Civic Data-Driven Innovation for Global Health and AI for All

Professor Buchan will explore how some of the world’s most pressing public health challenges might best be tackled with a global network of learning health systems – across 3 levels – linking patient, provider and population level insights and actions. He will give examples from Liverpool’s Covid-19 responses as to how the data-action gap was narrowed sufficiently to create the flywheel effect needed for ‘learning health systems’. For example, data-driven deployment and rapid evaluation of the world’s first voluntary mass testing with lateral flow devices, which reduced Covid-19 cases by a fifth and hospitalisation by a quarter. The underlying data science and engineering has persisted in Liverpool as core business after the pandemic via an NHS “Data into Action” programme and University-hosted Civic Health Innovation Labs (CHIL). Professor Buchan will argue that society needs civic clusters of health and care services, academic and industry partners to train and test AIs in a systemic way, networked to allow health systems to borrow strength from each other automatically.Further, Professor Buchan will argue the need for a standard, interactive form of digital self – the Health Avatar – that improves self-care, provider services and science synergistically. He will explore ways that avatar/AI-driven bio-sampling might work at scale – showing that prevention, precision, payer-value need common data and interoperable AI to radically improve healthcare.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-08-15
DOI
https://doi.org/10.5281/zenodo.16882548
Primary Topic
COVID-19 Digital Contact Tracing
Type
article
Field-Weighted Citation Impact
0.00
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article

Civic Data-Driven Innovation for Global Health and AI for All

Zenodo (CERN European Organization for Nuclear Research)
COVID-19 Digital Contact Tracing
article

Civic Data-Driven Innovation for Global Health and AI for All

article en

Abstract

Professor Buchan will explore how some of the world’s most pressing public health challenges might best be tackled with a global network of learning health systems – across 3 levels – linking patient, provider and population level insights and actions. He will give examples from Liverpool’s Covid-19 responses as to how the data-action gap was narrowed sufficiently to create the flywheel effect needed for ‘learning health systems’. For example, data-driven deployment and rapid evaluation of the world’s first voluntary mass testing with lateral flow devices, which reduced Covid-19 cases by a fifth and hospitalisation by a quarter. The underlying data science and engineering has persisted in Liverpool as core business after the pandemic via an NHS “Data into Action” programme and University-hosted Civic Health Innovation Labs (CHIL). Professor Buchan will argue that society needs civic clusters of health and care services, academic and industry partners to train and test AIs in a systemic way, networked to allow health systems to borrow strength from each other automatically.Further, Professor Buchan will argue the need for a standard, interactive form of digital self – the Health Avatar – that improves self-care, provider services and science synergistically. He will explore ways that avatar/AI-driven bio-sampling might work at scale – showing that prevention, precision, payer-value need common data and interoperable AI to radically improve healthcare.

Zenodo (CERN European Organization for Nuclear Research)
Industry, innovation and infrastructure
Openalex Percentile: Top 39%
COVID-19 Digital Contact Tracing
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