The Need for a Definition of Big Data for Nursing Science: A Case Study of Disaster Preparedness

Ho Ting Wong, Vico Chung Lim Chiang, Kup Sze Choi and Alice Yuen Loke
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Ho Ting Wong: Disaster Nursing Task Force, School of Nursing, the Hong Kong Polytechnic University, Hong Kong, China
Vico Chung Lim Chiang: Disaster Nursing Task Force, School of Nursing, the Hong Kong Polytechnic University, Hong Kong, China
Kup Sze Choi: School of Nursing, the Hong Kong Polytechnic University, Hong Kong, China
Alice Yuen Loke: Disaster Nursing Task Force, School of Nursing, the Hong Kong Polytechnic University, Hong Kong, China

IJERPH, 2016, vol. 13, issue 10, 1-13

Abstract: The rapid development of technology has made enormous volumes of data available and achievable anytime and anywhere around the world. Data scientists call this change a data era and have introduced the term “Big Data”, which has drawn the attention of nursing scholars. Nevertheless, the concept of Big Data is quite fuzzy and there is no agreement on its definition among researchers of different disciplines. Without a clear consensus on this issue, nursing scholars who are relatively new to the concept may consider Big Data to be merely a dataset of a bigger size. Having a suitable definition for nurse researchers in their context of research and practice is essential for the advancement of nursing research. In view of the need for a better understanding on what Big Data is, the aim in this paper is to explore and discuss the concept. Furthermore, an example of a Big Data research study on disaster nursing preparedness involving six million patient records is used for discussion. The example demonstrates that a Big Data analysis can be conducted from many more perspectives than would be possible in traditional sampling, and is superior to traditional sampling. Experience gained from the process of using Big Data in this study will shed light on future opportunities for conducting evidence-based nursing research to achieve competence in disaster nursing.

Keywords: Big Data; disaster preparedness; research method (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2016
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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