Civic Data-Driven Innovation for Global Health and AI for All
Year: 2025
Type: article
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.
Author: Buchan, Iain
Language: English
Subfield: Health Informatics
Field: Medicine
Domain: Health Sciences
Open Access status: green
OpenAlex ID: W6950190465
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