Health Ethics and Policy Laboratory, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland.
Institute for Ethics, History and the Humanities, Faculty of Medicine, University of Geneva, Geneva, Switzerland.
PLoS One. 2018 Oct 11;13(10):e0204937. doi: 10.1371/journal.pone.0204937. eCollection 2018.
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.
生物医学和健康研究中的大数据趋势能够实现大规模和多维的异质数据源聚合和分析,最终可能带来预防、诊断和治疗方面的益处。大数据健康研究的方法学新颖性和计算复杂性为伦理审查带来了新的挑战。在这项研究中,我们使用五个数据库进行了文献范围的综述,以确定和绘制与健康相关的大数据对伦理审查委员会(ERC)或类似机构审查委员会的主要挑战。最初共确定了 1093 篇出版物,经过两名研究人员独立进行摘要和全文筛选后,有 263 篇被纳入最终综合分析。对综合分析中所有文章的全文都进行了描述性数值总结和主题分析。我们的研究结果表明,尽管生物医学中的大数据趋势有可能推进临床研究、改善预防和优化医疗服务提供,但仍需要仔细考虑一些认识论、科学和规范性挑战。这些挑战与 ERC 的组成以及 ERC 成员在评估与健康相关的大数据研究的方法学和伦理可行性时应采用的评估标准都有关联。基于这项分析,我们就 ERC 如何适应这些挑战提供了一些初步建议。这项探索旨在为从事健康相关大数据研究的开展和/或评估的研究人员、ERC 和相关机构提供有用的信息。