The digital transformation of the health sector is at full speed, fueled by policy and growth strategies in the EU, the US, and elsewhere. Envisioned as a revolutionary pathway towards data-driven medical innovation, healthcare democratization, and patient empowerment, digital health has been endorsed by governments across the globe often with disregard for the adverse impacts of digital poverty, biased datasets, and algorithmic unfairness. Digital health technologies’ potential to enhance access to AI-mediated diagnoses, personalised treatments and transformative medicines and cures (e.g. gene editing) is frequently deployed to heighten expected benefits and downplay risks. But digital medical devices and data-driven systems developed using deep learning are often trained and tested on unrepresentative populations, with discriminatory consequences (e.g. racially encoded biases in an algorithm assessing kidney function reduce Black patients' access to kidney transplants).

Calls for a solidarity-based approach to data governance posit that the benefits and harms deriving from digital data use should be collectively borne by society to preclude data colonialism, earn public trust, overcome data diversity deficits, and distribute the benefits of data-driven innovation fairly. Moving towards digital health justice also requires concerted efforts to anticipate and prevent algorithmic biases and, where necessary, to uncover, disassemble, and redress algorithmic injustices. The involvement of lay publics in designing and implementing digital health technologies and data-driven systems has been claimed to be imperative for realising these goals. Yet there are many questions in relation to public involvement in digital health principles and policy that remain underexplored: who is (dis)engaged, what forms of citizenship and belonging are enacted through public involvement and how do these relationships reconfigure interactions between and (re)produce inequalities among the multiple stakeholders (e.g. patients, health professionals, decision-makers, data curators, IT experts) shaping the digital health landscape. Further empirical research is also needed to surface and understand the underlying democratic deficits in digital health governance and its social, legal, political, and personal implications, particularly for groups vulnerable to histories of exclusion and misrepresentation.

The wealth of questions and concepts emerging in connection to health digitisation span various disciplinary fields and could benefit from deeper theoretical grounding. This Research Topic seeks contributions that weave conceptual development and refinement with empirical studies on digital health from across the fields of Sociology, Anthropology, Political Science, Philosophy and Ethics. Potential contributors are invited to propose original research articles, conceptual analysis papers, review articles or policy and practice reviews addressing topics related to health digitisation.

Themes of interest include but are not restricted to the following:
• Digital health governance gaps, public (dis)trust in digital health, and data diversity deficits
• The social, ethical, legal, and personal implications of algorithmic decision-making, including how algorithmic biases are uncovered, exposed, and resisted during algorithmic training and up to the point of care (e.g. in clinical settings)
• The disruption, (re)shaping or transformation of patterns of exclusion through digital health technologies and services
• The emergence of new forms of advocacy, community mobilization, participation, and citizenship linked to health digitization and the (re)production of inequalities
• Opportunities, tensions, and limits to public involvement in digital health governance
• Participatory approaches to digital health technologies’ design, implementation, usage, and adaptation.

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