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Generating new knowledge from existing data: the use of large data sets for nursing research
Tracy Magee1, Susan M Lee, Karen K Giuliano
1Department of Maternal Child Nursing, University of Illinois at Chicago, Chicago, IL 60637, USA. tramagee@uic.edu
Nursing Research
|April 8, 2006
Summary
Nurse researchers can leverage existing large datasets for timely and cost-efficient studies. Analyzing secondary data offers unique opportunities to answer critical nursing questions and improve patient care.
Area of Science:
- Nursing Research
- Data Science
- Health Informatics
Background:
- Abundant data from diverse disciplines are available for nursing research.
- Secondary data analysis is an emerging method for knowledge translation in nursing practice.
Purpose of the Study:
- To explore methodological issues and practical applications of secondary data analysis in nursing.
- To guide nurse researchers in utilizing large, existing datasets for new nursing knowledge generation.
Main Methods:
- Analysis of three existing large datasets across three research studies.
- Discussion of developing theoretical frameworks, data set selection, variable operationalization, data preparation, and validity/reliability assessment.
Main Results:
- Secondary data analysis, while time-efficient, maintains the rigor of the research process.
- Illustrated conceptual congruence, internal/external validity threats, and reliability/generalizability issues using case studies.
Conclusions:
- Existing large datasets are valuable resources for answering nursing practice and research questions.
- Secondary data analysis provides a time- and cost-efficient pathway for nursing research, impacting patient care.
- Understanding methodological challenges is key for successful secondary data utilization in nursing.