Bibliometric Analysis of Development Trends and Research Hotspots in the Study of Data Mining in Nursing Based on CiteSpace

Abstract

Backgrounds: With the advent of the big data era, hospital information systems and mobile care systems, among others, generate massive amounts of medical data. Data mining, as a powerful information processing technology, can discover non-obvious information by processing large-scale data and analyzing them in multiple dimensions. How to find the effective information hidden in the database and apply it to nursing clinical practice has received more and more attention from nursing researchers.

Aim: To look over the articles on data mining in nursing, compiled research status, identified hotspots, highlighted research trends, and offer recommendations for how data mining technology might be used in the nursing area going forward.

Methods: Data mining in nursing publications published between 2002 and 2023 were taken from the Web of Science Core Collection. CiteSpace was utilized for reviewing the number of articles, countries/regions, institutions, journals, authors, and keywords.

Results: According to the findings, the pace of data mining in nursing progress is not encouraging. Nursing data mining research is dominated by the United States and China. However, no consistent core group of writers or organizations has emerged in the field of nursing data mining. Studies on data mining in nursing have been increasingly gradually conducted in the 21st century, but the overall number is not large. Institution of Columbia University, journal of Cin-computers Informatics Nursing, author Diana J Wilkie, Muhammad Kamran Lodhi, Yingwei Yao are most influential in nursing data mining research. Nursing data mining researchers are currently focusing on electronic health records, text mining, machine learning, and natural language processing. Future research themes in data mining in nursing most include nursing informatics and clinical care quality enhancement.

Conclusion: Research data shows that data mining gives more perspectives for the growth of the nursing discipline and encourages the discipline's development, but it also introduces a slew of new issues that need researchers to address.

Keywords: bibliometric analysis; data mining; global trends; hotspots; nursing.

Figure 1

Trend chart of the number of articles published on data mining in nursing.

Figure 2

Co-countries’ network (2002–2023).

Figure 3

Co- Institutions’ network (2002–2023).

Figure 4

Co-Authors’ network (2002–2023).

Figure 5

Keyword co-occurrence map (2000–2022).

Figure 6

Burst map of keywords (2002–2023).

Figure 7

Clustering map of keywords (2002–2023).

Figure 8

Timeline map of keywords (2002–2023).