerging technologies and foundational healthcare themes, demonstrating the field's adaptability and sustained relevance. Future research should extend the analysis to other journals and further consider ethical implications and global developments.
Keywords: Bibliometrics; Information Management; Medical Informatics; Medical Subject Headings; Natural Language Processing.