Open AccessRisks and Opportunities to Ensure Equity in the Application of Big Data Research in Public Health
Author(s) -
Paul S. Wesson,
Yulin Hswen,
Gilmer Valdez,
Kristefer Stojanovski,
Margaret A. Handley
Publication year - 2022
Publication title -
annual review of public health
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.239
H-Index - 144
eISSN - 1545-2093
pISSN - 0163-7525
DOI - 10.1146/annurev-publhealth-051920-110928
Subject(s) - big data , health equity , equity (law) , data science , public relations , context (archaeology) , public health , computer science , political science , medicine , data mining , geography , nursing , law , archaeology
The big data revolution presents an exciting frontier to expand public health research, broadening the scope of research and increasing the precision of answers. Despite these advances, scientists must be vigilant against also advancing potential harms toward marginalized communities. In this review, we provide examples in which big data applications have (unintentionally) perpetuated discriminatory practices, while also highlighting opportunities for big data applications to advance equity in public health. Here, big data is framed in the context of the five Vs (volume, velocity, veracity, variety, and value), and we propose a sixth V, virtuosity, which incorporates equity and justice frameworks. Analytic approaches to improving equity are presented using social computational big data, fairness in machine learning algorithms, medical claims data, and data augmentation as illustrations. Throughout, we emphasize the biasing influence of data absenteeism and positionality and conclude with recommendations for incorporating an equity lens into big data research.