Visualising nursing data using correspondence analysis
Evidence & Practice    

Visualising nursing data using correspondence analysis

Peter Kokol Professor, Faculty of Electrical Engineering and Computer Science, University of Maribor, Maribor, Slovenia
Helena Blažun Vošner Head, Faculty of Health Sciences, Center for International Cooperation, University of Maribor
Danica Železnik Dean, University College of Health Sciences, Slovenj Gradec, Slovenia
Background

Digitally stored, large healthcare datasets enable nurses to use ‘big data’ techniques and tools in nursing research. Big data is complex and multi-dimensional, so visualisation may be a preferable approach to analyse and understand it.

Aim

To demonstrate the use of visualisation of big data in a technique called correspondence analysis.

Discussion

In the authors’ study, relations among data in a nursing dataset were shown visually in graphs using correspondence analysis. The case presented demonstrates that correspondence analysis is easy to use, shows relations between data visually in a form that is simple to interpret, and can reveal hidden associations between data.

Conclusion

Correspondence analysis supports the discovery of new knowledge.

Implications for practice

Knowledge obtained using correspondence analysis can be transferred immediately into practice or used to foster further research.

Nurse Researcher. doi: 10.7748/nr.2016.e1441

Correspondence

peter.kokol@um.si

Peer review

This article has been subject to double-blind review and has been checked for plagiarism using automated software

Received: 25 October 2015

Accepted: 17 March 2016

Published online: 04 August 2016