Journal article
A guide to understanding big data for the nurse scientist: A discursive paper
Nursing inquiry, Vol.31(3), e12648
07/2024
DOI: 10.1111/nin.12648
PMID: 38865286
Abstract
Big data refers to extremely large data generated at high volume, velocity, variety, and veracity. The nurse scientist is uniquely positioned to leverage big data to suggest novel hypotheses on patient care and the healthcare system. The purpose of this paper is to provide an introductory guide to understanding the use and capability of big data for nurse scientists. Herein, we discuss the practical, ethical, social, and educational implications of using big data in nursing research. Some practical challenges with the use of big data include data accessibility, data quality, missing data, variable data standards, fragmentation of health data, and software considerations. Opposing ethical positions arise with the use of big data, and arguments for and against the use of big data are underpinned by concerns about confidentiality, anonymity, and autonomy. The use of big data has health equity dimensions and addressing equity in data is an ethical imperative. There is a need to incorporate competencies needed to leverage big data for nursing research into advanced nursing educational curricula. Nursing science has a great opportunity to evolve and embrace the potential of big data. Nurse scientists should not be spectators but collaborators and drivers of policy change to better leverage and harness the potential of big data.Big data refers to extremely large data generated at high volume, velocity, variety, and veracity. The nurse scientist is uniquely positioned to leverage big data to suggest novel hypotheses on patient care and the healthcare system. The purpose of this paper is to provide an introductory guide to understanding the use and capability of big data for nurse scientists. Herein, we discuss the practical, ethical, social, and educational implications of using big data in nursing research. Some practical challenges with the use of big data include data accessibility, data quality, missing data, variable data standards, fragmentation of health data, and software considerations. Opposing ethical positions arise with the use of big data, and arguments for and against the use of big data are underpinned by concerns about confidentiality, anonymity, and autonomy. The use of big data has health equity dimensions and addressing equity in data is an ethical imperative. There is a need to incorporate competencies needed to leverage big data for nursing research into advanced nursing educational curricula. Nursing science has a great opportunity to evolve and embrace the potential of big data. Nurse scientists should not be spectators but collaborators and drivers of policy change to better leverage and harness the potential of big data.
Details
- Title: Subtitle
- A guide to understanding big data for the nurse scientist: A discursive paper
- Creators
- Henry Ofori Duah - University of Cincinnati Medical CenterSamantha Boch - University of Cincinnati Medical CenterSara Arter - Miami UniversityNichole Nidey - University of IowaJoshua Lambert - University of Cincinnati Medical Center
- Resource Type
- Journal article
- Publication Details
- Nursing inquiry, Vol.31(3), e12648
- DOI
- 10.1111/nin.12648
- PMID
- 38865286
- NLM abbreviation
- Nurs Inq
- ISSN
- 1440-1800
- eISSN
- 1440-1800
- Language
- English
- Electronic publication date
- 06/12/2024
- Date published
- 07/2024
- Academic Unit
- Epidemiology; Addiction Medicine; Craniofacial Anomalies Research Center
- Record Identifier
- 9984641960202771
Metrics
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