Considerations for ethics review of big data health research: A scoping review.

Marcello Ienca,Samia Hurst,Christian Lovis,Effy Vayena,Godfrey Biemba,Milo Puhan,Agata Ferretti

doi:10.1371/journal.pone.0204937

Marcello Ienca, Samia Hurst + Show 5 more

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https://doi.org/10.1371/journal.pone.0204937

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Abstract

Big data trends in biomedical and health research enable large-scale and multi-dimensional aggregation and analysis of heterogeneous data sources, which could ultimately result in preventive, diagnostic and therapeutic benefit. The methodological novelty and computational complexity of big data health research raises novel challenges for ethics review. In this study, we conducted a scoping review of the literature using five databases to identify and map the major challenges of health-related big data for Ethics Review Committees (ERCs) or analogous institutional review boards. A total of 1093 publications were initially identified, 263 of which were included in the final synthesis after abstract and full-text screening performed independently by two researchers. Both a descriptive numerical summary and a thematic analysis were performed on the full-texts of all articles included in the synthesis. Our findings suggest that while big data trends in biomedicine hold the potential for advancing clinical research, improving prevention and optimizing healthcare delivery, yet several epistemic, scientific and normative challenges need careful consideration. These challenges have relevance for both the composition of ERCs and the evaluation criteria that should be employed by ERC members when assessing the methodological and ethical viability of health-related big data studies. Based on this analysis, we provide some preliminary recommendations on how ERCs could adaptively respond to those challenges. This exploration is designed to synthesize useful information for researchers, ERCs and relevant institutional bodies involved in the conduction and/or assessment of health-related big data research.

Highlights

The generation of digital data has drastically increased in the last years due to the ubiquitous deployment of digital technology as well as advanced computational analytics techniques [1, 2]
Data breakdown by medical speciality and field of medical application indicates that big data approaches have been discussed and evaluated in relation to several branches of medicine including neurology and psychiatry (n = 31), oncology (n = 17), cardiology (n = 8), medical
As the application of big data in healthcare [43] and the market size forecasts for big data hardware, software and professional services investments in the healthcare and pharmaceutical industry are growing steadily [44], there will be a parallel need to assess the impact of this expanding sociotechnical trend

Summary

Introduction

The generation of digital data has drastically increased in the last years due to the ubiquitous deployment of digital technology as well as advanced computational analytics techniques [1, 2]. The term big data is still vaguely defined. Considerations for ethics review of big data health research: A scoping review data with diverse levels of analysable structuration, coming from heterogeneous sources (online data, social media profiles, financial records, self-tracked parameters, etc.), produced with high frequency and which can be further processed and analysed using computational techniques. While the term big data has become nearly ubiquitous, there is controversy over what data volumes are sufficiently large to obtain the big data label. For example, suggested that data should be considered big when they cross the threshold of the conventional databases systems’ capacity in processing information [3]

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