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. 2022 Mar 22;12(3):e053447.
doi: 10.1136/bmjopen-2021-053447.

Big Data Reality Check (BDRC) for public health: to what extent the environmental health and health services research did meet the 'V' criteria for big data? A study protocol

Pui Pui Tang  1 , I Lam Tam  1 , Yongliang Jia  2   3 , Siu-Wai Leung  4   5
Affiliations

Big Data Reality Check (BDRC) for public health: to what extent the environmental health and health services research did meet the 'V' criteria for big data? A study protocol

Pui Pui Tang et al. BMJ Open. .

Abstract

Introduction: Big data technologies have been talked up in the fields of science and medicine. The V-criteria (volume, variety, velocity and veracity, etc) for defining big data have been well-known and even quoted in most research articles; however, big data research into public health is often misrepresented due to certain common misconceptions. Such misrepresentations and misconceptions would mislead study designs, research findings and healthcare decision-making. This study aims to identify the V-eligibility of big data studies and their technologies applied to environmental health and health services research that explicitly claim to be big data studies.

Methods and analysis: Our protocol follows Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols (PRISMA-P). Scoping review and/or systematic review will be conducted. The results will be reported using PRISMA for Scoping Reviews (PRISMA-ScR), or PRISMA 2020 and Synthesis Without Meta-analysis guideline. Web of Science, PubMed, Medline and ProQuest Central will be searched for the articles from the database inception to 2021. Two reviewers will independently select eligible studies and extract specified data. The numeric data will be analysed with R statistical software. The text data will be analysed with NVivo wherever applicable.

Ethics and dissemination: This study will review the literature of big data research related to both environmental health and health services. Ethics approval is not required as all data are publicly available and involves confidential personal data. We will disseminate our findings in a peer-reviewed journal.

Prospero registration number: CRD42021202306.

Keywords: biotechnology & bioinformatics; health services administration & management; occupational & industrial medicine; public health.

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Conflict of interest statement

Competing interests: None declared.

Figures

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Figure 1
Flowchart diagram for study selection.
See this image and copyright information in PMC

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