From the American College of EpidemiologyEthics, big data and computing in epidemiology and public health
Introduction
It has been more than 15 years since the original 2000 American College of Epidemiology (ACE) Ethics Guidelines [1] were published. Since then, specialized fields of epidemiology (e.g., genetic and molecular epidemiology) have emerged, and as has awareness that epidemiology is closely interconnected with other fields (e.g., health information technology, global health and noncommunicable diseases). These advances have changed the profession of epidemiology, introducing numerous concepts related to big data and computing. Since the Guidelines' original publication, additional ethical issues in the context of specialized fields of epidemiology have emerged and presented challenges. To address this need, the Ethics Committee hosted a symposium session at the 2016 Epidemiology Congress of the Americas held in Miami, FL, June 21–24, 2016. This article presents a summary and further discussion of that symposium session. The session addressed three topics: (1) the international policy and human rights implications of big data and computing (B.M.K.); (2) the fallacy of “secondary” data sources (L.M.L.); and (3) the benefits, risks, and duties of citizens to contribute to big data (K.W.G.). This article exemplifies the Ethics Committee's ongoing consultative efforts to highlight contemporary topics in the area of ethics and epidemiology relevant to professional epidemiologists. We are targeting a diverse audience of health care researchers including epidemiologists, health care informatics specialists, geneticists, health care providers, policymakers, and others who work with, or are interested in working with big data.
Section snippets
Big data: potential and challenges
The current technological landscape permits the digitization and storage of unprecedented amount of data from many sources, including smart phones, text messages, credit card purchases, online activity, electronic medical records, and global positioning system data. Many of these data sources contain personal information both related and unrelated to health, including for example, geographic location, health or social security number, and credit card number. Various forms of health information
Evolving epidemiology data sources
Historically, we have divided the sources of health information into two categories: primary and secondary. “Primary data” refer to data collected for a specific research question using an instrument (e.g., a survey or laboratory test) designed or chosen to optimize validity. “Secondary data” refers to existing data that were collected for a purpose other than the specific research question at hand. Secondary data might come from routine public health surveillance, population-based health
Evolving access and regulatory landscape
The motivation for the use of big data includes the efficiencies gleaned from creating “economies of scale.” First, data are rapidly generated from genetic, medical, socioeconomic, social media, and geospatial sources; disease and other types of registries; primary care and community clinics; and from data sources that include air pollution, climate, and contaminated soils and water. Second, these data are able to be stored in internet-based centers which would allow government agencies the
Ethical principles revisited
The ethical dimensions of big data and population health research are not unlike the common ethical principles in epidemiology research and practice. Whatever our data source, we must uphold the ethical principles that reflect what we value—minimizing harms while maximizing benefits, ensuring just distribution of burdens and benefits, respect individual autonomy through informed consent, privacy and confidentiality, build trust, and maintain scientific rigor [1]. To honor these ethical
Societal contributions to big data
Epidemiology has always been information-intensive. Indeed, its very existence depends on the collection and analysis of data and information. Much of that data and information relates, pertains, or is somehow linked to individual people, their families, or their communities. Given the goals and successes of epidemiology and other population health sciences and the sustainability and quality of health care systems, one should infer that the collection and analysis of data and information is
Ethical framework to address big data
Traditional approaches to the issues of big data have relied on ethical principles requiring protection from presumed harm from biomedical research. A new and more positive approach to address the challenges of big data emphasizes human rights. Indeed, this is the basis for the Framework for Responsible Sharing of Genomic and Health-Related Data established by the Global Alliance for Genomics and Health (GA4GH; https://genomicsandhealth.org/). At the core of the Framework is the understanding
Conclusion
The purpose of this article is a “call to action” in the area of ethics, big data, and computing in epidemiology and public health. Also, to provide readers with information about the activities of the college and to give readers of the Annals of Epidemiology a broad perspective on a recent major epidemiological issue. Our intentions for this article and subsequent ethics and epidemiology publications as part of the work of the Ethics Committee are for these resources to be nimble, accessible,
Next steps
Our plenary session dealt with ethics, big data, and computing in epidemiology and public health from the perspective of our speakers including research and teaching expertise in the areas of ethics, epidemiology, genomics, health policy, legal dimensions, bioethics, and bioinformatics. Additional perspectives may not have been adequately addressed in the plenary session including but not limited to the ethical considerations surrounding study methods/design, data collection/analysis, standards
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