Session Submission Summary

The Learning Health System as a Socio-Technical System of Translation

Thu, August 30, 4:00 to 5:30pm, ICC, C2.5

Session Submission Type: Traditional (Closed) Panel

Abstract

The governance of life through algorithms and big data, e.g. ‘social sorting’ in automated systems, is a core STS subject. Whilst increasing amounts of personal data (in health, forensics, education, etc.) are generated at scale and deposited in databases, often a comprehensive approach to their analysis, use, and transparent governance remains lacking. This panel contributes to debates on the use of large-scale data agglomeration, analysis, and application in the life sciences, specifically in healthcare, by considering the ways in which STS can inform emergent systems using the example of Learning Health Systems (LHS).
This panel will focus on LHS as a recent reframing of health information infrastructure and health care delivery that promises to leverage the significant amounts of patient and practice-generated data in efforts to reduce costs and medical error, and to improve health outcomes. However, data may be incomplete or proprietary, or may not reflect the realities of the publics they mean to serve thus falling short on the promissory note. This panel explores socio-technical imaginaries of LHS, and considers the role of STS in anticipatory analysis of social and ethical aspects of the emergence of various forms of such systems. The panel will be structured as one session of five speakers presenting empirical work, and one session as a roundtable to consider how STS may reveal the sociotechnical, political and ethical dimensions of emerging LHS and its role, if any, in informing governance.

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