Y.6.PK.1. Advancing health equity with digitalisation and AI across urban and rural contexts
Abstract
Health inequities remain a persistent challenge across both urban and rural settings, driven by differences in healthcare workforce availability, infrastructure, and socioeconomic conditions. Addressing these disparities is a key priority in global and European public health strategies. At the same time, rapid advances in digitalisation and artificial intelligence (AI) create new opportunities to improve prevention, promotion, access, coordination, and quality of care. However, they also raise critical concerns regarding bias, fairness, and unequal implementation. This workshop examines under which conditions digitalisation and AI can support health equity in urban and rural settings, with a specific focus on their implications for system resilience, accessibility, and fairness. Bringing together interdisciplinary expertise from epidemiology, social sciences, digital health, law, and machine learning (ML), the session adopts a structured, multi-level perspective that links methodological innovation for improving health equity in urban and rural settings. The session follows a coherent analytical progression combining short presentations with a moderated interactive discussion. First, methodological approaches using ML are presented to measure health inequities in access to and quality of healthcare across rural and socioeconomically deprived areas. Second, practical experiences with implementing digital health and AI services in rural settings are discussed, focusing on their potential to mitigate workforce shortages. Third, a systems perspective examines how AI tools can improve coordination and continuity of care while remaining sensitive to contextual differences between urban and rural environments. Fourth, ethical and rights-based perspectives address questions of data justice, algorithmic bias, and the implications of AI for fundamental health rights, particularly in underserved populations. By explicitly linking evidence, implementation, and normative considerations, the workshop provides complementary insights for policymakers, researchers, and practitioners. Hereby, the workshop explicitly links methodological innovation with real-world application and policy considerations. Building on this, participants will be invited in the second part of the session to reflect on key questions, including the transferability of digital solutions across contexts, risks of reinforcing existing inequities, and requirements for equitable implementation. Participants will leave with a clearer understanding of the risks and opportunities associated with digitalisation and AI in different contexts, such as public health domains and living environments in rural or urban settings, as well as identifying conditions under which these technologies can support equitable and sustainable public health system transformation across Europe.
Key messages: • Digitalisation and AI can reduce health inequities, but only if implementation addresses bias, access, and contextual differences.
• Interdisciplinary approaches are essential to ensure digital health solutions are equitable across urban and rural settings.
Related
- Advancing health equity in cancer care through collaborative research agenda development: a provincial workshop guided by patient-oriented research in Alberta, Canada
- Gender-transformative action as a strategy for health system strengthening: a framework for advancing equity, accountability, and resilience.
- Emerging information technologies across the autism service and prevention continuum: a narrative review of screening, diagnosis, intervention, and health equity
- Poverty-modulated tree equity shapes health burdens across U.S. cities
- Assessment of sex inequalities in current tobacco smoking across 165 countries: a WHO Health Equity Assessment Toolkit analysis.
BibTeX
@article{ecoledeshautesetudesensantepubliquefrance2026y6pk1,
title = {{Y.6.PK.1. Advancing health equity with digitalisation and AI across urban and rural contexts}},
author = {Ecole des Hautes Etudes en Santé Publique (France), EUPHA Digital Health and AI section and Nolwenn Le Meur and Stefan Buttigieg},
journal = {The European Journal of Public Health},
year = {2026},
month = oct,
doi = {10.1093/eurpub/ckag169.711},
url = {https://doi.org/10.1093/eurpub/ckag169.711},
note = {CC BY-NC 4.0},
}
RIS
TY - JOUR
TI - Y.6.PK.1. Advancing health equity with digitalisation and AI across urban and rural contexts
AU - Ecole des Hautes Etudes en Santé Publique (France), EUPHA Digital Health and AI section
AU - Nolwenn Le Meur
AU - Stefan Buttigieg
PY - 2026
DA - 2026/10/01
JO - The European Journal of Public Health
DO - 10.1093/eurpub/ckag169.711
UR - https://doi.org/10.1093/eurpub/ckag169.711
AB - Health inequities remain a persistent challenge across both urban and rural settings, driven by differences in healthcare workforce availability, infrastructure, and socioeconomic conditions. Addressing these disparities is a key priority in global and European public health strategies. At the same time, rapid advances in digitalisation and artificial intelligence (AI) create new opportunities to improve prevention, promotion, access, coordination, and quality of care. However, they also raise critical concerns regarding bias, fairness, and unequal implementation. This workshop examines under which conditions digitalisation and AI can support health equity in urban and rural settings, with a specific focus on their implications for system resilience, accessibility, and fairness. Bringing together interdisciplinary expertise from epidemiology, social sciences, digital health, law, and machine learning (ML), the session adopts a structured, multi-level perspective that links methodological innovation for improving health equity in urban and rural settings. The session follows a coherent analytical progression combining short presentations with a moderated interactive discussion. First, methodological approaches using ML are presented to measure health inequities in access to and quality of healthcare across rural and socioeconomically deprived areas. Second, practical experiences with implementing digital health and AI services in rural settings are discussed, focusing on their potential to mitigate workforce shortages. Third, a systems perspective examines how AI tools can improve coordination and continuity of care while remaining sensitive to contextual differences between urban and rural environments. Fourth, ethical and rights-based perspectives address questions of data justice, algorithmic bias, and the implications of AI for fundamental health rights, particularly in underserved populations. By explicitly linking evidence, implementation, and normative considerations, the workshop provides complementary insights for policymakers, researchers, and practitioners. Hereby, the workshop explicitly links methodological innovation with real-world application and policy considerations. Building on this, participants will be invited in the second part of the session to reflect on key questions, including the transferability of digital solutions across contexts, risks of reinforcing existing inequities, and requirements for equitable implementation. Participants will leave with a clearer understanding of the risks and opportunities associated with digitalisation and AI in different contexts, such as public health domains and living environments in rural or urban settings, as well as identifying conditions under which these technologies can support equitable and sustainable public health system transformation across Europe. Key messages: • Digitalisation and AI can reduce health inequities, but only if implementation addresses bias, access, and contextual differences. • Interdisciplinary approaches are essential to ensure digital health solutions are equitable across urban and rural settings.
SN - 1101-1262
SN - 1464-360X
ER -