Following the algorithm: How epidemiological risk-scores do accountability

Abstract

Epidemiological risk scores are calculative devices that mediate and enact versions of accountability in public health and preventive medicine. This article focuses on practices of accountability by following a cardiovascular risk score widely used in medical counselling in Germany. We follow the risk score in the making, in action, and in circulation to explore how the score performs in doctor-patient relations, how it recombines epidemiological results, and how it shapes knowledge production and healthcare provision. In this way, we follow the risk score’s various trajectories – from its development at the intersection of epidemiology, general medicine and software engineering, to its usage in general practitioners’ offices, and its validation infrastructures. Exploring the translations from population to individual and back that are at work in the risk score and in the primary prevention of cardiovascular disease, we examine how versions and distributions of accountability are invoked and practiced as the score is developed and put to use. The case of a simple risk score used in everyday counselling brings into relief some key shifts in configurations of accountability with emerging versions of ‘health by the algorithm’. While there is an increasing authority of algorithmic tools in the fabric of clinical encounters, risk scores are interwoven with local specificities of the healthcare system and continue to be in the making.

Datafication and accountability in public health: Introduction to a special issue

“…In their contribution to this volume, Amelang and Bauer (2019) present a study of a cardiovascular risk score and its translation to preventive medicine in Germany. They analyze how epidemiological risk scores work as ‘accountability devices’ and show how they, despite their algorithmic character, continue to be in the making.…”

Making Sense of Algorithms: Relational Perception of Contact Tracing and Risk Assessment during COVID-19

“…In this paper, we examine how Chinese people make sense of Health Code, the contract tracing and risk assessment algorithm released by the Chinese government in cooperation with private technology companies. Echoing a growing scholarly focus on exploring people's perception of the algorithms in practice at different sites and in different contexts (Amelang and Bauer, 2019;Brayne and Christin, 2020;Christin, 2017), we demonstrate how people perceive Health Code along three axes: privacy issues, technology use, and implementation.…”

“…The designers, creators and owners of a technology offer only a partial account of the meaning a technology has in society, and algorithms are no different. They change over time through dynamic interplay not only with the data they receive and the coders making updates and edits, but also the heterogeneity of public individuals who use it (Amelang and Bauer, 2019;Brayne and Christin, 2020). Indeed, in recent years public cognizance of algorithms has advanced immensely.…”

Seeing like a State, Enacting like an Algorithm: (Re)assembling Contact Tracing and Risk Assessment during the Covid-19 Pandemic

“…Algorithms influence more and more aspects of our life. They are widely applied in settings such as city management, policing, and medicine (Amelang and Bauer 2019;Brayne 2017;Houston, Gabrys, and Pritchard 2019). They progressively shape what information we acquire, what loan we can get, what job we obtain, and what life chances we have (Fourcade and Healy 2017;Mittelstadt et al 2016;Rona-Tas 2020).…”

“…Outputs themselves do not have any power. Algorithms gain their power in their enrollment of other actors for authoritative use (Amelang and Bauer 2019;Christin 2020). In the case of Health Code, it refers to the process of collecting contact and symptom data on the one hand, and utilization of its risk assessment on another.…”