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Biomedical investment in digital technologies has flooded society with staggering volumes of data, spurring high-tech innovations such as performance metrics, clinical algorithms, and public data dashboards. In examining the social life of data artifacts, scholars draw from actor-network theory to emphasize data's ability to represent social reality while circulating within it, while others suggest formal data models fail to account for invisible relations on the ground. Yet little work has examined the role of human reflexivity in crafting complex human-data configurations in practice, such as how situated human actors relate to data representations within the social reality they intimately know themselves. Drawing on ethnographic fieldwork of Electronic Health Records (EHRs) and data analytics integration from inside the digital safety-net, this article shows how health care workers recognize data simultaneously capture, obscure, and envision their everyday work of caring for the marginalized. By demonstrating how the same data point may in one context demonstrate good care while in another obscure it, these findings suggest need to broaden attention to the social life of data beyond delimited focus on standards and their travels. Digital technologies do not simply capture the social, but multiply it. Biomedical data then do not have one social life, but many., (Copyright © 2021 The Author. Published by Elsevier Ltd.. All rights reserved.)

Background: Recent research and policy initiatives propose addressing the social determinants of health within clinical settings. One such strategy is the expansion of routine data collection on patient Race, Ethnicity, and Language (REAL) within electronic health records (EHRs). Although previous research has examined the general views of providers and patients on REAL data, few studies consider health care workers' perceptions of this data collection directly at the point of care, including how workers understand REAL data in relation to health equity., Objective: This qualitative study examines a large integrated delivery system's implementation of REAL data collection, focusing on health care workers' understanding of REAL and its impact on data's integration within EHRs., Results: Providers, staff, and administrators expressed apprehension over REAL data collection due to the following: (1) disagreement over data's significance, including the expected purpose of collecting REAL items; (2) perceived barriers to data retrieval, such as the lack of standardization across providers and national tensions over race and immigration; and (3) uncertainty regarding data's use (clinical decision making vs. system research) and dissemination (with whom the data may be shared; eg, public agencies, other providers, and insurers)., Conclusion: Emerging racial disparities associated with COVID-19 highlight the high stakes of REAL data collection. However, numerous barriers to health equity remain. Health care workers need greater institutional support for REAL data and related EHR initiatives. Despite data collection's central importance to policy objectives of disparity reduction, data mandates alone may be insufficient for achieving health equity., Competing Interests: The authors declare no conflict of interest., (Copyright © 2021 Wolters Kluwer Health, Inc. All rights reserved.)