Big Data in Context: Addressing the Twin Perils of Data Absenteeism and Chauvinism in the Context of Health Disparities Research

Edmund W. J. Lee · Kasisomayajula Viswanath

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Big Data Technologies and Applications Ethics and Social Impacts of AI Health disparities and outcomes

Abstract

Recent advances in the collection and processing of health data from multiple sources at scale-known as big data-have become appealing across public health domains. However, present discussions often do not thoroughly consider the implications of big data or health informatics in the context of continuing health disparities. The 2 key objectives of this paper were as follows: first, it introduced 2 main problems of health big data in the context of health disparities-data absenteeism (lack of representation from underprivileged groups) and data chauvinism (faith in the size of data without considerations for quality and contexts). Second, this paper suggested that health organizations should strive to go beyond the current fad and seek to understand and coordinate efforts across the surrounding societal-, organizational-, individual-, and data-level contexts in a realistic manner to leverage big data to address health disparities.

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2016Big data analytics: Understanding its capabilities and potential benefits for healthcare organizations 2018Potential Biases in Big Data: Omitted Voices on Social Media 2017Big Data Science: Opportunities and Challenges to Address Minority Health and Health Disparities in the 21st Century 2013Social media use by community-based organizations conducting health promotion: a content analysis 2016An Argument for Ecological Research and Intervention in Health Communication

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