{"title":"重症监护病房临床决策支持系统的研究主题与趋势：文献计量学分析。","authors":"Xun Deng, Lu Liu, Tingting Peng, Shan Zhang","doi":"10.1111/nicc.70112","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Hospital administrators apply information technology to improve healthcare quality; however, a comprehensive bibliometric analysis remains limited.</p><p><strong>Aim: </strong>To explore the research topic, key contributors and development trends of clinical decision support systems (CDSS) in intensive care units (ICUs).</p><p><strong>Study design: </strong>Between January 1, 2014, and December 31, 2024, a bibliometric analysis was undertaken. CiteSpace software was used to conduct a visual analysis of literature retrieved from the Web of Science Core Collection database. Publishing countries, institutions, authors, cited journals and keywords were reported.</p><p><strong>Results: </strong>A total of 817 articles were included in the final analysis. The annual publication volume showed an overall upward trend. The United States was the country with the highest number of publications (338 articles, 41.37%), and the University of Pittsburgh was the most prolific institution (29 articles, 3.55%). Herasevich, Vitaly from Mayo Clinic, Dept Anesthesiol, was the most prolific author (8 articles, 0.98%). Critical Care Medicine was the most cited journal (n = 421). Research hotspots primarily focused on the integration of CDSS with clinical practice, intelligent decision support-driven precision ICU care and the effectiveness of CDSS in managing ICU patients. Research trends centred on prediction, respiratory distress syndrome and artificial intelligence.</p><p><strong>Conclusions: </strong>This study highlights key research areas in CDSS applications in ICUs, focusing on clinical integration, precision care and patient management, offering insights for improving healthcare quality.</p><p><strong>Relevance to clinical practice: </strong>The findings from this bibliometric analysis can assist ICU nurses in advancing research on integrating CDSS into ICU practices, developing intelligent decision support tools and addressing gaps in precision care, prediction models and AI-driven solutions to enhance patient outcomes and optimise critical care management.</p>","PeriodicalId":51264,"journal":{"name":"Nursing in Critical Care","volume":"30 4","pages":"e70112"},"PeriodicalIF":3.0000,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Research Topics and Trends of Clinical Decision Support Systems in Intensive Care Units: A Bibliometric Analysis.\",\"authors\":\"Xun Deng, Lu Liu, Tingting Peng, Shan Zhang\",\"doi\":\"10.1111/nicc.70112\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Hospital administrators apply information technology to improve healthcare quality; however, a comprehensive bibliometric analysis remains limited.</p><p><strong>Aim: </strong>To explore the research topic, key contributors and development trends of clinical decision support systems (CDSS) in intensive care units (ICUs).</p><p><strong>Study design: </strong>Between January 1, 2014, and December 31, 2024, a bibliometric analysis was undertaken. CiteSpace software was used to conduct a visual analysis of literature retrieved from the Web of Science Core Collection database. Publishing countries, institutions, authors, cited journals and keywords were reported.</p><p><strong>Results: </strong>A total of 817 articles were included in the final analysis. The annual publication volume showed an overall upward trend. The United States was the country with the highest number of publications (338 articles, 41.37%), and the University of Pittsburgh was the most prolific institution (29 articles, 3.55%). Herasevich, Vitaly from Mayo Clinic, Dept Anesthesiol, was the most prolific author (8 articles, 0.98%). Critical Care Medicine was the most cited journal (n = 421). Research hotspots primarily focused on the integration of CDSS with clinical practice, intelligent decision support-driven precision ICU care and the effectiveness of CDSS in managing ICU patients. Research trends centred on prediction, respiratory distress syndrome and artificial intelligence.</p><p><strong>Conclusions: </strong>This study highlights key research areas in CDSS applications in ICUs, focusing on clinical integration, precision care and patient management, offering insights for improving healthcare quality.</p><p><strong>Relevance to clinical practice: </strong>The findings from this bibliometric analysis can assist ICU nurses in advancing research on integrating CDSS into ICU practices, developing intelligent decision support tools and addressing gaps in precision care, prediction models and AI-driven solutions to enhance patient outcomes and optimise critical care management.</p>\",\"PeriodicalId\":51264,\"journal\":{\"name\":\"Nursing in Critical Care\",\"volume\":\"30 4\",\"pages\":\"e70112\"},\"PeriodicalIF\":3.0000,\"publicationDate\":\"2025-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Nursing in Critical Care\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1111/nicc.70112\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"NURSING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nursing in Critical Care","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1111/nicc.70112","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"NURSING","Score":null,"Total":0}
Research Topics and Trends of Clinical Decision Support Systems in Intensive Care Units: A Bibliometric Analysis.
Background: Hospital administrators apply information technology to improve healthcare quality; however, a comprehensive bibliometric analysis remains limited.
Aim: To explore the research topic, key contributors and development trends of clinical decision support systems (CDSS) in intensive care units (ICUs).
Study design: Between January 1, 2014, and December 31, 2024, a bibliometric analysis was undertaken. CiteSpace software was used to conduct a visual analysis of literature retrieved from the Web of Science Core Collection database. Publishing countries, institutions, authors, cited journals and keywords were reported.
Results: A total of 817 articles were included in the final analysis. The annual publication volume showed an overall upward trend. The United States was the country with the highest number of publications (338 articles, 41.37%), and the University of Pittsburgh was the most prolific institution (29 articles, 3.55%). Herasevich, Vitaly from Mayo Clinic, Dept Anesthesiol, was the most prolific author (8 articles, 0.98%). Critical Care Medicine was the most cited journal (n = 421). Research hotspots primarily focused on the integration of CDSS with clinical practice, intelligent decision support-driven precision ICU care and the effectiveness of CDSS in managing ICU patients. Research trends centred on prediction, respiratory distress syndrome and artificial intelligence.
Conclusions: This study highlights key research areas in CDSS applications in ICUs, focusing on clinical integration, precision care and patient management, offering insights for improving healthcare quality.
Relevance to clinical practice: The findings from this bibliometric analysis can assist ICU nurses in advancing research on integrating CDSS into ICU practices, developing intelligent decision support tools and addressing gaps in precision care, prediction models and AI-driven solutions to enhance patient outcomes and optimise critical care management.
期刊介绍：
Nursing in Critical Care is an international peer-reviewed journal covering any aspect of critical care nursing practice, research, education or management. Critical care nursing is defined as the whole spectrum of skills, knowledge and attitudes utilised by practitioners in any setting where adults or children, and their families, are experiencing acute and critical illness. Such settings encompass general and specialist hospitals, and the community. Nursing in Critical Care covers the diverse specialities of critical care nursing including surgery, medicine, cardiac, renal, neurosciences, haematology, obstetrics, accident and emergency, neonatal nursing and paediatrics.
Papers published in the journal normally fall into one of the following categories:
-research reports
-literature reviews
-developments in practice, education or management
-reflections on practice
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