Open AccessBig Data in Context: Addressing the Twin Perils of Data Absenteeism and Chauvinism in the Context of Health Disparities Research
Author(s) -
Edmund W. J. Lee,
Kasisomayajula Viswanath
Publication year - 2020
Publication title -
jmir. journal of medical internet research/journal of medical internet research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.446
H-Index - 142
eISSN - 1439-4456
pISSN - 1438-8871
DOI - 10.2196/16377
Subject(s) - chauvinism , big data , health equity , public health , context (archaeology) , health informatics , data science , absenteeism , leverage (statistics) , public relations , political science , psychology , computer science , medicine , data mining , social psychology , geography , nursing , archaeology , politics , law , machine learning
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.