Institutional Shadow Bodies: Problems in Mental Health Information Seeking

• In Event: The Interpretive, Affective, and Ethical Work of Big Data in Health Care and Medicine - I

Abstract

Providing a robust account of data flows in mental health care requires a multi-faceted discussion of the barriers that surface in everyday struggles to access resources. These barriers include persistent stigma against seeking mental health care; structural inequalities of race, class, gender identity, sexuality and privilege; and the incomplete and informalized systems of transferring and translating necessary information for care. Rather than distinct obstacles to seeking care, these barriers are intertwined, overlapping and profoundly local. This project follows the messy paths of data about mental health care through a localized investigation of institutions charged with providing resources. Drawing on semi-structured interviews with mental health providers in Philadelphia, this study explores the gaps in access to services and information for mental health. In particular, we examine the contingent, contested, and constricted nature of such information, which is subject to interpretation (sometimes misinterpretation) and structural barriers. Following Balka and Star (2016), we present shadow bodies (partial and incomplete representations of a patient’s body derived from inchoate and scattered notes and data points) as a framework for understanding the ways that routinized information flows fail to capture the messiness, complexity and context of mental health needs. While Balka and Star theorized shadow bodies at the level of individual patients, we examine shadow bodies at multiple levels: institutional, physical, and infrastructural.

Authors

• Megan Bogia, Harvard University

• Chloé Nurik, University of Pennsylvania