ArticleHealthcare informatics research2025
Tracking the Evolution of Research Topics in Healthcare Informatics Research Using Keywords and MeSH Terms.
Article in Healthcare informatics research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- First-Line Treatment of IGHV-Unmutated Chronic Lymphocytic Leukemia: A Network Meta-Analysis of Targeted and Chemoimmunotherapy Regimens.European journal of haematology · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
objectivesThis 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.
methodsData 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.
resultsAmong 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.
conclusionsThis 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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.