AI for Scaling Digital Public Health: From Centres of Academic Excellence to Scaled Adoption

Objectives, themes and relevance

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This workshop will explore mechanisms to building pathways that allow digital health and AI innovation to scale, leveraging from the opportunities that Centres of Academic Excellence provide to test and validate solutions and move beyond concepts faster into scalable, investable solutions.

• Understand why most digital health innovations fail to scale
• Examine the role of evidence pipelines in enabling adoption and, ultimately, investments
• Explore how AI supports end-to-end pathway innovation
• Learn how funders, regulators, health systems policy and decision-makers and academia must co-design innovation

Relevance

The digital health sector suffers from a lack of scaling pathways. Numerous digital health pilots emerge yearly, in almost every health system in the world. Yet very few scale up and are widely adopted. While AI-innovation has rapidly evolved, adoption remains slow, heavily fragmented and unequally distributed. Innovations collapse in the “valley of death” not because they fail to address a real need but, often, the surrounding system is unprepared for their adoption. Innovation is then a system-level problem. 

This workshop proposes to address this issue by reimagining the innovation pathway placing Centres of Academic Excellence at the centre of the innovation process, not as knowledge producers but, rather, as a space for validating innovations, sandbox for testing regulatory environments, a broker for building partnerships and launchpad for scalable innovation adoption.

Drawing on the experience from the Global Business School for Health and the Global Health and Digital Innovation Foundation, this session will examine why pilots fail to scale and propose a pathway for innovation that enables adoption and sustainability.

Key thematic areas

Innovation pathways for digital public health; research translation and knowledge transfer; regulatory designs from design; AI-enabled pathways for innovation and feedback systems; cross-sectoral innovation

Intended audience

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This workshop targets the following audiences: academics and PhD researchers; Innovation Leads; Health Systems Leaders and Policy makers; regulators; digital health founders.

Expected Outcomes

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The Workshop is an opportunity to discuss key principles and drivers of innovation in health systems and identify key enablers to scale digital public health including opportunities arising from artificial intelligence. Participants will leave with:

• Understanding of systems-based view of innovation
• New concepts and a practical translation framework for digital public health innovations that scale by design
• Understanding the role of artificial intelligence in supporting and accelerating the innovation pathways for digital public health innovations and a roadmap for sustainable, scalable digital public health goods
• Expanded professional networks and discussions with panellists and participants on scaling challenges, innovation, etc.

Format and schedule (provisional)

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The session will set the scene with an opening message, followed by short abstract presentations that will provide the background to the panel discussion. The session will be moderated and will encourage interactive debates with the audience.

Time	Activity
0-10 min	Opening message: Why pilots don’t scale? Dimitrios Kalogeropoulos
10-40 min	Setting the scene – Principle for scaling digital public health innovation in complex health systems Meike Schleiff & Clara Aranda-Jan
40-50 min	Introduction to Panellists
50-80 min	Mini panel
80-90 min	Closing insights & next steps

Speakers

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