This webinar will explore how digital technologies are changing paediatric healthcare, focusing on how emerging technological solutions can enhance patient experiences, improve diagnostic accuracy, expand healthcare accessibility, and empower both young patients and their families through innovative digital platforms and patient-centred approaches.

Key themes:

• What is the current state of the digital health landscape in paediatrics?
• Current technological innovations in paediatric care.
• Emerging trends and breakthrough technologies. 
• How can we develop inclusive digital solutions for paediatric care? 
• Addressing healthcare disparities through technology.
• Culturally sensitive digital health interventions.
• Accessibility strategies for diverse paediatric populations.
• How can digital health technology act as an enabler in paediatric care? 
• Telemedicine and remote patient monitoring.
• Mental health digital platforms for children
• Assistive technologies in paediatric care.

Speakers:

• Paul Dimitri, Professor of Child Health and Consultant in Paediatric Endocrinology, Sheffield Children's NHS Foundation Trust
• Susan Shelmerdine, Children's Imaging Expert & Academic, The Royal College of Radiologists
• Venkat Reddy, Clinical Director, Children, Young People and Families Directorate, Cambridgeshire and Peterborough NHS FT, Officer for Digital Health and Technology, Royal College of Paediatrics and Child Health

Key Discussion Points

1. The Big Picture: Paediatric Health Technology

• Children: 25% of population, 100% of the future – early interventions are critical.

• Challenges in scaling paediatric technology due to small commercial market and diverse age needs.

• Importance of collaboration, consortium models, and creating scalable solutions.

• Successful funding journey from £50k seed to £50M+ leveraged for paediatric tech.

• Upcoming National Centre for Child Health Technology (Sheffield, 2026) to centralize innovation with children’s voices at its core.

2. AI in Paediatric Imaging (Fracture Detection)

• Fractures: common but often missed (up to 10% in ED).

• AI shows promise as a decision-support tool, particularly aiding less-experienced clinicians.

• Limited real-world evidence; AI struggles with rare bone diseases and subtle fracture types.

• Need for more studies on AI’s impact on clinical workflow, safeguarding (abuse detection), and economic viability.

• Risk of “automation bias”: will clinicians overlook non-fracture pathologies if AI focuses only on fractures?

• PPIE (Patient and Public Involvement & Engagement) insights: patients demand transparency, consent, accuracy, and human oversight.

3. Digital Innovation in Autism Diagnosis & Care

• Pre-COVID autism assessment was heavily in-person and slow; COVID forced rapid digitization.

• Remote video assessments (BOSA) and parent-guided play therapy (PACT) showed success but faced digital exclusion challenges.

• AI applications are emerging:

  • Video analysis tools (e.g., Cognoa) for early autism screening.

  • AI speech pattern recognition and movement analysis show high accuracy but need validation.

  • AI can reduce diagnostic inequality, identifying girls and minority children often missed.

• Emphasis on early intervention, routine data surveillance, and supporting families without waiting for formal diagnoses.

4. Practical Tips for Involving Children in Research & Tech Development

• “No technology for us, without us” – children’s involvement is essential, not optional.

• Effective methods: co-design workshops, child advisory groups, creative engagement.

• Children often understand digital tech better than adults and offer valuable insights.

• Resources like RCPCH’s "Recipe for Involvement" and the Alan Turing Child AI Consortium were recommended.

5. Cross-Cutting Themes

• Inclusive innovation must balance technological potential with ethical, practical, and social considerations.

• Collaboration between industry, academia, NHS, and children themselves is key.

• Scaling solutions requires robust data infrastructure, economic models, and policy alignment.

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