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Accepted Paper:
Paper short abstract:
I will present the perspectives and concerns of cardiologists, data scientists and a platform developer regarding predictive algorithms and digital twin technologies. I will show how their actions to develop these technologies and underlying values, e.g., shape patients' roles and responsibilities.
Paper long abstract:
My PhD research is embedded in the MyDigiTwin consortium, a research initiative aiming to create a digital Twin platform where citizens, including patients, can compare their health data to big data references. The ambition of the technology promotors is to improve early detection and prevention, in this case of cardiovascular disease. As the development of these digital twins is still in R&D, I aim to discover how potential new roles, and responsibilities of citizens and physicians, including notions of ‘good care’, are inscribed in technology development.
Through interviewing cardiologists, data scientists and platform developers, I explored how they envision the added value of these technologies, and how they should be implemented in healthcare. I use the notion of ‘scripts’ to analyze how the envisioned functionalities of the technology enable and constrain the patients' actions.
I found that stakeholders had divergent ideas on the role of digital twins. Many stakeholders characterized it primarily as a tool to be adopted or disseminated by cardiologists or other medical professionals. Hence, they aim to improve the interpretability and validity of the algorithms to raise clinicians' trust. Here, the responsibility for care and disseminating information to patients remains primarily with physicians. Another perspective contests this and advocates digital twins to be a tool for patients. They focus on making the scientific information and predictions by the algorithms accessible and understandable. Subsequently, responsibility for health is shifted towards the patient. I will discuss how power asymmetries within the consortium, shape the design of digital twins.
Digital transformations of diagnosis and diagnostic moments
Session 1 Friday 19 July, 2024, -