Open AccessSocial determinants of health in the Big Data mode of population health risk calculation
Author(s) -
Rachel Rowe
Publication year - 2021
Publication title -
big data and society
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.244
H-Index - 37
ISSN - 2053-9517
DOI - 10.1177/20539517211062881
Subject(s) - public health , big data , population , social determinants of health , health promotion , public relations , asset (computer security) , economics , sociology , business , political science , health care , medicine , environmental health , economic growth , computer security , computer science , nursing , operating system
Amidst the climate of crisis surrounding the rise in opioid-related overdose in the USA, early in 2019, Google and Deloitte launched ‘Opioid360’. Here came a platform combining browser histories, credit, insurance, social media, and traditional survey data to sell the service of risk calculation in population health. Opioid360's approach to automating risk calculation not only promised to identify persons ‘at risk’ of opioid dependence, but also paved the way for broader applications anticipating common chronic diseases and coordinating logistical operations involved in pandemic response. Beginning with this experimental platform, this paper develops an analysis of the Big Data mode of risk calculation - an epistemological and political shift that involves technology companies, investors, insurers, governments, and public health institutions. The analysis focuses on the re-emergence of ‘social determinants of health’ (SDOH) in the rhetoric accompanying novel analytic platforms that estimate, calculate, and compute individual health risks. While the treatment of SDOH has always been a site of political contestation within the discipline of public health, powerful interests are crystallising around the concept and instrumentalising it in platforms that sell algorithmic prediction. Silicon Valley's breed of asset-oriented technoscience appears not only to be amplifying the behaviouralist elements of public health. Among the stakes of the Big Data mode is the paradoxical retreat from changing social conditions that contribute to the prevalence of health and illness in populations; and instead, the promotion of an apparatus for pricing and exchanging individual risk or excluding from services those who bear risk most acutely.