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Data Mining in Nursing: A Bibliometric Analysis (1990-2017).

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Data mining in nursing is rapidly growing, with most applications in clinical settings. Research trends differ between Chinese and English papers, focusing on knowledge discovery versus practice improvement.

Keywords:
Bibliometric analysisData miningNursing informatics

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Area of Science:

  • Nursing Informatics
  • Data Science
  • Health Services Research

Background:

  • Data mining applications in nursing have seen significant growth since 1990.
  • A systematic review was conducted to analyze trends and future directions.
  • The study encompasses both English and Chinese literature.

Purpose of the Study:

  • To systematically review and analyze the trends and future directions of data mining in nursing.
  • To identify the primary applications and research focus of data mining in nursing.
  • To compare the focus of data mining research in Chinese and English nursing literature.

Main Methods:

  • Systematic literature search of English and Chinese databases.
  • Inclusion of keywords related to data mining and nursing.
  • Analysis of 407 retrieved papers published between 1990 and 2017.

Main Results:

  • A rapid increase in data mining publications in nursing was observed in the five years preceding 2017.
  • Clinical nursing represented the most common application area, accounting for 50.6% of studies.
  • Chinese papers predominantly focused on discovering new nursing knowledge and rules.
  • English papers emphasized leveraging data mining to enhance and promote nursing practice.

Conclusions:

  • Data mining is an increasingly important tool in nursing research and practice.
  • Future research should consider the distinct focuses observed in different language publications.
  • The findings highlight the potential for data mining to advance nursing knowledge and improve patient care.