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A guide to understanding big data for the nurse scientist: A discursive paper
Henry Ofori Duah1, Samantha Boch1,2, Sara Arter3
1College of Nursing, University of Cincinnati, Cincinnati, Ohio, USA.
Nursing Inquiry
|June 12, 2024
Summary
Nurse scientists can use big data to generate new patient care hypotheses. This guide explores the practical, ethical, and educational aspects of big data in nursing research.
Area of Science:
- Nursing Science
- Health Informatics
- Data Science
Background:
- Big data, characterized by volume, velocity, variety, and veracity, presents significant opportunities for healthcare research.
- Nurse scientists are strategically positioned to utilize big data for generating novel hypotheses in patient care and healthcare systems.
- Understanding the implications of big data is crucial for advancing nursing science.
Purpose of the Study:
- To provide an introductory guide for nurse scientists on the use and capabilities of big data.
- To discuss the practical, ethical, social, and educational implications of big data in nursing research.
Main Methods:
- This paper offers a conceptual overview and discussion of big data in nursing research.
- It addresses challenges and opportunities associated with big data utilization.
- Ethical considerations, including confidentiality, anonymity, and autonomy, are examined.
Main Results:
- Practical challenges include data accessibility, quality, standardization, and fragmentation.
- Ethical debates involve balancing data utility with patient privacy and autonomy.
- Health equity dimensions and the need for data equity are highlighted.
Conclusions:
- Advanced nursing education curricula should integrate big data competencies.
- Nurse scientists must actively engage as collaborators and policy drivers in leveraging big data.
- Embracing big data is essential for the evolution of nursing science.
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