Artificial Intelligence in Nursing Decision-Making: A Bibliometric Analysis of Trends and Impacts
<b>Background:</b> Nursing decision-making is pivotal for patient safety and care quality. While artificial intelligence (AI) offers transformative potential in this field, a comprehensive analysis of global research trends is lacking. <b>Methods:</b> We conducted a bibliomet...
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MDPI AG
2025-06-01
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| Series: | Nursing Reports |
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| author | Mengdie Hu Yan Wang Yunsong Liu Bingqing Cai Fanjing Kong Qian Zheng Dan Zhao Guanghui Gao Zhouguang Hui |
| author_facet | Mengdie Hu Yan Wang Yunsong Liu Bingqing Cai Fanjing Kong Qian Zheng Dan Zhao Guanghui Gao Zhouguang Hui |
| author_sort | Mengdie Hu |
| collection | DOAJ |
| description | <b>Background:</b> Nursing decision-making is pivotal for patient safety and care quality. While artificial intelligence (AI) offers transformative potential in this field, a comprehensive analysis of global research trends is lacking. <b>Methods:</b> We conducted a bibliometric analysis of 238 publications (197 research papers, 41 reviews) from the Web of Science Core Collection (2003–2025) using CiteSpace and VOSviewer. <b>Results:</b> The results reveal growing interest (7.59% annually) in the field of AI in nursing decision-making, with contributions from 54 countries/regions. The USA leads in the number of publications, followed by China and Canada, while the United Kingdom stands out in terms of citation impact. Institutions such as Columbia University and Harvard Medical School dominate in both the publication volume and citation frequency. Journal analysis shows that the top three journals in terms of publication volume in this field are <i>Cin-Computers Informatics Nursing</i>, <i>Journal of Nursing Management</i>, and <i>Applied Clinical Informatics</i>. Keyword analysis highlights the significant potential of natural language processing technologies, particularly those based on large language models (e.g., ChatGPT), in nursing decision-making. Furthermore, emerging trends are evident, with the sudden appearance and rapid growth of keywords such as “patient safety” and “user acceptance”, indicating a shift in research focus from purely technology-driven studies to a greater emphasis on the practical impact of AI technologies on nursing systems and their clinical applications. <b>Conclusions:</b> This study delineates the current landscape and evolving trends of AI in nursing decision-making, emphasizing its progression from theoretical frameworks to clinical integration, thereby providing valuable references for future research. |
| format | Article |
| id | doaj-art-f3d89f7dd05b455dbf268e59976b8ed6 |
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| issn | 2039-439X 2039-4403 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Nursing Reports |
| spelling | doaj-art-f3d89f7dd05b455dbf268e59976b8ed62025-06-25T14:15:32ZengMDPI AGNursing Reports2039-439X2039-44032025-06-0115619810.3390/nursrep15060198Artificial Intelligence in Nursing Decision-Making: A Bibliometric Analysis of Trends and ImpactsMengdie Hu0Yan Wang1Yunsong Liu2Bingqing Cai3Fanjing Kong4Qian Zheng5Dan Zhao6Guanghui Gao7Zhouguang Hui8Department of VIP Medical Services, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, ChinaDepartment of VIP Medical Services, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, ChinaChina Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, ChinaDepartment of VIP Medical Services, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, ChinaDepartment of VIP Medical Services, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, ChinaDepartment of VIP Medical Services, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, ChinaDepartment of VIP Medical Services, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, ChinaDepartment of VIP Medical Services, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, ChinaDepartment of VIP Medical Services, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China<b>Background:</b> Nursing decision-making is pivotal for patient safety and care quality. While artificial intelligence (AI) offers transformative potential in this field, a comprehensive analysis of global research trends is lacking. <b>Methods:</b> We conducted a bibliometric analysis of 238 publications (197 research papers, 41 reviews) from the Web of Science Core Collection (2003–2025) using CiteSpace and VOSviewer. <b>Results:</b> The results reveal growing interest (7.59% annually) in the field of AI in nursing decision-making, with contributions from 54 countries/regions. The USA leads in the number of publications, followed by China and Canada, while the United Kingdom stands out in terms of citation impact. Institutions such as Columbia University and Harvard Medical School dominate in both the publication volume and citation frequency. Journal analysis shows that the top three journals in terms of publication volume in this field are <i>Cin-Computers Informatics Nursing</i>, <i>Journal of Nursing Management</i>, and <i>Applied Clinical Informatics</i>. Keyword analysis highlights the significant potential of natural language processing technologies, particularly those based on large language models (e.g., ChatGPT), in nursing decision-making. Furthermore, emerging trends are evident, with the sudden appearance and rapid growth of keywords such as “patient safety” and “user acceptance”, indicating a shift in research focus from purely technology-driven studies to a greater emphasis on the practical impact of AI technologies on nursing systems and their clinical applications. <b>Conclusions:</b> This study delineates the current landscape and evolving trends of AI in nursing decision-making, emphasizing its progression from theoretical frameworks to clinical integration, thereby providing valuable references for future research.https://www.mdpi.com/2039-4403/15/6/198artificial intelligencenursingdecision makingbibliometrics |
| spellingShingle | Mengdie Hu Yan Wang Yunsong Liu Bingqing Cai Fanjing Kong Qian Zheng Dan Zhao Guanghui Gao Zhouguang Hui Artificial Intelligence in Nursing Decision-Making: A Bibliometric Analysis of Trends and Impacts Nursing Reports artificial intelligence nursing decision making bibliometrics |
| title | Artificial Intelligence in Nursing Decision-Making: A Bibliometric Analysis of Trends and Impacts |
| title_full | Artificial Intelligence in Nursing Decision-Making: A Bibliometric Analysis of Trends and Impacts |
| title_fullStr | Artificial Intelligence in Nursing Decision-Making: A Bibliometric Analysis of Trends and Impacts |
| title_full_unstemmed | Artificial Intelligence in Nursing Decision-Making: A Bibliometric Analysis of Trends and Impacts |
| title_short | Artificial Intelligence in Nursing Decision-Making: A Bibliometric Analysis of Trends and Impacts |
| title_sort | artificial intelligence in nursing decision making a bibliometric analysis of trends and impacts |
| topic | artificial intelligence nursing decision making bibliometrics |
| url | https://www.mdpi.com/2039-4403/15/6/198 |
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